research issues in wireless communication

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https://www.nist.gov/programs-projects/future-wireless-communications-systems-and-protocols

Future Wireless Communications Systems and Protocols

5G and beyond communications will include several technical advancements that enable innovative applications such as wireless backhauling, Augmented/Virtual Reality (AR/VR), 8K video streaming and sensing. This project is focused on system-level insights and performance analyses of emerging wireless protocols and standards. Our goal is to use measurement-based models for wireless propagation in the design, the development and the evaluation of next generation wireless communications systems. We work with industry and the research community to improve the accuracy and availability of system-level modeling tools dedicated for such purposes. 

Description

Millimeter wave communication systems and protocols.

5G and beyond wireless communication systems make use of the Millimeter-Wave (mmWave) band.  While this band offers unprecedented throughput thanks to the large bandwidth available, it also suffers from larger propagation loss compared to the sub-6 Ghz band. This characteristic imposes a complete rethinking of the traditional communication paradigm, i.e., omni-directionality. Indeed, to guarantee adequate received signal power, mmWave systems employ directional beams formed by antenna arrays, i.e., beamforming. Beamforming focuses the power (both in transmission and in reception) towards the chosen direction by properly steering the antenna elements of the antenna array. 

The directionality of the communication poses a number of new challenges, including : 

Beamforming requires to select (Beamforming Training) and adapt (Beamforming Tracking) the directional beams to use between two nodes that are willing to communicate. Beamforming Training and Tracking is of paramount importance for mmWave communications as it drives the performance of the communication links. The initial approach, introduced in IEEE 802.11ad and 3GPP release 15, has been to perform an exhaustive search among all the possible beams combinations. However, there are obvious scalability issues with this approach, especially in the context of MIMO systems. Therefore more efficient beamforming Training/Tracking algorithms are needed.   

Most wireless and application protocols have been designed with omnidirectional communications in mind. on the other hand, highly directional communications will impose drastic changes on radio-resource allocation schemes in order to take full-benefits of the directionality of the communication. 

The usage of multiple antennas to compensate for the high propagation loss, enables the PHY to exploit spatial multiplexing techniques to achieve even greater throughput. The design of MIMO precoding and equalization algorithms requires channel estimation techniques tailored to the mmWave propagation characteristics.  

A realistic platform that accurately characterizes the propagation environment is vital to evaluate and develop efficient beamforming, radio-resource allocation and channel estimation algorithms and models, as well as antenna array systems that will address these challenges. Until now, research and development has been conducted separately using tools and platforms that are not integrated and generally not compatible. This presents a major impediment to the development and deployment of future generation millimeter wave systems. Our response is to develop a realistic platform that includes accurate characterization of the channel propagation environment: The Quasi-Deterministic (Q-D) Framework. 

Quasi-Deterministic (Q-D) Framework  

While the development of standard specifications for IEEE 802.11ad/ay is complete, innovative research using IEEE 802.11ad/ay devices is still challenging due to the prohibitive cost of test-bed equipment and the lack of open-source and flexible platforms. The NIST Q-D framework aims to overcome some of these challenges by providing researchers in the mmWave community a set of high-fidelity tools to evaluate and better understand the inter-workings of the IEEE 802.11ad/ay protocols.  

Evaluating performance end-to-end often requires the following: 

An accurate representation of the channel model at 60 GHz. 

A flexible and high-fidelity antenna model.  

PHY model and digital baseband transceiver PHY abstractions. 

A system-level simulator that implements the MAC and PHY specifications of IEEE 802.11ad/ay and that includes realistic channel models, antenna models, and PHY layer abstractions.  

To this end, we developed in collaboration with IMDEA and the University of Padova five different open-source tools as displayed in Figure 1.  

The NIST Q-D Channel Realization Software 1 : This Matlab tool implements the channel between nodes/antennas pairs in the network using ray tracing and Q-D methodology ( link ). The channel is described through the Multi-Path Components (MPCs) properties such as number of MPCs, path loss, delay, angles of arrival and departures. User can define its own 3D environment and nodes mobility/rotations. This software includes a visualizer to display the generated MPCs between each pair of nodes. 

The Codebook Generator 2 : This Matlab tool generates Phased Antenna Arrays properties such as steering vectors and Antenna Weight Vectors based on user-defined Phased Antenna Arrays characteristics (geometry, number of elements, etc.).  

The Integrated Sensing and Communication Physical Layer Model 3 : This tool is a Matlab implementation enabling baseband link-level simulation of millimeter-wave (mm-wave) wireless communication and sensing systems. ISAC-PLM models the Physical Layer (PHY) of IEEE 802.11ay, including a growing set of features, such as Multi-User Multiple-Input Multiple-Output (MU-MIMO) link level simulation, IEEE 802.11ay single carrier (SC)/orthogonal frequency-division multiplexing (OFDM) waveform generation, synchronization, channel estimation, carrier frequency offset (CFO) estimation and correction. It provides an end-to-end simulation platform, including transmitter and receiver, importing the channel realized by the Q-D Channel Realization Software.   The software allows to compute several metrics, such as bit error rate, packet error rate, target range and target velocity estimation accuracy.  It can be used to export lookup tables of packet error rate varying SNR, in AWGN or mm-wave channel, for different modulation and coding schemes.

The ns-3 802.11ad/ay with Q-D channel implementation 4 : The ns-3 system-level simulator has been modified to include IEEE 802.11ad/ay functionalities. Our implementation imports the channel realized by the NIST Q-D Channel Realization Software, the antenna characteristics produced by the Codebook Generator, and includes the PHY layer abstraction by the NIST 802.11ay PHY to obtain high-fidelity system-level evaluation.  

The NIST Q-D Interpreter 3 : IEEE 802.11ad/ay system-level performance highly depends from the beamforming applied at the transmitter/receiver side. To help interpretation of the beamforming training results, we developed a python 3D visualizer that takes as an input the beamforming results obtained in ns-3 and displays the antenna patterns for a transmitter/receiver communication.  

____________________________________________________________________

• Developed by NIST in collaboration with University of Padova SIGNET Group
• Developed by IMDEA WNG Group
• Developed by NIST
• Developed by IMDEA WNG Group in collaboration with NIST

Integrated Communication and Sensing Systems

Sensing and communication systems are competing technologies, sharing the same spectrum and using similar hardware components. The idea of Integrated Sensing And Communication (ISAC) systems has recently gained the attention of research and standardizations communities. Co-designing sensing and communication systems allows to efficiently re-use the spectrum and the hardware resources, for example reusing the communication waveforms and devices to enable sensing applications. For this reason, integrated communication and sensing has been identified as an enabling technology for 5G/6G, and the next-generation Wi-Fi system.

The ubiquitous presence of WiFi devices in our everyday life offers a unique opportunity to enable innovative applications such as presence detection, gesture recognition, or person identification, re-using existing WiFi devices. IEEE has recently (September 2020) started a new task group, TGbf, to extend the current IEEE 802.11ay high throughput functionalities, with cm-level sensing resolution.

IEEE 802.11bf envisions to enable sensing for a wide range of applications such as gesture recognition, number of persons in a room, breathing activity, etc. The requirements for these applications can be vastly different, e.g., detect an object proximity requires less amount of information and accuracy compared to detect a person and identify its pose.

The design of integrated communication and sensing systems poses several challenges including:

• Resource allocation: The sensing accuracy performance will be strongly dependent on the availability and update frequency of the channel measurements. However, as IEEE 802.11bf re-uses the communication link, sending and exchanging sensing information can be solely seen as an overhead from a WiFi performance point-of-view, reducing throughput and increasing latency. In this case, the larger the overhead, the better the sensing accuracy will be at the cost of a lower transmission data rate.
• Cooperation and scheduling:  cooperative sensing (CSENS) is foreseen as a key enabler of high-resolution sensing. CSENS will use multiple sensing devices collaborating to capture additional information about the surrounding environment (e.g., in case of blockage between a sensing device and a target, another sensing device could still be able to sense the target). CSENS will also incur additional overhead as it will not only require more entities in the sensing framework but will also raise new challenges such as synchronization between the multiple entities, establishment of a distributed sensing measurements, fusion of partial sensing information, etc.
• Beamforming training at mm-wave: the optimization of the beamforming training to maximize the communication performance creates very narrow beams. The limited field of view does not allow to have sense the entire environment.

The NIST ISAC Framework  

The Q-D channel model realization software will be used as a baseline to create the NIST ISAC Channel Realization software by introducing the concept of targets, i.e., person or object to sense. While the NIST ISAC Channel Realization software can support different target models, our current study focus on human targets, which can enable several applications such as presence detection and localization.  The human motion is modeled with kinematic models, which approximate the human body as a collection of joints. The NIST 802.11ay PHY is enhanced with dedicated ISAC sensing signal processing to obtain range-doppler information, which allows the detection of moving objects. Finally, the NIST Q-D interpreter is extended to allow the visualization of the interaction between the wireless signal and the human target, while displaying the correspondent range-doppler map.

PUBLICATIONS

Beamforming training.

• M. Kim, T. Ropitault, S. Lee, N. Golmie, H. Assasa, and J. Widmer, "A Link Quality Estimation-based Beamforming Training Protocol for IEEE 802.11 ay MU-MIMO Communications", in IEEE Transactions on Communications, Vol. 69, No. 1, January 2021. 
• M. Kim, T. Ropitault, S. Lee and N. Golmie, "Efficient MU-MIMO Beamforming Protocol for IEEE 802.11ay WLANs", in IEEE Communications Letters, Vol. 22, No. 1, January 2019. 
• Y. Kim, S. Lee and T. Ropitault, "STS Adaptation for Beamforming Training of Asymmetric Links in IEEE 802.11ay-based Dense Networks", in Proceedings of IEEE Vehicular Technology Conference (VTC Spring 2020), June 2020. 
• Y. Kim, S. Lee, and T. Ropitault, "Adaptive Scheduling for Asymmetric Beamforming Training in IEEE 802.11ay-based Environments", in Proceedings of IEEE Wireless Communications and Networking Conference (WCNC 2019), April 2019. 

PHY Layer Evaluation

• J. Zhang, S. Blandino, N. Varshney, J. Wang, C. Gentile and N. Golmie, "Multi-User MIMO Enabled Virtual Reality in IEEE 802.11ay WLAN," 2022 IEEE Wireless Communication and Networking Conference.
• A. Bodi, J. Zhang, J. Wang, and C. Gentile, " Physical-Layer Analysis of IEEE 802.11ay using a Channel Fading Model from Mobile Measurements", in IEEE  International Conference on Communications (ICC 2019), May 2019. 
• N. Varshney, J. Zhang, J. Wang, A. Bodi and N. Golmie, "Link-Level Abstraction of IEEE 802.11ay based on Quasi-Deterministic Channel Model from Measurements," in Proc. of 2020 IEEE Vehicular Technology Conference (VTC2020-Fall), April 2020.  
• S. Blandino, T. Ropitault, A. Sahoo and N. Golmie, "Tools, Models and Dataset for IEEE 802.11ay CSI-based Sensing," 2022 IEEE Wireless Communication and Networking Conference.

T. Ropitault, S. Blandino, N. Varshney and N. Golmie, "Q-D simulation & Modeling framework for sensing", presented at TGbf.

S. Blandino, T. Ropitault, N. Varshney and T. Ropitault, "A preliminary channel model using raytracing to detect human presence", presented at TGbf

Hybrid MAC Performance

• C. Pielli, T. Ropitault, N. Golmie, and M. Zorzi, “An analytical model for CBAP allocations in IEEE 802.11ad,” in IEEE Transactions on Communications, vol. 69, no. 1, 2021.
• J. Chakareski, M. Khan, T. Ropitault, and S. Blandino, “6DOF virtual reality dataset and performance evaluation of millimeter wave vs. free-space-optical indoor communications systems for lifelike mobile VR streaming,” in 2020 54th Asilomar Conference on Signals, Systems, and Computers, 2020.
• T. Azzino, T. Ropitault and M. Zorzi, "Scheduling the Data Transmission Interval in IEEE 802.11ad: A Reinforcement Learning Approach," 2020 International Conference on Computing, Networking and Communications (ICNC), May 2020. 
• C. Pielli, T. Ropitault, and M. Zorzi    "The Potential of mmWaves in Smart Industry: Manufacturing at 60 GHz", in International Conference on Ad-Hoc Networks and Wireless, AdHoc Now 2018, pp. 64-67. 

The Q-D framework

• H. Assasa, N. Grosheva, T. Ropitault, S. Blandino, N. Golmie, and J. Widmer, “Implementation and evaluation of a wlan IEEE 802.11ay model in network simulatorns-3,” in Proceedings of the Workshop on Ns-3, WNS3 ’21, (New York, NY, USA), 2021.
• H. Assasa, T. Ropitault, S. Lee and N. Golmie, "Enhancing the ns-3 IEEE 802.11ad Model Fidelity: Beam Codebooks, Multi-Antenna Beamforming Training, and Quasi-Deterministic mmWave Channel", in Workshop on ns-3 (WNS3 2019), June 2019. 
• H. Assasa, J. Widmer, J. Wang, T. Ropitault, and N. Golmie, "An Implementation Proposal for IEEE 802.11 ay SU/MU-MIMO Communication in ns-3", in Workshop on Next-Generation Wireless with ns-3 (WNG 2019), June 2019 
• H. Assasa, J. Widmer, T. Ropitault, A. Bodi, and N. Golmie, "High Fidelity Simulation of IEEE 802.11 ad in ns-3 Using a Quasi-deterministic Channel Model", in Workshop on Next-Generation Wireless with ns-3 (WNG 2019), June 2019 

Ultra-Dense networks

• M. Kim, T. Ropitault, S. Lee and N. Golmie, "A Throughput Study for Channel Bonding in IEEE 802.11ac Networks," in IEEE Communications Letters, vol. 21, no. 12, pp. 2682-2685, Dec. 2017. 
• T. Ropitault and N. Golmie, "ETP algorithm: Increasing spatial reuse in wireless LANs dense environment using ETX," 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC). 
• T. Ropitault, "Evaluation of RTOT algorithm: A first implementation of OBSS_PD-based SR method for IEEE 802.11ax," 2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC) 

Major Accomplishments

• Participating in IEEE working groups (TGay, TGbf).
• Over 20 peer-reviewed publications on the evaluation and improvement of IEEE 802.11ax/ad/ay.
• Developed (in collaboration with IMDEA) the first open-source ns-3 IEEE 802.11ay implementation. Main features include MIMO Beamforming Training and Quasi-Deterministic propagation model

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• Published: 15 February 2023

Wireless communications sensing and security above 100 GHz

• Josep M. Jornet   ORCID: orcid.org/0000-0001-6351-1754 1 ,
• Edward W. Knightly 2 &
• Daniel M. Mittleman   ORCID: orcid.org/0000-0003-4277-7419 3  

Nature Communications volume  14 , Article number:  841 ( 2023 ) Cite this article

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• Fibre optics and optical communications
• Terahertz optics

The field of sub-terahertz wireless communications is advancing rapidly, with major research efforts ramping up around the globe. To address some of the significant hurdles associated with exploiting these high frequencies for broadband and secure networking, systems will require extensive new capabilities for sensing their environment and manipulating their broadcasts. Based on these requirements, a vision for future wireless systems is beginning to emerge. In this Perspective article, we discuss some of the prominent challenges and possible solutions which are at the forefront of current research, and which will contribute to the architecture of wireless platforms beyond 5G.

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Introduction.

Over the last two decades, wireless communications exploiting radio-frequency waves have become a ubiquitous feature of modern life. With each subsequent advance in technology has come countless new tools and capabilities, transforming the way we live. Now, as the rollout of 5G systems continues, researchers are considering the design of subsequent generations of networks, as well as visions for future implementations of Wi-Fi, Bluetooth, and other short-range wireless systems. It is worth noting that most previous wireless platforms, from the days of Marconi, have been confined to operate in the frequency range below a few gigahertz. Yet, rapid growth in demand for wireless services has changed the game; we are now forced to consider using higher frequencies, in order to find the bandwidth needed to support continued exponential growth in wireless traffic. One of the novel features of modern Wi-Fi and 5G variants such as IEEE 802.11ay 1 involves their ability to access higher frequencies in the millimeter-wave range, above 10 GHz. As these systems mature, it is therefore natural that research interests have now begun to turn to even higher frequencies. Like the mmWave Wi-Fi and 5G bands, the use of these higher frequencies is motivated in large part by the desire for access to larger bandwidth, and the associated higher data rates. Indeed, although the maximum data rate that can be supported within the 5G standard exceeds 7 gigabits per second (Gbps), more than an order of magnitude larger than the fastest 4G data rate, the huge (and ongoing) growth in demand for wireless access has made it clear that even higher rates will be needed in the future 2 .

For this reason, the cutting edge of wireless research lies at frequencies above 100 GHz 3 , often referred to as the “terahertz (THz) range”. Most of this research is focused on a few specific broad spectral bands, including the waveguide D band (110−170 GHz) which has been previously employed for television broadcasts during the Beijing Olympics 4 , and the higher frequency bands defined by the recent IEEE 802.15.3d standards document (252−322 GHz) 5 . These frequencies are well beyond even the highest millimeter-wave bands included in today’s Wi-Fi and 5G standards.

Opening this relatively unexplored realm of the electromagnetic spectrum will involve a host of challenging new research problems. In this Perspective article, we discuss some of the interesting issues facing researchers in the race to develop ultra-high-frequency wireless systems. Many of these challenges are associated with aspects of the physics of the interaction of these high-frequency waves with the world. Above 100 GHz, system designers will need to consider some physical regimes that have not previously been relevant for legacy wireless systems, or even in some cases for the mmWave bands of 5G. We first consider a few of the more prominent issues associated with these new operating regimes. We note that near-infrared or visible light optical communication systems, operating at even higher frequencies, are also of significant research interest, but are beyond the scope of this article.

Some challenges

One aspect of this discussion can be understood from the Friis equation, which describes the power received by an antenna P RX in a line-of-sight point-to-point wireless link. Expressed in dB, this relation is:

Here, P TX is the power generated by the transmitter, G T and G R are the transmitter and receiver antenna gains respectively (in dBi), and the last term, the free-space path loss (FSPL), describes the decrease in power per unit area of an expanding electromagnetic wavefront in terms of the propagation distance D and the wavelength λ 6 . This term becomes dominant at high frequencies. When considering an increase in the frequency by a factor of 100 (for example, from the typical 4G cellular frequency of 2.8 GHz to 280 GHz, a frequency in the 802.15.3d standard), the FSPL increases by 40 dB (see Fig.  1 ). Because the FSPL is smaller at lower frequencies, high-gain antennas are not always required; it is possible to operate a wireless link in which the transmitter broadcasts to a wide range of angles. For example, typical cellular antennas often span a 120° broadcast sector. At higher frequencies, the increasing FSPL can be offset with high-gain antennas, which concentrate the radiated power into a smaller angular range. Above 100 GHz, these broadcasts begin to act more like beams, propagating in a well-defined direction with low divergence 7 . There are of course many possible options for high-gain antennas, but translating these to the THz range is not always trivial, due to (among other things) the requirement of broadband operation. For example, phased array antennas are a well-established technology at lower frequencies, employing tuned phase shifters for each of the antenna elements in an array to implement beam steering or wavefront shaping. This approach, also being used in 5G systems, becomes more challenging as we design systems with larger fractional bandwidths. Phase shifters commonly operate at a fixed wavelength or frequency. When injecting a broadband signal to a phase shifter, the different frequency components experience different phases, resulting in beam squinting. Instead, a true-time-delay operation, in which all the signal frequency components experience the same phase delay, may be required in place of a simple phase shifter for individual elements of an antenna array 8 . The design of active efficient high-gain antennas with suitable form factors and efficiency remains an important research challenge.

The attenuation of a propagating radio wave due to both free-space path loss and atmospheric absorption, for an assumed propagation distance of 100 m, at a temperature of 15 °C and relative humidity of 59%, using a standard atmospheric model (see [10, 11]). The shaded areas indicate the range of frequencies corresponding to legacy wireless systems, the 5G millimeter-wave range, and the THz spectrum. The hatched areas are the two bands of significant interest for communications mentioned in the text.

A second important distinction between low and high-frequency propagation involves atmospheric attenuation (which has been neglected in Eq. ( 1 ) above). This loss also increases with frequency, in the form of several spectrally narrow absorption peaks riding on top of a smoothly increasing continuum absorption. In terrestrial systems, all of the important absorption lines above 120 GHz are due to rotational and ro-vibrational excitations in gas-phase water molecules 9 , 10 , some of which are strong enough to inhibit long-range propagation for frequencies near their line centers. These discrete absorption lines, therefore, serve to break the spectrum up into a series of broad bands which are well suited for transmission over longer distances, in which the relatively small continuum background (due to water dimers and other species) is the dominant contribution to atmospheric loss 11 . In fact, these absorption resonances need not always be considered a hindrance; with careful frequency tuning, they can be exploited for enhanced wireless security 12 . Despite some older conventional wisdom, the atmosphere is not opaque to radiation in the 100–1000 GHz range; if the H 2 O lines are avoided, point-to-point links in the km range are certainly feasible 4 , 13 , 14 , 15 . Inclement weather also contributes additional loss; 16 , 17 however, these may be tolerable under certain conditions, and indeed terahertz beams appear to be more robust against atmospheric scintillation and certain weather conditions (e.g., fog) than, for example, free-space optical signals in the near-infrared 18 .

A third issue of note is of the roles of scattering from surfaces and of material absorption. When considering interactions with surfaces, the characteristics of the scattered field are determined by the roughness of the surface, in comparison with the wavelength of the radiation, as well as the extent to which the surface absorbs (rather than scatters) the incoming radiation. A smooth (compared to lambda) surface reflects like a mirror; a rough surface produces a diffuse (not strongly directional) scattered wave. In a typical indoor environment, for instance, conventional wireless systems operate at frequencies where absorption is low in many materials, and where many surfaces are smooth compared to the (longer) wavelength. So, it is generally assumed that there can be many multiply-scattered paths between the transmitter and receiver, producing a rich scattering environment in which the field at any location is a stochastic superposition of many different wavelets. In contrast, the wireless channel at THz frequencies is quite different 19 . Typically a propagating wave experience much higher attenuation when interacting with most surfaces, due to absorption losses in the materials 20 , and commonly encountered surfaces can either be smooth or rough, in comparison with the (much smaller) wavelength (see Fig.  2 ). As a result, both indoor 21 and outdoor 22 environments are typically much more sparse, with fewer paths connecting the transmitter to receiver. Because many surfaces are smooth enough to act like mirrors, scattering in a specular direction (i.e., angle of reflection = angle of incidence) can often be dominant. Researchers have therefore been able to exploit ray tracing as an accurate means for predicting and understanding signal paths in THz propagation simulations 21 , 23 . In addition, due to the opacity of many objects including people, issues such as blockage of the direct line-of-sight (LOS) path can pose challenges for maintaining connectivity, as would be the case with a laser-based free-space optical link. However, due to the millimeter-scale wavelength, steering around such blockage events by exploiting a specular reflection from a surface in the environment is more feasible at THz frequencies 24 . Even non-specular reflections (diffuse scattering from rough surface 25 ) can be employed to maintain a link, although obviously with a lower signal-to-noise ratio 26 and added dispersion 27 . The shift from omnidirectional broadcasts with rich scattering to directional beams with sparse paths also has important implications for the security of such communication channels, rendering eavesdropping more challenging. Yet, vulnerabilities due to scattering still remain 28 , 29 , 30 , and must be considered in system design.

Measured bit error rate (BER) for a 2-m link which incorporates a specular reflection from a cinderblock wall, as shown in the top left photo. The effects of absorption and scattering are separated by measuring the link on the bare wall (blue points), the same wall with a conformal metal foil coating that eliminates penetration into the cinderblock (red points), and a flat metal plate which eliminates both absorption and scattering (black points). The photo images in ( a ) depict the three situations corresponding to the measurements in ( b ). Reprinted from Ma, J., Shrestha, R., Moeller, L. & Mittleman, D. M.; Channel performance of indoor and outdoor terahertz wireless links. APL Photon. 3, 051601 (2018)., with the permission of AIP Publishing.

Defining wavefronts and waveforms

These various novel features of THz waves force us to rethink common practices in wireless communication systems and, at the same time, open the door to new strategies not available in traditional wireless networks in microwave and even millimeter-wave bands.

On the one hand, relating to the spatial behavior of terahertz radiation, the requirement for high-gain directional antennas strongly suggests the use of radiating structures that are much larger than the wavelength. By recalling that the far field of an antenna occurs for distances greater than 2 × D 2 /λ, where D is the antenna’s largest dimension, it is likely that many wireless systems at terahertz frequencies will operate in the near field. For example, a 10 cm antenna, such as a dish antenna or an antenna array, at 130 GHz has a far-field distance of 8.6 m and the same antenna size at 300 GHz has a far-field distance of 20 m, larger than many indoor environments in which a THz LAN could be employed. This is a major distinction from lower frequency wireless systems, which generally operate exclusively in the far field.

This result has multiple consequences. First, wireless propagation, channel, and multi-user interference models, which have been derived under the assumption of far-field operation 6 , cannot simply be repurposed for higher frequency systems. Indeed, many models for terahertz communications continue to neglect to capture near-field effects 31 . Second, most algorithms behind the control of smart directional antenna systems, including beamforming and beam-steering, have also generally been developed under the far-field assumption 32 . For many possible antennas, including large radiating structures such as the increasingly popular intelligent surfaces 33 , this is not the case even at lower frequencies.

To overcome this latter challenge, there are several recent works 34 , 35 that explore beam focusing as a way to achieve beamforming-like capabilities but in the near field. In beam focusing, the weights or phases at different antenna elements are set to emulate that of a dielectric lens. While this is a valid solution for static scenarios, tracking and constantly changing the point on which the signal needs to be focused results in a significant overhead in terms of signaling the channel state information.

Going beyond beam focusing, if we are ready to abandon common practices and assumptions such as that the generated signal can be approximated as a plane wave or a Gaussian directional beam, operating in the near field opens the door to a host of new possibilities in wavefront engineering (whereby wavefronts we refer to the spatial intensity and phase profiles of the signals being transmitted). Although many of these ideas have been considered for some time, for instance in the optics community, it is only with the advent of directional links that they may reach their full potential in wireless systems. For example, at lower frequencies where received signals can often contain rich multi-path components, it can be challenging to exploit polarization diversity to double channel capacity. In contrast, such strategies are likely to be far more effective with a line-of-sight directional link 36 .

Other important examples may arise from considerations of more exotic wavefronts which can be prepared in the near field of an emitting aperture. For instance, by adopting Bessel beams, i.e., beams whose intensity profile in space can be described by a Bessel function of a certain order 37 , a beam can focus (in the near field) not at a point but along a line. This can drastically simplify the operational requirements in mobile networks. Moreover, Bessel beams exhibit a self-healing property, i.e., even when partially blocked by an obstacle, they can recreate the original intensity and phase profile at a distance. Similarly, the use of accelerating beams such as Airy beams, which can be programmed at the origin to bend after a given number of wavelengths 38 , can also be utilized to overcome or minimize the impact of obstacles, a major problem for practical mobile terahertz communications and sensing systems. Figure  3 shows computed cross-sections of a few of these options, illustrating the dramatically different behavior that can be obtained in the near field of a transmitting aperture.

Calculated electric field (left) and intensity (right) patterns for three engineered near-field radiation patterns: a focused Gaussian beam (top), a Bessel beam (middle), and an accelerating Airy beam (bottom).

Further, all these beams can also be engineered to carry orbital angular momentum (OAM). Different OAM mode orders are orthogonal, enabling the multiplexing of streams at the same frequency, at the same time, and in the same direction 39 . As discussed in the literature 40 , OAM multiplexing can be seen as a particular case of multiple input multiple output (MIMO) communications, but one in which channels are orthogonal from the start (and not because of how multi-path propagation affects them). Moreover, while these wavefronts can be generated using static phase masks (such as axicons for Bessel beams or spiral phase plates for different OAM modes), the same can be achieved by the utilization of dense antenna arrays 41 , 42 , which (unlike phase masks) could also in principle be dynamically reconfigurable 43 , 44 . We note that the security vulnerabilities associated with using such unusual wavefronts could be quite different from those associated with conventional side-lobe eavesdropping or jamming attacks 45 , and could offer new opportunities for enhancing link security 46 .

On the other hand, relating to the frequency behavior of terahertz radiation, there is a need for waveforms, the temporal variations of the transmitted signals, that can overcome various challenges, including those introduced by frequency-dependent molecular absorption in the channel (see Fig.  1 ) and by increasingly prominent hardware imperfections (e.g., nonlinearities in broadband frequency up- and down-converting systems). As of today, there is no answer to the question of what waveform will be used for 6G terahertz systems. While the common solutions at lower frequencies, including orthogonal frequency division modulation/multiplexing (OFDM), single-carrier OFDM also known as DFT spread OFDM, or the recently proposed orthogonal time-frequency-spatial modulation (OTFS) 47 could be adapted to terahertz frequencies, there are also other options, including waveforms unique to the terahertz band that enable applications not available at lower frequencies. For example, very short pulses, just a few hundreds of femtoseconds long, as in terahertz time-domain spectroscopy (THz-TDS) platforms 48 or BiCMOS impulse radiators 49 , can be utilized to implement low-complexity non-coherent modulation which is able to support a large number of users transmitting at very large data rates over a short range, provided that proper equalization techniques are implemented to compensate for the effects of multi-path propagation 2 , 50 . This is particularly useful when the encoding purposely biases the transmission of zeros over the transmission of ones to overcome the impact of noise and interference. At the same time, for longer communication distances, the broadening of the molecular absorption lines results in narrower communication bandwidths at longer distances. This effect can be exploited to use the channel as a filter and help to separate simultaneous data streams at the same frequency for users in the same direction but at different distances (see Fig.  4 ) 51 . Moreover, if spectral efficiency and peak data rates are not the drivers, there are other ways to exploit the available bandwidth above 100 GHz, for example in the form of secure communication and spectrum sharing techniques based on ultra-broadband spread spectrum 52 .

Leveraging the spectral filtering effect of atmospheric water vapor absorption resonances to implement hierarchical bandwidth modulation, in which nearby users can access the full bandwidth of the transmitted signal, while more distant users, whose channel bandwidth is narrower, only employ the smaller range at the center of the spectrum.

Ultimately, we envision that the spatial and spectral aspects of terahertz signals should not be considered separately, but instead, the spatial wavefront and temporal waveform should be jointly designed to optimize the performance of systems and unleash this spectrum. For example, as discussed above, different wavefronts are commonly generated with different types of phase masks which can be, in some cases, intrinsically narrowband. However, when trying to transmit ultra-broadband signals through such structures, the resulting wavefronts are far from ideal. To prevent this, frequency-selective pre-distortion of the waveforms being transmitted can be employed to ensure that the desired wavefront is produced over the entire bandwidth. This becomes even more important when producing complex wavefronts using arrays that approximate the lens response with a discrete (rather than continuous) pattern.

Components for the physical layer

Of course, the impact of the unique properties of terahertz radiation does not end with propagation, wavefronts, and waveforms. It will also influence the redesign of common devices in traditional systems for operation at higher frequencies and will open the door to novel hardware solutions that are not practical or even possible at lower frequency bands.

As one example, the small wavelength of terahertz waves leads to small fundamental resonant antennas (e.g., dipole, slots, or patches). When used individually, these antennas exhibit low effective areas resulting in the very high spreading losses discussed above. However, it is this small size of radiating structures that allows us to integrate very large numbers of antennas in a very small footprint. For example, in a 10 cm × 10 cm footprint, one could in principle integrate 200 × 200 (40,000!) dipole antennas at 300 GHz spaced λ/2 apart. The fabrication of such large on-chip arrays is a significant challenge, but rapid progress is being made 43 , 44 .

While such antennas or radiating elements can be envisioned, there are other components besides the antennas that would need to be integrated into the chip (potentially through 3D stacking), depending on the application that is needed. For example, a true-time delay controller per element would be needed to engineer the aforementioned broadband wavefronts. Moreover, if the goal were to develop transmitting or receiving antenna arrays that can support MIMO communications, each antenna would require a complete RF chain (i.e., a local oscillator, mixer, filter, amplifier, and data converter). Integrating such arrays is a major bottleneck with today’s electronic and photonic transceiver technologies due to their size, as well as packaging and thermal constraints. Arrays with element spacing greater than λ/2 produce far-field radiation patterns with grating lobes, which could be leveraged for multi-beam systems, but are otherwise not desirable. Instead, antenna array architectures aimed at minimizing the number of RF chains while minimally impacting the array capabilities have been proposed, such as the array-of-sub-arrays architecture 47 , in which separate RF chains drive separate subsets of fixed or only phase-controlled antenna elements 53 . Other solutions could be the adoption of signal processing techniques for sparse antenna arrays, which so far have generally been used only in the context of imaging 54 , 55 .

There are also a number of new technologies that only become available when operating at terahertz frequencies (or above). For instance, researchers have proposed the use of graphene to build plasmonic transceivers and antennas that intrinsically operate in the terahertz band 56 . Graphene, which supports the propagation of surface plasmon polariton (SPP) waves at terahertz frequencies and at room temperature, can be used (1) as a two-dimensional electron gas where plasma waves oscillations at terahertz frequencies occur 57 , (2) as a plasmonic waveguide where the properties of SPP waves can be electrically tuned 58 , and (3) as the active element of a nano-patch antenna, able to convert SPP waves into free-space electromagnetic waves 59 , all with devices that are significantly smaller than the free-space wavelength. While being sub-wavelength in size leads to low radiation efficiencies, this can be compensated through dense integration of the elements. Moreover, the sub-wavelength nature of each radiator also leads to negligible mutual coupling as long as elements are placed more than a plasmonic wavelength apart. From a signal processing perspective, being able to sample space with a resolution higher than λ/2 leads to both oversampling gain and the ability to engineer wavefronts (such as those noted above) with much higher accuracy than traditional λ/2-spaced arrays could ever support 60 .

The shift to higher frequencies also offers fascinating opportunities to engineer devices with advanced functionality, which are either impossible or impractical at lower frequencies. For example, recent research has focused on leaky-wave antennas, based on guided wave devices which incorporate a mechanism to permit some fraction of the guided wave to ‘leak’ out into free space. This leaked signal manifests a strong coupling between the frequency of the radiation and the direction in which it propagates. Leaky-wave antennas are neither new nor exclusive to the terahertz range 61 . However, the wavelength scale, and spectral bandwidth, of signals at these high frequencies means that such devices can operate in a unique regime of form factor and functionality, such that it is now plausible to consider new roles for these components in wireless systems. Leaky-wave components can be valuable for multi-frequency signal distribution (i.e., multiplexing) 62 and for sensing tasks such as the radar-like location of objects within a broadcast sector 63 . If both transmitter and receiver are equipped with a leaky-wave antenna, they can together provide a fast and efficient method for simultaneously determining both the angular location of a mobile receiver and its angular rotation relative to the transmitter 64 . Building on this approach, recent work has demonstrated arrays with true-time-delay elements to accomplish similar localization tasks 65 . One could even envision creating arrays of leaky-wave devices for enhanced wavefront control. This is another idea which has previously been considered at lower frequencies 66 , but which could find new possibilities in a different frequency regime.

The challenging propagation of terahertz waves and, in particular, the issue of blockage, motivates the consideration of strategies to improve reliability. As noted above (see Fig.  2 ), non-line-of-sight paths are available, even at these high frequencies, although they are sparse relative to what is typically encountered at lower frequencies. One interesting approach relies on the development of devices that can help us engineer not only the transmitter and receiver but also the propagation environment (i.e., the channel). This idea has inspired a great deal of research in the general area of intelligent reflecting surfaces, which could be distributed throughout an indoor network to facilitate signal distribution and overcome transient blockage events. As with other devices discussed here, an intelligent reflecting surface (IRS), such as those based on programmable reflectarrays, has been considered previously at lower frequencies 67 . However, at frequencies above 100 GHz and with current applications in mind, the benefits that such structures bring to wireless systems may now prove too valuable to ignore. Today, there are numerous different technologies under consideration as the basis for IRS devices. For example, smart surfaces have been proposed which replace conventional switching elements employed at lower frequencies, such as varactor diodes, with graphene patches 56 . Dense reflectarrays with integrated switching elements have been designed and implemented in silicon CMOS 43 , 44 and in III-V semiconductor platforms using high-electron-mobility transistor (HEMT) structures 68 . We have also recently shown that array devices, in the hands of a clever adversary, can also open up interesting new security vulnerabilities (see Fig.  5 ) 69 . It is too early to tell how this interesting approach to engineering the broadcast environment will ultimately be achieved, but it is quite clear that any of these possible solutions would drastically change the way that networks are designed and operated.

A clever eavesdropper (Eve) can insert an engineered reflector, such as a flexible metasurface (photo) into the line-of-sight path between the transmitter (Alice) and the intended receiver (Bob), in order to direct a portion of the spectrum towards the eavesdropper (upper schematic). This low-profile attack would be difficult for Alice and Bob to detect, but would direct a significant signal toward Eve (lower panel).  Adapted from Zhambyl Shaikhanov, Fahid Hassan, Hichem Guerboukha, Daniel Mittleman, and Edward Knightly. 2022. Metasurface-in-the-middle attack: From Theory to Experiment. In Proceedings of the 15th ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec '22).© Association for Computing Machinery, New York, NY, USA, 257–267. https://doi.org/10.1145/3507657.3528549 .

Implications for the control plane

With the above considerations in mind, it becomes clear that networks of the future, which have the capability to exploit THz frequency bands, will operate quite differently from networks of today. One obvious example is that a transmitter, employing a narrow pencil-like beam, will need to know where to point it. This and other examples suggest that networks will require joint communications and sensing capabilities, and moreover that new approaches will be required for managing these capabilities in order to ensure high quality of service and efficient use of system resources.

As a first step, we note that radio sensing can have two purposes: The first purpose is to identify clients, devices, and objects in the environment, e.g., for presence detection and analysis of environmental objects and their mobility to optimize the signal-to-noise of wireless links 70 . The second purpose builds on the first and targets to understand the RF environment for network optimization, e.g., to localize uncontrolled sources of interference in order to avoid or null them. Today’s RF sensing applications are quite impressive and include monitoring people in a room behind a wall 71 and monitoring individual heart rate 72 . Unfortunately, today’s RF methods have two fundamental limits. First, their inputs are the gains and phases of the channel matrix H and they subsequently rely on the dimensionality of H for resolution. Thus, to improve resolution further, array sizes would need to approach a massive MIMO scale, thus incurring the corresponding issues of size, cost, power consumption, and computational requirements. Second, because these methods were designed to operate below 6 GHz, their wavelength is centimeter to decimeter scale, limiting resolution correspondingly 73 .

As noted above, the use of THz frequencies opens up a number of new possibilities for joint sensing and communications, with important implications for the functioning of the control plane of the network, which is responsible for functions such as beam alignment and spectrum management. For example, as mentioned above, a directive transmitter and receiver must dynamically align their beams toward each other. In today’s standards for both 5G and Wi-Fi, a serial sector sweep is used for initial beam alignment, to sequentially test different directions. This trial-and-error method becomes increasingly cumbersome as beams become narrower. In contrast, the aforementioned leaky-wave device can be used to rapidly track mobile clients by using the received spectral signature 64 to estimate the receiver’s relative angle from the transmitter (see Fig.  6 ), a scheme which can be generalized to three-dimensional localization 74 . As another example, with arrays of sub-wavelength elements, one can envision a centimeter-scale surface with ~1000 independently controllable devices. This high oversampling yields new possibilities for dual-purposing communication and sensing: not only could one realize classical communication capabilities (e.g., beamforming and nulling of interferers or enhancing security), but one could also realize sensor functions (e.g., localization of users) with the same device 75 .

An integrated circuit, fabricated in silicon CMOS, which realizes a leaky-wave antenna for single-shot localization of multiple users in a broadcast sector via broadband excitation of the angularly dispersive aperture. Figure adapted from H. Saeidi, S. Venkatesh, X. Lu and K. Sengupta, "THz Prism: One-Shot Simultaneous Localization of Multiple Wireless Nodes With Leaky-Wave THz Antennas and Transceivers in CMOS," in IEEE Journal of Solid-State Circuits, vol. 56, no. 12, pp. 3840-3854, Dec. 2021, https://doi.org/10.1109/JSSC.2021.3115407 . with permission of the authors under a Creative Commons license: https://creativecommons.org/licenses/by/4.0 .

Likewise, beam steering must also incorporate cases in which a direct line-of-sight path is not available. As discussed above, an IRS could be used to realize a reflected path thereby increasing coverage and avoiding blockage. However, building the device is not enough; in order to function properly, the network’s control plane must discover and configure this path, including properties of the IRS itself: for example, if the IRS provides a non-specular reflection, it must know the targeted incoming and outgoing angles. Since a network may alternate serving users in time, the IRS would need to reconfigure not only due to user mobility, but also according to which users are transmitting and receiving. Beam steering devices must also consider the new wavefronts described in Section 3. For example, in typical demonstrations of beams such as OAM 39 , the transmitter, and receiver are manually aligned and are typically placed broadside. To employ such wavefronts in a mobile network will require adaptation not only for location, but also for the relative orientations of the transmitter and receiver when they are not ideally oriented.

As noted above, the aforementioned techniques based on the idea of an IRS have previously been considered for use at lower frequencies, but their implementation takes on new urgency at these higher frequencies. In addition, there are some approaches which have been more widely employed at lower frequencies, and which can also offer valuable capabilities in the THz range. One good illustration is the assessment of angle-of-arrival for a mobile user via cooperative estimation of spatial correlations among multiple antennas, for example in a massive MIMO architecture. This possibility has recently been considered by Peng et al. 76 in the context of a THz network. Such legacy control-plane methods can play an important role, but will in general need some rethinking in view of the highly directional nature of transmissions in these networks, as well as the possibility (discussed above) that the user could be in the near field of the array.

Today’s wireless networks provide multi-user capabilities, in which an access point or base station transmits to (or receives from) multiple users simultaneously in order to increase aggregate data rate and decrease latency. Realizing this capability with THz frequencies will require two new advances. First, waveforms and modulation formats must be designed to support simultaneous transmission, incorporating that users will not be co-located and will be using directional transmissions. In some downlink cases, spatial separation of receivers combined with narrow beams may provide a simple starting point. Yet, for the uplink, and even for the downlink when users are close together, interference and co-stream management must be carefully controlled. Second, even if a network has the physical capability to realize a multi-user transmission, control plane mechanisms are needed to coordinate the transmission. Namely, the control plane must identify and localize the users, determine the appropriate spectrum and modulations to use, trigger the transmission at the correct time, and so on. In some cases, these functions are sufficiently similar to those of existing networks that comparable methods can be used; in other cases, entirely new protocols will need to be developed. For example, while traditionally medium access control protocols are driven by the transmitter, an alternative procedure based on receiver-initiated link synchronization, in which a receiver periodically polls potential transmitters as its antenna sweeps / scans the space, can increase the reliability and throughput and reduce latency 77 .

The many challenges discussed in this article have inspired a great deal of research over the last few years (only a small fraction of which could be included here). One challenge, not discussed above, involves the potential interference of wireless signals at these frequencies with existing (for the most part, passive) users involved in earth sensing or radio astronomy. Numerous research communities employ highly sensitive receivers to harvest information about the status of our atmosphere and the molecular composition of astronomical objects. It is critical that any active communication services that exploit frequencies above 100 GHz must be designed to avoid interference with these important existing communities 78 . Of course, because of the higher atmospheric attenuation and the high gain of transmitting antennas, issues of sharing and interference may be quite different at these high frequencies. More research is required, for example, to establish the limits for interference, or to demonstrate antenna configurations whose side lobes are designed to avoid interference with overhead satellites.

Unsurprisingly, the daunting nature of the technical challenges has also inspired some skepticism from some researchers in the field. A few have noted that R&D expenditures in THz systems from many of the major telecommunications companies remain only a small fraction of their total R&D budget. Of course, this is not surprising, since the market for these systems also remains tiny. At this juncture, one should not expect massive private sector investment in a technology that is probably at least a decade away. Another oft-stated concern relates to the need for such systems. Twenty years ago, a common refrain was that nobody would ever require frequency bands above 10 GHz for consumer applications; ten years ago, it was 60 GHz; today, with the emergence of the first commercial backhaul devices operating in D band 79 , the threshold has now moved to 140 GHz. In fact, we choose to regard this moving target as an optimistic indicator of the rapid progress in the field. This progress is embodied in exciting recent publications, including breakthrough new link demonstrations 80 , 81 and rapid advances in solid-state device technology 82 , 83 , 84 , 85 .

Of course, there are valid reasons for concern; the challenges discussed in this article are indeed formidable. Nevertheless, we feel that the research results of the last few years have established that THz technologies are a promising foundation for future needs in wireless networks, which seem likely to exploit these frequencies for at least some of their key functions 86 . While many open questions remain, there is at this point a clear and compelling motivation to pursue the goal of THz wireless.

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Acknowledgements

The authors gratefully acknowledge the assistance of Kaushik Sengupta, Hichem Guerboukha, and Duschia Bodet in assembling figures for this manuscript. D.M.M. acknowledges funding support from the US National Science Foundation (grant numbers 1923733, 1954780, 2148132, and 2211616) and the Air Force Research Laboratory (award number FA8750-19-1-0500). E.W.K. acknowledges funding support from Cisco, Intel, the US National Science Foundation (grant numbers 1955075, 1923782, 1824529, and 2148132), and the Army Research Laboratory (grant W911NF-19-2-0269). J.M.J. acknowledges funding support from the US National Science Foundation (grant numbers 1955004, 2011411, and 2117814) and the Air Force Research Laboratory (award number FA8750-19-1-0200).

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Jornet, J.M., Knightly, E.W. & Mittleman, D.M. Wireless communications sensing and security above 100 GHz. Nat Commun 14 , 841 (2023). https://doi.org/10.1038/s41467-023-36621-x

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Future Wireless Communication Technology towards 6G IoT: An Application-Based Analysis of IoT in Real-Time Location Monitoring of Employees Inside Underground Mines by Using BLE

Sushant kumar pattnaik.

1 School of Electronics Engineering, KIIT University, Bhubaneswar 751024, India; [email protected] (S.K.P.); ni.ca.tiik@tefsadkj (J.K.D.)

Soumya Ranjan Samal

2 Faculty of Telecommunications, Technical University of Sofia, 1756 Sofia, Bulgaria; gb.aifos-ut@pkv

3 Department of Electronics & Communication Engineering, Silicon Institute of Technology, Bhubaneswar 751024, India

Shuvabrata Bandopadhaya

4 School of Physical Sciences, Banasthali Vidyapith University, Rajasthan 304022, India; [email protected]

Kaliprasanna Swain

5 Department of Electronics & Communication Engineering, Gandhi Institute for Technological Advancements, Bhubaneswar 752054, India; [email protected]

Subhashree Choudhury

6 Department of Electrical and Electronics Engineering, Siksha ‘O’ Anusandhan, Bhubaneswar 751030, India; moc.liamg@3eerhsahbus

Jitendra Kumar Das

Albena mihovska.

7 Department of Business Development & Technologies, Aarhus University, 8000 Aarhus, Denmark; kd.ua.hcetb@aksvohima

Vladimir Poulkov

Associated data.

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

In recent years, the IoT has emerged as the most promising technology in the key evolution of industry 4.0/industry 5.0, smart home automation (SHA), smart cities, energy savings and many other areas of wireless communication. There is a massively growing number of static and mobile IoT devices with a diversified range of speed and bandwidth, along with a growing demand for high data rates, which makes the network denser and more complicated. In this context, the next-generation communication technology, i.e., sixth generation (6G), is trying to build up the base to meet the imperative need of future network deployment. This article adopts the vision for 6G IoT systems and proposes an IoT-based real-time location monitoring system using Bluetooth Low Energy (BLE) for underground communication applications. An application-based analysis of industrial positioning systems is also presented.

1. Introduction

In recent years, wireless technology has been one of the fastest-growing technologies in the area of communication. Today, wireless technology is becoming one of the largest carriers of digital data around the globe. According to the Cisco Visual Networking Index (VNI) Global Mobile Data Traffic for 2016 to 2022, worldwide mobile data traffic increased about 10-fold over these 6 years, reaching 77 exabytes (approx.) per month by 2022 ( Figure 1 a [ 1 ]). According to [ 1 ], the device mix is becoming smarter (advanced computing and multimedia competencies with at least 3G connectivity) with an increasing number of smart devices with high computing capabilities and better network connectivity, which creates a growing demand for smarter and more intelligent networks. The share of smart devices and connections as a percentage of the total will increase from 46 percent in 2016 to 85 percent by 2022, a more than two-fold increase during the figure time frame Figure 1 b [ 1 ]. It is expected that 75 billion devices will be connected by the end of 2025 [ 2 ]. Service providers around the globe are busy rolling out 5G networks to meet the growing demand of the end consumer for greater bandwidth, higher safety and quicker connectivity on the move. Many vendors have additionally begun area trials for 6G and are getting closer to rolling out 5G deployments in the direction of the end of the forecast length.

Cisco Annual Report from 2016 to 2022 [ 2 ]: ( a ) Cisco Visual Networking Index Global Mobile Data Traffic from 2016 to 2022; ( b ) Global Growth of Smart Mobile Devices and Connections Excluding Low-Power Wide-Area (LPWA).

Moreover, the heterogeneous nature of the next-generation communication networks in terms of the application, communication technology used and involvement of diversified devices brings a large variety of requirements and expectations. Today’s world is focusing more on the IoT due to its wide range of applications from human-centric to industry 4.0/industry 5.0. Nevertheless, device-to-device (D2D), machine-to-machine (M2M) and vehicle-to-vehicle (V2V)/V2X communication technologies constitute the real applications showing the widespread advantages of the IoT [ 3 , 4 , 5 , 6 , 7 , 8 , 9 ]. Furthermore, reliable data transmission with low latency is another key challenge for successful IoT applications [ 10 ]. The emergence of the Internet of Everything (IoE), which offers remarkable solutions for massive data transmission to the edge network, and the integration of Industrial Control Systems (ICSs) with the IoE recast it as the Industrial Internet of Everything (IIoE) [ 5 ]. Again, with the evolution of different emerging technologies such as artificial intelligence (AI), machine learning (ML), cloud computing, cognitive computing, edge computing, fog computing, blockchain technology, etc., various challenges are being addressed in different IoT industrial applications. Such complex IoT networks provide substantial technological prospects that facilitate the realization of good quality of service (QoS) and quality of experience (QoE). For example, the Internet of SpaceThings (IoST) for high speed, reduced latency and umbrella Internet coverage; the Social Internet of Things (SIoT) for an interface between human and social networks; the Internet of NanoThings (IoNT) for telemedicine; and the Internet of UnderwaterThings (IoUT) for improving ocean water quality, cyclonic/tsunami disaster management, etc. [ 11 ].

In view of this, the IoE introduces essential protection challenges due to the wide variety of functionality and demanding situations. There is always a dependency of the IoT on cellular networks since long-term evolution (LTE) was introduced, which is enhanced as 5G/6G in some specific scenarios. The demand for high throughput, high energy efficiency and better connectivity with reduced latency time can be attained beyond 5G/6G networks [ 12 ]. The 6G system will offer a better enrollment of the IoT devices as the 5G IoT has provided a solid foundation. The future 6G network is envisioned to be service-oriented, where software-defined networks (SDN) and network function virtualization (NFV) will play a vital role in the end-to-end architecture [ 13 ]. These technologies are capable of providing better coverage with high throughput, improved spectrum efficiency, greater bandwidth and ultra-low latency. The 6G IoT system is sustainable for high-accuracy localization and sensing, which are necessary for most of the envisioned highly computationally intensive applications.

Related Work and Key Contributions

A growing number of research works focus on current advances in wireless and IoT technology, including in-depth analysis of the advanced technology concepts, methodology and techniques.

Specifically, [ 14 ] provides a comprehensive survey on key enabling technology for 6G, where the emphasis is on a discussion of the operation of the individual technology with useful statistics for industries and academic researchers on the potential for investigating new research directions. The authors of [ 15 ] discussed the requirements of 6G and recent research trends to enable 6G capabilities and design dimensions by employing disruptive technologies such as artificial intelligence (AI) and driving the emergence of new use cases and applications manifested by stringent performance requirements. A review of 6G in terms of use cases, technical requirements, usage and key performance indicators (KPI) is presented in [ 16 ]. Here, the authors presented a preliminary definition roadmap, specifications, standardization and regulation for 6G. A survey on wireless evolution toward 6G networks is presented in [ 17 ], discussing the capabilities of network slicing technology with AI to enable a multitude of services with different quality of service (QoS) requirements for 6G networks. A comprehensive survey on the existing trends, applications, network structure and technologies of 6G is presented in [ 18 ], with a focus on industrial markets and use cases of 6G that take advantage of a better on-device processing and sensing, high data rates, ultra-low latencies and advanced AI. In [ 19 ], the authors presented an overview of 6G describing the complete evolution path from 1G networks to date and focusing on several key technologies such as terahertz communications, optical wireless communications (OWC) and quantum communications for improving the data rates.

A comprehensive survey on the convergence of the IoT and 6G is presented in [ 20 , 21 ] with a focus on edge intelligence, reconfigurable intelligent surfaces, space–air–ground–underwater communications, terahertz communications, massive ultra-reliable and low-latency communications and blockchain as the technologies that empower future IoT networks. A comprehensive study on 6G-enabled massive IoT is presented in [ 22 ], where ML and blockchain technologies are discussed as the primary security and privacy enablers. In [ 23 ], the potential of the IoT and 6G for various use cases in healthcare, smart grid, transport and Industry 4.0 have been elaborated jointly with the challenges during their practical implementations. Several shortcomings of 5G and features of 6G related to social, economic, technological and operational aspects such as the weakness of short packet and sensing-based URLLC, which may limit the dependability of low-latency services with high data rates or the lack of support of advanced IoT technologies are discussed in [ 24 ]. Current research activities, therefore, should focus on innovative techniques such as advanced time-stamp stream filtering combined with intelligent network slicing to support multi-party (source) data stream synchronization in very low latency environments coupled with distributed control (at the edge).

In [ 25 ], the author mainly focuses on the integration of blockchain technology into 6G, the IoTand IIoT networks. Blockchain technology has a strong potential to fulfill the requirements for massive 6G-based IoT for the integrity of personal data protection, data privacy and security and scalability. Furthermore, a sustainable ecosystem-focused business model, driven by blockchain-empowered 6G networks is thoroughly analyzed to deal with the cutting-edge worldwide economic disaster. Envisioning the green 6G–IoT network, a novel joint design technique using intelligent reflective surface (IRS) and ambient backscatter communication (ABC) is proposed in [ 26 ]. This method is primarily based on the joint design of an iterative beamforming vector, an IRS phase shift and reflection coefficients to decrease the AP’s transmit power without affecting the QoS. The author in [ 27 ] addressed the three fundamental components, i.e., artificial intelligence (AI), mobile ultra-high speed and the (IoT) for the future 6G network. The authors focused on the recent approaches, research issues and key challenges of IoT network topology and terahertz (Tz) frequency. A comprehensive survey of existing 6G and IoT-related works is summarized in Table 1 .

A Comprehensive Survey of existing 6G and IoT related works.

The contributions to this paper can be outlined as follows:

• We present the vision of the IoT with the technologies impacting it with their key features
• We review several applications and challenges of the IoT in different domains.
• We present different connectivity standards of the IoT and a rigorous review of these technological standards
• We present a comparative analysis between 5G and 6G.
• We present the vision and key features of 6G with its different aspects.
• We present a brief review of several challenges of 6G.
• We propose a BLE-based real-time location monitoring system by using the IoT

The remainder of this article is organized as follows. Section 2 presents the vision, applications and challenges of the IoT, including the connectivity standards and a comparative analysis of their capabilities. In Section 3 , a comparative analysis of 5G and 6G with the vision key features and the challenges of 6G is presented. Section 4 proposes and discusses a BLE-based real-time location monitoring system by using the IoT. Finally, we draw conclusions in Section 5 . Related abbreviations are listed in the Appendix. A schematic representation of the structure of the paper is shown in Figure 2 .

Structure of the Paper.

2. Visions, Applications and Challenges of the IoT

In the last few decades, the IoT has become the most promising and thriving area of research in academia and industry. The IoT extends the existence of communication by converging clients, businesses and industries by connecting intelligent things with each other through the cloud. These smart connections encompass different network applications, communication technologies and smart devices along with physical and virtual things. The IoT paradigm is a transformation from a centralized computer-based network to a completely distributed network of smart devices. To take the potential benefits of the IoT and to compete globally, the IoT European Research Cluster (IERC) has focused mainly on establishing a cooperation platform between companies and organizations for developing more research activities on the IoT at the European level. The primary objective of IERC is to facilitate making the research activities more ambitious and neoteric. The International Telecom Union (ITU) was the first international agency to produce a report on the IoT in 2005 [ 28 ]. Thereafter a new standard of the IoT was approved by the ITU in 2012 [ 29 ]. However, the term IoT was first used by the Massachusetts Institute of Technology’s (MIT’s) Kevin Ashton in 1999 [ 30 ].

2.1. Vison of the IoT

The vision of the IoT has different perspectives based on the data generated by the connected objects and the technology used. During the early stages of IoT implementation, the vision was to identify the physical objects by using radio frequency identification (RFID) tags. However, due to recent technological advances, the vision of the IoT has been reformed by encapsulating varying technologies and smart sensors. The IoT leads the way in unfolding the new generations of different compelling applications and services in the field of Industrial IoT (IIoT), Industry 4.0 and Society 5.0. Figure 3 , illustrates the key technologies that impact the IoT.

Technologies impacting the IoT.

2.2. Applications of the IoT

IoT applications in various sectors have been assessed based on their impacts on society and the economy along with their technology readiness level (TRL). The applications of the IoT are diversified based on their use in different fields such as intelligent homes, healthcare, agriculture, transportation, the environment, education, retail and logistics, industries and many more [ 31 , 32 , 33 , 34 ]. Consequently, the IoT has also had an impact during the pandemic era of COVID-19 in many aspects, e.g., contact tracing, virus detection by temperature scanning, remote health monitoring, quarantine e-tracking, virus spread control, etc., and also in tackling the post-COVID-19 situation [ 35 , 36 , 37 , 38 ]. AI-integrated IoT technology for the early detection of COVID-19 is discussed in [ 37 ]. This research mainly focuses on analyzing the extracted features of cough, shortness of breath and speech difficulties by using long short-term memory (LSTM) with recurrent neural network (RNN). In [ 38 ], an IoT-based real-time learning system is developed to control the spread of COVID-19 infection in the context of smart healthcare for residents. The system is used to monitor and analyze user activities and environmental parameters which helps predict critical cases, so alerts can be sent to the caretakers. A few applications of the IoT are briefly presented in Table 2 .

Applications of the IoT.

2.3. The IoT Challenges

With an increase in the number of smart devices and real-time applications, the complexity of IoT networks has increased in terms of their densities and architecture. These complexities scale down the performance competencies of the current IoT network. There are several IoT challenges, namely, universal standardization, connectivity, cloud computing, energy efficiency, IoT protocol and architecture in addition to security and privacy. The IoT is still in its developing stage; so many more challenges have to be addressed with the revolution of technologies in the future research domains of the IoT. A few challenges of the IoT are briefly presented in Table 3 .

Challenges of the IoT.

2.4. IoT Connectivity Standards

As per the IoT analytics report, there are mainly 21 IoT connectivity standards that can be broadly classified in two ways: as cellular IoT and non-cellular IoT connectivity standards. The cellular IoT standards are operated at a licensed spectrum, whereas the non-cellular IoT is operated at a non-licensed spectrum. Different IoT connectivity standards are depicted in Figure 4 [ 135 ] [Source: IoT Analytics Report 2021]. A comparative analysis of different IoT connectivity standards is presented in Table 4 .

IoT Connectivity Standards.

Comparison of different IoT Connectivity Standards.

3. Vision, Key Features and Challenges of 6G

With the standardization of 5G about to complete and its commenced global deployment, several latent limitations to meet the necessary requirements of IoT systems still remain. These impediments mainly relate to the high computation, security, wireless brain-computer interface (WBCI) intelligent communication in terms of more autonomous human-to-machine (H2M) communication, holographic communication (augmented reality/virtual reality) and AI. These data-hungry applications require more spectrum bandwidth (e.g., mm-wave) and high spectral efficiency which can be realized at the sub-terahertz (sub-THz) and THz bands [ 154 ]. Furthermore, due to the incorporation of a wide variety of mobile applications, there are some more challenges (beyond uRLLC, coverage, localization, privacy, power consumption, better quality-of-service, etc.) that need to be addressed in the future B5G wireless communication standards. In this context, the 6G is attracting more researchers from academia and industries towards itself. A comparative analysis between 5G and 6G is presented in Table 5 .

A comparative analysis between 5G and 6G.

3.1. Vision and Key Features of 6G

Despite the dramatic revolution of IoT–5G application in today’s wireless networks, 6G is anticipated to excel 5G in many ways, not only in daily life, but also in Society 5.0. Even though 6G is not a talking point of global harmony so far, some additional features with more potential and capabilities are being discussed. In this section, a comprehensive vision of a 6G network is presented from multiple perspectives as shown in Figure 5 .

Vision and key features of 6G [ 22 , 26 , 154 , 156 , 165 , 166 , 167 , 168 , 169 , 170 , 171 , 172 , 173 , 174 , 175 , 176 , 177 , 178 , 179 , 180 , 181 , 182 , 183 , 184 , 185 , 186 ].

3.1.1. Intelligent Network

As 6G is envisioned as a fully automated and smart network, the incorporation of AI, MLand quantum machine learning (QML) makes the future wireless networks more intelligent and predictive by limiting human efforts [ 176 , 187 ]. AI and ML are the transforming technologies and data analytics tools in the modern era of wireless communication that bring new research challenges in the field of 6G IoT [ 186 ]. By using big data and ML, a more precise performance prediction model can be implemented in a 6G IoT network to make smart decisions for security, optimization, resource allocation, network management, self-organization, etc., [ 155 , 156 , 157 , 158 , 159 , 160 , 161 , 162 , 163 , 164 , 165 , 188 ]. Due to the high veracity/volume data and complex 6G IoT network structure, it is necessary to instigate more futuristic learning/training frameworks for high-dimension neural networks (HDNN) [ 165 ].

3.1.2. Decentralized Network

Due to the emergence of multi-access edge computing (MEC) in the 5G network, there are several limitations in the centralized network, e.g., privacy, security, trust, incompatibility of the existing protocol to the dynamic connectivity and distributed and ubiquitous computing [ 166 ]. Thus, it is necessary to prepare a blueprint of decentralized architecture to support such a dynamic and autonomous network. In this regard, blockchain is a promising technology for the future 6G network and is capable of dealing with these challenges. Blockchain technology can provide a decentralized network management framework that can be used for resource management, data sharing/storage, spectrum sharing and other challenges [ 172 , 173 , 174 , 175 , 189 ].

3.1.3. Green Network

The 6G network is expected to meet the essential requirements for energy-efficient wireless communication globally. The green 6G network enables minimum energy utilization and helps achieve a peak data rate (THz) during signal transmission. A significant improvement in the energy efficiency of a network can be greatly experienced by incorporating different energy-harvesting techniques [ 154 , 190 ]. This also helps facilitate green communication by reducing CO 2 emission. In addition, several communication techniques, e.g., D2D communication, massive multiuser multiple-input-multiple-output (MIMO), heterogeneous network (HetNet), green IoT, non-orthogonal multiple access, energy-harvesting communications, etc., may be adopted to facilitate green communication for future wireless networks [ 191 , 192 , 193 ].

3.1.4. Superfast Network

With reference to the data analysis shown in Figure 1 , the ever-increasing demand for high data rate and seamless connectivity to such ultra-dense networks can be provided by integrating terahertz (THz) (ranges from 0.1–10 THz) communication in 6G networks [ 168 , 177 , 178 ]. A vast amount of unused radio spectra which can be efficiently used to increase network capacity is available in the THz band. THz is additionally reasonable for high data rate transmission and short-range communication by empowering the ultra-high bandwidth and uLLC paradigms. An extensive review of THz communication with its future scope and challenges is presented in [ 194 ].

3.1.5. Human-Centric

It is believed that human-centric communication is a key feature of the 6G network. With the help of this technology, sharing and/or accessing different physical features can be possible by humans. To accelerate human-centric communication rather than technology/machine-centric communication, the principal means of human perception must be incorporated into the communication system module [ 195 ]. A human-centric communication framework needs two fundamental aspects—technology and user experience (UE). The latter includes human behavior as well as psychological and socioeconomic contexts and needs to be considered during the modeling and analysis of the communication system [ 183 , 184 , 195 ].

In 2016, Society 5.0 was initiated by the Japanese cabinet in its Fifth Science and Technology with a vision to build a “Super Smart Society” [ 196 ]. Later, the vision was revised and presented by the Keidanren Business Federation with the prime focus of delivering sustainable development goals (SDGs) through the creation of Society 5.0 [ 183 , 184 , 197 ]. Society 5.0 is designed to solve different social issues by taking advantage of technological advancements. Considering different aspects of economic growth, social and environmental conditions, 17 primary objectives and 167 goals are listed in the Agenda 2030 by the United Nations to address several global challenges [ 198 , 199 ].

3.2. Challenges of 6G

Even though several advanced features have been added to 6G networks to enhance the performance matrices in comparison with 5G networks, there are still some key challenges that must be addressed further. These challenges are broadly classified into two categories: (i) technological challenges that include high throughput, EE, connectivity flexibility, more intelligent optimization techniques, etc., and (ii) non-technological challenges including industry barriers, spectrum allocation, regulatory policies and standardization, etc. [ 200 ]. A few key challenges of the future 6G networks are summarized in Figure 6 .

Challenges of 6G [ 5 , 154 , 156 , 200 , 201 , 202 , 203 ].

In addition, due to the integration of the IoE, terrestrial and non-terrestrial communication networks in 6G, their different heterogeneous highlights must be considered to productively coordinate them. Heterogeneity is likewise present in the protocol that those communication networks will comply with. Thus, 6G is taking on the massive task of integrating a number of heterogeneous aspects [ 203 ]. Furthermore, due to the inclusion of mm-Wave and THz communication, 6G networks are facing several more open challenges, e.g., more sensitive low-power transmitter, new model architecture, advanced propagation techniques for better coverage and directional communication. The networks must also deal with system noise, channel fading and fluctuations [ 169 , 203 , 204 , 205 ]. Several more challenges such as computational and processing resources due to the application of AI [ 206 ], a few ML application-related challenges [ 207 ], training issues and interoperability challenges [ 208 ], challenges in estimating the channel information by using reconfigurable intelligent surfaces (RIS) [ 209 , 210 ] and computational and trade-off challenges due to the application of artificial neural networks (ANN) in the IoT [ 211 ] have been recognized for the future 6G networks.

4. An IoT-Based Real-Time Location Monitoring System by Using BLE

Mining is one of the most speculative businesses around the globe. Most of the mines all over the world are lagging in different safety measures causing many casualties and deaths. The basic causes of death in underground mines are gas accidents, rock falling, ventilator accidents, fire, explosions, etc. Considering the safety issues of the employees/workers inside the mines, real-time location tracing of those employees becomes a major concern. Effective underground communication is necessary to collect more information about the mines or workers. However, there are various constraints while collecting the real-time data inside the mines such as restricted transmitting power, large attenuation of the transmitted signal from the rock wall and low penetration of the electromagnetic signal. In this regard, it is always beneficial to take the potential advantages of low-power and short-range communication technologies such as, RFID, Zigbee, Bluetooth, Bluetooth low energy (BLE), etc.

In this section, a scenario for a Bluetooth low energy (BLE) beacon-based real-time location monitoring of employees/workers by using the IoT is presented. A BLE beacon and microcontroller are used to design this asset-tracking product and have been implemented in the IoT here by connecting this device to the cloud.

4.1. State-of-Art

Underground communication inside mines is a major factor for the safety and security concerns of the mineworkers. The advent of IoT technology and its usefulness can be beneficial for the mining industry. It is believed that a robust communication infrastructure using IoT technology inside the mines may enhance the safety of the workers and is also capable of providing real-time information resulting in quick action to avoid lethal situations. Several researchers have proposed various frameworks and ideas for efficient communication inside the mines based on IoT technology, which includes low-power and short-range communication.

The authors of [ 212 , 213 ] proposed a wireless sensor network (WSN)-based monitoring system for underground mines. In this proposed technique, various sensors are placed at different locations to collect activities and positions of the employees, and the collected data are transferred to the end user or the central server via BS. Nageswari et al. [ 214 ], proposed an IoT-based smart mine monitoring system that uses radio frequency (RF) technology for communication purposes inside the mines. With this proposed technique the real-time location and real-time sensing of the dynamically varying environment can be achieved by using RF technology and WSN network, respectively. The major drawback of this proposed model is that large-signal transmission loss occurs through the walls of underground mines. An IoT-based mine safety system using WSN was proposed in [ 215 , 216 ]. In these proposed techniques, the authors used a Zigbee module for information collection from the cloud and measured the surrounding parameters of underground mines with the help of various sensors. A mine safety system using WSN was proposed in [ 217 ], where the authors constructed a prototype by using Zigbee and WSN to monitor safety issues and to measure the ambient properties, e.g., temperature, humidity, airflow, etc., inside the underground mines. A Zigbee compliant RFID-based safety system for underground coal mines was proposed in [ 218 ], where a unified wireless mesh-network infrastructure was used to monitor and locate the workers and measure the different environmental parameters inside the coal mines. Similarly, an IoT-based system for underground coal mines that uses a microcontroller, a node MCU and various sensors to measure the environmental conditions and safety measures of workers was proposed in [ 219 ]. A LoRaWAN-based coal safety and health monitoring system was proposed in [ 220 ]. In this proposed methodology, LoRaWAN uses low-power RF with a wide communication range and IoT technology for monitoring the workers’ health and observing the status of the circumstances in the coal mines.

There are several existing technologies used for communication purposes in underground mines. The most common approaches are RFID, Zigbee, Bluetooth, GPS, etc. Table 6 presents a comparative analysis of some existing technologies in terms of their pros and cons [ 214 , 215 , 216 , 217 , 218 , 219 , 220 , 221 ].

A comparative analysis of some existing technologies.

4.2. Proposed System Architecture and Workflow

To overcome these issues, our proposed technique uses BLE, which is a low-power and low-cost technology. This proposed methodology reduces the deployment cost and complexities by using the BSs of the existing cellular network infrastructure for the communication process. The system architecture of BLE-based real-time location monitoring in mines by using the IoT is shown in Figure 7 . In this scenario, two base stations (BS) are deployed to provide necessary services (uplink/downlink) to the BLE devices through the central office server as shown in Figure 7 a, and the complete workflow is shown in Figure 7 b.

Proposed system architecture and workflow. ( a ) Proposed System Model; ( b ) Complete Workflow Process.

Figure 7 a shows the coverage area of BLE and cell towers based on their transmitted power. The blue and green colored portion shows the energy region of BLE devices and cell towers, respectively. As can be seen, cell tower 0 transmits more power compared to cell tower 1. All the BLE devices are wearable or are attached to the employee working inside the mines. In this proposed method, beacons are considered because they can be easily identified by single board computers (SBC) as shown in Figure 8 . Different beacons are accessed by the nearest SBC based on their coverage area. The blue-colored region indicates the transmitted energy by the beacon signal as shown in Figure 8 a. The system contains beacons that are small and inexpensive, which emit signals in the same fashion as BLE. The used beacons have a short-range and can triangulate position in the same way that a phone uses cell towers with an assisted global positioning system (AGPS). These transmitters are deployed at known points inside the mines, and they permit the device to obtain area fixes. This data can be utilized to make new client encounters, for example, turn-by-divert headings for indoor situating from gateways/applications that read the guide signals.

Position of SBC and random distribution of BLE devices inside the mine area ( a , b ).

The scenario presented in Figure 8 a,b shows the position of the SBC (fixed position) and a random distribution of BLE devices, as the position of BLE device (wearable) depends on the position of the employee working inside the mine. The BLE receivers/gateway receives the universally unique identifier (UUID) transmitted by the beacons in a repetitive manner as shown in Figure 8 a,b. These signals can be utilized to differentiate between subgroups and individual ones in the subgroups. It is modified to check the accessible BLE signals “on the air” and the received signals contain the accompanying snippets of data in a bundle size of 60 bits, with 10 bits specifying major and minor values. The received signal strength indicator (RSSI) values can be utilized to decide the distance of the receiver to every one of the reference points. As those region statistics are stored inside the database, navigation of the receiver also can be tracked, and alerts can be generated if certain rules are violated. All the beacon data are stored in a local server through the gateway and then transferred to the central office server through cell towers as shown in Figure 8 a,b. The central office server is continuously updated based on the real-time information sent by the BLE beacon through the gateway. This information can be used to find the real-time location of the employees/workers inside the mines.

4.3. Simulation Result and Discussion

The simulation result in Figure 9 shows the discovery time of the BLE devices. It can be seen that the visibility time of the BLE device is constant, and the delay time is also very small. Hence, it helps to find the real-time location of the employees/workers inside the mines within a short time. Due to the small visibility time, the rescue process can be improved for the employees/workers (real-time locations) inside the underground mines during any hazardous situation.

Discovery time of BLE device.

5. Conclusions

This paper summarizes and relates the future direction of IoT applications to current 6G trends, development sand challenges. The study looked at the vision and different technologies impacting the IoT as outcomes of international research. The paper considered the applications in various sectors and provided a summary of the different IoT technologies. The various IoT connectivity standards and a few challenges remaining open for IoT integration with cellular systems were outlined. The IoT is a basic building block for next-generation industrial standard 4.0/5.0 smart applications in home, city, agriculture, healthcare and many more uses, but this requires a major upgrade of the physical and network layers of upcoming cellular wireless networks. In this paper, a brief comparison between 5G and 6G was presented in terms of the technical features. The vision and key features of 6G along with the implementation challenges were discussed. This paper also includes a case study related to the real-time application of the IoT to locate the employees in underground mines using BLE technology. The system architecture and workflow for the given application were presented. This article might assist the researcher apprehend various challenges with their applications of the IoT and 6G to the real world.

Acknowledgments

The authors acknowledged support from the project HOLOTWIN (D01-285/06.10.2020) financed by the Ministry of Education and Science of Bulgaria.

Abbreviations

Funding statement.

The APC was funded by the Ministry of Education and Science of Bulgaria fund research project HOLOTWIN (D01-285/06.10.2020).

Author Contributions

S.K.P.: concept and setup preparation, design of system model; S.R.S.: concept, methodology creation, model selection, analysis and simulations supervision, text editing; S.B.: text and plot preparation, design of system model supervision, simulations and review; K.S. and S.C.: setup preparation, design of system model supervision, data preparation and text editing; J.K.D. and A.M.: methodology validation, model validation, setup preparation and data preparation, V.P.: overview of model validation, final model preparation, data preparation supervision, text editing and review. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Data availability statement, conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Location Privacy Preservation for Location Based Service Applications: Taxonomies, Issues and Future Research Directions

• Published: 06 April 2024
• Volume 134 , pages 1617–1639, ( 2024 )

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• Ajay K. Gupta   ORCID: orcid.org/0000-0001-9666-5047 1 &
• Udai Shanker 1  

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Context-aware computing processes the mobile user’s query/transaction submitted from anywhere at any time. Basically, location based services (LBSs) are continuous, local, and spatially confined applications of computing in the context-aware mobile environment, where queries/transactions are initiated by the mobile users. The smartphones as a resultant of today’s advanced mobile technologies allow these mobile users to access numerous LBSs and provide information interactively to them depending on their locations. The mobile user’s positions and associated confidential information enable more sensitive information to be created; but, it inevitably leads to a threat that these sensitive information may be used for different purposes by the third parties. Also, there is lack of state of the art location privacy preservation procedures to be able to create a balance between user location/ activity privacy preservation and quality of services in LBSs technologies. Therefore, there is a need to do more research efforts to ensure the privacy of these mobile users by developing the secured location-based technologies. Thus, our this study specifically discusses the aforementioned issues, a literature for the taxonomy of the privacy preservation approaches available to the research community with comparative analysis over the common attributes, highlighting limitations/strength, recent advancement and provides possible research directions for the further investigation of the unanswered questions.

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Gupta, A.K., Shanker, U. Location Privacy Preservation for Location Based Service Applications: Taxonomies, Issues and Future Research Directions. Wireless Pers Commun 134 , 1617–1639 (2024). https://doi.org/10.1007/s11277-024-10977-9

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