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The article discusses the telecommunication industry has evolved to provide services for new types of Internet of Things (IoT) devices in addition to basic mobile phone or internet services. Topics include the extended reality devices, sensors, and ground and aerial robots, to name a few. With the deployment of these new services, it is difficult for the wireless network to support ubiquitous connections with diverse quality-of-service (QoS) requirements.

The article reports that looking to 2030 and beyond, revolutionary enhancement of data transmission rates in sixth generation (6G) and beyond systems are required to meet the challenge of increasing communication traffic due to the massive exchange of information. Development of technologies and systems enabling Terabit-per-second (Tbps) wireless communications need to support long term exponential capacity increase of mobile communication networks.

Vehicle-to-vehicle (V2V) wireless communication systems are fundamental in many intelligent transportation applications, e.g., traffic load control, driverless vehicle, and collision avoidance. Hence, developing appropriate V2V communication systems and standardization require realistic V2V propagation channel models. However, most existing V2V channel modeling studies focus on car-to-car channels; only a few investigate truck-to-car (T2C) or truck-to-truck (T2T) channels. In this paper, a hybrid geometry-based stochastic model (GBSM) is proposed for T2X (T2C or T2T) channels in freeway environments. Next, we parameterize this GBSM from the extensive channel measurements. We extract the multipath components (MPCs) by using a joint maximum likelihood estimation (RiMAX) and then determine the cluster types based on their evolution patterns. We classify the determined clusters into line-of-sight, single-bounce reflections from static interaction objects (IOs), single-bounce reflections from mobile IOs, multiple-bounce reflections, and density multipath components (DMCs). Particularly, we model multiple-bounce reflections as double clusters following the COST 273/COST2100 method. This paper presents the complete parameterization of the channel model. We validate this model by comparing the delay spread and the angular spreads of arrival/departure obtained from the proposed model with the measurement data. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surfaces (RISs) have been recently considered as a promising candidate for energy-efficient solutions in future wireless networks. Their dynamic and low-power configuration enables coverage extension, massive connectivity, and low-latency communications. Due to a large number of unknown variables referring to the RIS unit elements and the transmitted signals, channel estimation and signal recovery in RIS-based systems are the ones of the most critical technical challenges. To address this problem, we focus on the RIS-assisted wireless communication system and present two joint channel estimation and signal recovery schemes based on message passing algorithms in this paper. Specifically, the proposed bidirectional scheme applies the Taylor series expansion and Gaussian approximation to simplify the sum-product procedure in the formulated problem. In addition, the inner iteration that adopts two variants of approximate message passing algorithms is incorporated to ensure robustness and convergence. Two ambiguities removal methods are also discussed in this paper. Our simulation results show that the proposed schemes show the superiority over the state-of-art benchmark method. We also provide insights on the impact of different RIS parameter settings on the proposed schemes. [ABSTRACT FROM AUTHOR]

The explosive growth of Internet-of-Things (IoT) applications such as smart cities and Industry 4.0 have led to drastic increase in demand for wireless bandwidth, hence motivating the rapid development of new techniques for enhancing spectrum utilization needed by new generation wireless communication technologies. Among others, dynamic spectrum access (DSA) is one of the most widely accepted approaches. In this paper, as an enhancement of existing works, we take into consideration of inter-node collaborations in a dynamic spectrum environment. Typically, in such distributed circumstances, intelligent dynamic spectrum access almost invariably relies on self-learning to achieve dynamic spectrum access improvement. Whereas, this paper proposes a DSA scheme based on deep reinforcement learning to enhance spectrum and access efficiency. Unlike traditional Q-learning-based DSA, we introduce the following to enhance the spectrum efficiency in dynamic IoT spectrum environments. First, deep double Q-learning is adopted to perform local self-spectrum-learning for IoT terminals in order to achieve better dynamic access accuracy. Second, to accelerate learning convergence, federated learning (FL) in edge nodes is used to improve the self-learning. Third, multiple secondary users, who do not interfere with each other and have similar operation condition, are clustered for federated learning to enhance the efficiency of deep reinforcement learning. Comparing with the traditional distributed DSA with deep learning, the proposed scheme has faster access convergence speed due to the characteristic of global optimization for federated learning. Based on this, a framework of federated deep reinforcement learning (FDRL) for DSA is proposed. Furthermore, this scheme preserves privacy of IoT users in that FDRL only requires model parameters to be uploaded to edge servers. Simulations are performed to show the effectiveness of theproposed FDRL-based DSA framework. [ABSTRACT FROM AUTHOR]

In this paper, the design of a multiple-input multiple-output (MIMO) optical wireless communication (OWC) link based on vertical cavity surface emitting laser (VCSEL) arrays is systematically carried out with the aim to support data rates in excess of 1 Tb/s for the backhaul of sixth generation (6G) indoor wireless networks. The proposed design combines direct current optical orthogonal frequency division multiplexing (DCO-OFDM) and a spatial multiplexing MIMO architecture. For such an ultra-high-speed line-of-sight (LOS) OWC link with low divergence laser beams, maintaining alignment is of high importance. In this paper, two types of misalignment error between the transmitter and receiver are distinguished, namely, radial displacement error and orientation angle error, and they are thoroughly modeled in a unified analytical framework assuming Gaussian laser beams, resulting in a generalized misalignment model (GMM). The derived GMM is then extended to MIMO arrays and the performance of the MIMO-OFDM OWC system is analyzed in terms of the aggregate data rate. Novel insights are provided into the system performance based on computer simulations by studying various influential factors such as beam waist, array configuration and different misalignment errors, which can be used as guidelines for designing short range Tb/s MIMO OWC systems. [ABSTRACT FROM AUTHOR]

In concurrent spectrum sharing scenarios between radars and wireless communication systems, one strict approach to protect the radar from undesired interference is locating the base stations outside a guard (or exclusion) zone of the radar. As a result, users inside that zone experience bad communication coverage. This paper uses Reconfigurable Intelligent Surfaces (RISs) to improve the base station coverage of users in the radar exclusion zone. The paper shows, through analysis and simulation, that joint optimization of base station and RIS locations improves the probability of coverage in the exclusion zone over the shared spectrum without disturbing the radar operation. [ABSTRACT FROM AUTHOR]

Fixed Satellite Services (FSS) used to be alone at the C-Band spectrum in most countries. Since the deployment of 5G in many countries (i.e., 3.3–3.6 GHz), FSS is not the exclusive system in the C-Band anymore. In order to minimize the detrimental interference for the FSS to allowable levels, regional exclusion zones of maximum radiated power in 5G base stations (BS) are proposed and evaluated. In this paper, a measurement campaign has been carried out, and an analysis of the interference has been studied. A filtering model, namely Filter to Remove Broadband Interference 5G (FIREBRING), is proposed and analyzed concerning the carrier-to-noise ratio (C/N). Moreover, this paper focuses on the evaluation of the 5G interference into the FSS. The proposed solution deployed an Low-Noise Block (LNB) with a band frequency of 3.7 to 4.2 GHz to test the satellite down-conversion signal at the receiver. The paper offered a complete analysis of the 5G signal, taking into account the implications of out-of-band emissions, potentially LNB saturation into FSS receiver, and the repercussions of the deployment of the 5G BS active antenna systems. With the LNB and down-converter in place, it can be found that the signal interference between 1.450 GHz and 1.550 GHz, is nearly 18 dB. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS) technology is promising to enhance wireless communications services by providing smart radio environment. In this paper, we investigate the RIS aided cellular networks with device-to-device (D2D) users, and maximize the sum of the transmission rate of the D2D communications and the cellular networks from a new perspective. In addition to solving the typical resource allocation problems for D2D communications, this paper further optimize the wireless environment by adjusting the position and phase shift of the RIS. To solve this non-convex problem, we propose a novel decentralized double deep Q-network (D3QN) framework for the resource allocation at users and a centralized DDQN for RIS optimization at the base station (BS), which are verified to achieve the near-optimal performance with lower complexity and enhanced robustness. Simulation results illustrate that the proposed framework can achieve higher transmission rates compared to benchmarks, meanwhile meeting the quality of service (QoS) requirements at the BS and D2D users. [ABSTRACT FROM AUTHOR]

The reconfigurable intelligent surface (RIS), which consists of many low-cost reflecting elements, can enhance the reception of the desired signal and suppress the interference. Considering the above advantages, this paper investigates the RIS-assisted wireless communication in the presence of an interferer, where a receiver receives the desired signal and interference from a transmitter and an interferer, respectively, and the RIS is deployed to assist this system. First, an interference-limited channel capacity maximization problem is formulated, and a numerical algorithm based on the fraction programming and optimality conditions is proposed to obtain the optimal solution. Then, this paper shows the upper boundary of the maximal capacity with interference and discusses what kind of channel conditions can achieve the upper boundary and the corresponding optimal phase shifts. Next, this paper analyzes the asymptotic behaviors of the maximal capacity in the scenarios that some or all of the number of reflecting elements, antennas at the transmitter, and interferer go to infinity. Finally, this paper generalizes the above results to the multiple interferers scenario. [ABSTRACT FROM AUTHOR]

Indoor optical wireless communication (IOWC) is a key technology complementing radio communication in 6G. Typically, the downlink of IOWC is implemented using visible light and uplink is implemented using infrared. Though the downlink of IOWC has been studied well, the uplink of multiple-access IOWC requires further research. In this paper, power allocation strategies in the uplink of IOWC with multiple non-cooperative users is studied. Optimizing power allocation in IOWC that maximize sum-rate with power constraints becomes a non-convex problem. First, this paper proposes an alternating maximization algorithm to compute near optimal power allocation policies for small number of users. Next, a phenomenon of invariance is observed when the number of users in the system is large. Under invariance, the optimal power allocation policy of a user becomes independent of other users, thereby facilitating fast and decentralized computation of power allocation strategies. From simulations, it was observed that the invariance can occur even with five to ten users. For the first time, a rigorous analysis of the invariance phenomenon is provided. An algorithm to compute the optimal power allocation at invariance is proposed; this algorithm is proven to achieve the global maxima in sum-rate without the channel knowledge of other users. [ABSTRACT FROM AUTHOR]

The prospects of using a Reconfigurable Intelligent Surface (RIS) to aid wireless communication systems have recently received much attention from academia and industry. Most papers make theoretical studies based on elementary models, while the prototyping of RIS-aided wireless communication and real-world field trials are scarce. In this paper, we describe a new RIS prototype consisting of 1100 controllable elements working at 5.8 GHz band. We propose an efficient algorithm for configuring the RIS over the air by exploiting the geometrical array properties and a practical receiver-RIS feedback link. In our indoor test, where the transmitter and receiver are separated by a 30 cm thick concrete wall, our RIS prototype provides a 26 dB power gain compared to the baseline case where the RIS is replaced by a copper plate. A 27 dB power gain was observed in the short-distance outdoor measurement. We also carried out long-distance measurements and successfully transmitted a 32 Mbps data stream over 500 m. A 1080p video was live-streamed and it only played smoothly when the RIS was utilized. The power consumption of the RIS is around 1 W. Our paper is vivid proof that the RIS is a very promising technology for future wireless communications. [ABSTRACT FROM AUTHOR]

The matroidal connectivity and conditional matroidal connectivity are novel indicators to measure the real faulty tolerability. In this paper, for the $n$ n -dimensional alternating group graph $AG_{n}$ A G n , the structure properties and (conditional) matroidal connectivity are studied based on the dimensional partition of $E(AG_{n})$ E (A G n) . We prove that for $S\subseteq E(AG_{n})$ S ⊆ E (A G n) under some limitation on the number of faulty edges in each dimensional edge set, if $|S|\leq (n-1)!-1$ | S | ≤ (n - 1) ! - 1 , then $AG_{n}-S$ A G n - S is connected. We study the value of matroidal connectivity and conditional matroidal connectivity of $AG_{n}$ A G n . Furthermore, simulations have been carried out to compare the matroidal connectivity with other types of conditional connectivity in $AG_{n}$ A G n . The simulation result shows that the matroidal connectivity significantly improves these known fault-tolerant capability of alternating group graphs. [ABSTRACT FROM AUTHOR]

This paper considers a caching system of a single server and multiple users. We aim to characterize the memory-rate tradeoff for caching with uncoded cache placement, under nonuniform file popularity. Focusing on the modified coded caching scheme (MCCS) recently proposed by Yu, etal., we formulate the cache placement optimization problem for the MCCS to minimize the average delivery rate under nonuniform file popularity, restricting to a class of popularity-first placements. We then present two information-theoretic lower bounds on the average rate for caching with uncoded placement, one for general cache placements and the other restricted to the popularity-first placements. By comparing the average rate of the optimized MCCS with the lower bounds, we prove that the optimized MCCS attains the general lower bound for the two-user case, providing the exact memory-rate tradeoff. Furthermore, it attains the popularity-first-based lower bound for the case of general $K$ users with distinct file requests. In these two cases, our results also reveal that the popularity-first placement is optimal for the MCCS, and zero-padding used in coded delivery incurs no loss of optimality. For the case of $K$ users with redundant file requests, our analysis shows that there may exist a gap between the optimized MCCS and the lower bounds due to zero-padding. We next fully characterize the optimal popularity-first cache placement for the MCCS, which is shown to possess a simple file-grouping structure and can be computed via an efficient algorithm using closed-form expressions. Finally, we extend our study to accommodate nonuniformity in both file popularity and size, where we show that the optimized MCCS attains the lower bound for the two-user case, providing the exact memory-rate tradeoff. Numerical results show that, for general settings, the gap between the optimized MCCS and the lower bound only exists in limited cases and is very small. [ABSTRACT FROM AUTHOR]

Human Body Communication (HBC) is an alternative to radio wave-based Wireless Body Area Network (WBAN) because of its wide bandwidth leading to enhanced energy efficiency. Designing Modern HBC devices need the accurate electrical equivalent of the HBC channel for energy efficient communication. The objective of this paper is to present an improved lumped element-based detailed model of Galvanic HBC channel which can be used to explain the dependency of the channel behaviour on the internal body dependent parameters such as electrical properties of skin and muscle tissue layers along with the external parameters such as electrode size, electrode separation, geometrical position of the electrodes and return-path or parasitic capacitances. The model considers the frequency-dependent impedance of skin and muscle tissue layers and the effect of various coupling capacitances between the body and Tx/Rx electrodes to the Earth-Ground. A 2D planar structure of skin and muscle tissue layers is simulated using a Finite Element Method (FEM) tool to prove the validity of the proposed model. The effect of symmetry and asymmetry at the transmitter and receiver ends is also explained using the model. The model become very useful for fast calculation of Galvanic channel response without using any FEM tool. Experimental results show that the galvanic response is not only a function of channel length but also depends on the mismatch at the transmitter and receiver end. In case of a very high mismatch scenario, the channel behavior is dominated by the capacitive HBC, even for a galvanic excitation and termination. [ABSTRACT FROM AUTHOR]

This paper derives the asymptotic distribution of the normalized $k$ -th maximum order statistics of a sequence of non-central chi-square random variables with non-identical non-centrality parameters. We demonstrate the utility of these results in characterizing the signal-to-noise ratio in three different applications in wireless communication systems where the statistics of the $k$ -th maximum channel power over Rician fading links are of interest. Furthermore, we derive simple expressions for the asymptotic outage probability, average throughput, achievable throughput, and average bit error probability. The proposed results are validated via extensive Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

In this paper, we consider deploying an intelligent reflecting surface (IRS) to enhance the downlink (DL) energy transfer and uplink (UL) information transmission efficiency for secure multiple-input multiple-output (MIMO) wireless powered communication networks (WPCNs). We aim to maximize the secrecy throughput of all users by jointly optimizing the DL/UL time allocation, the energy transmit covariance matrix of hybrid access point (AP), the information transmit beamforming matrix of users and the phase shifts of IRS in DL/UL, subject to constraints of energy/information transmit power at the hybrid AP/users and that of unit-modulus IRS phase shifts for DL/UL. To tackle the non-convex problem, we first transform the original problem into an equivalent form based on the mean-square error (MSE) method given time allocation, and then apply the alternating algorithm to update the optimization variables iteratively. Specifically, the energy covariance matrix and the information beamforming matrix are obtained based on the dual subgradient method. For the IRS phase shifts, we investigate two IRS beamforming reflection setups, namely different DL/UL IRS beamforming and identical DL/UL IRS beamforming. For the former case, the second-order cone programming technique and the Majorization-Minimization algorithm/element by element iterative algorithm are applied to obtain the DL and UL IRS phase shifts, respectively. For the latter case, the IRS phase shifts are obtained by the successive convex approximation technique. To further reduce the computational complexity of the single-user system, we derive the closed-form solutions of IRS phase shifts in each iteration for the two different reflection setups. Simulation results show that all the proposed algorithms can greatly improve the secrecy throughput compared to the conventional system without IRS. [ABSTRACT FROM AUTHOR]

The intelligent omni-surface (IOS) is a dynamic metasurface that has recently been proposed to achieve full-dimensional communications by realizing the dual function of anomalous reflection and anomalous refraction. Existing research works provide only simplified models for the reflection and refraction responses of the IOS, which do not explicitly depend on the physical structure of the IOS and the angle of incidence of the electromagnetic (EM) waves. Therefore, the available reflection-refraction models are insufficient to characterize the performance of full-dimensional communications. In this paper, we propose a complete and detailed circuit-based reflection-refraction model for the IOS, which is formulated in terms of the physical structure and equivalent circuits of the IOS elements, as well as we validate it with the aid of full-wave EM simulations. Based on the proposed circuit-based model for the IOS, we analyze the asymmetry between the reflection and transmission coefficients. Moreover, the proposed circuit-based model is utilized for optimizing the hybrid beamforming of IOS-assisted networks and hence improving the system performance. To verify the circuit-based model, the theoretical findings, and to evaluate the performance of full-dimensional beamforming, we implement a prototype of IOS and deploy an IOS-assisted wireless communication testbed to experimentally measure the beam patterns and to quantify the achievable rate. The obtained experimental results validate the theoretical findings and the accuracy of the proposed circuit-based reflection-refraction model for IOSs. [ABSTRACT FROM AUTHOR]

Spectral-compatible radar emission has a paramount importance in realizing the coexistence of radar with wireless communications. In this paper, we deal with the design of spectral-compatible transmit beampattern with minimum peak sidelobe level for a narrowband multiple-input multiple-output(MIMO) radar. We also consider constraints that are imposed due to the practical high power amplifier(HPA) used in modern radars. The constraints are used to control the dynamic range on the magnitude of each signal, to control variations in the transmit power from the individual antennas and the total energy of the signals. The considered problem is challenging as it is non-convex. To this end, we propose an iterative solution that incorporates the majoriztion-minimization(MM) and alternating direction method of multipliers(ADMM) frameworks. Our solution avoids the computationally expensive operations such as matrix inverse and eigenvalue decomposition. We provide numerical results to validate the proposed solution. The results show that the method provides the intended spectral-compatible beampattern while maintaining a beampattern synthesize performance that is comparable to the state-of-the-art work. [ABSTRACT FROM AUTHOR]

Massive MIMO is a promising air interface technology for 5G wireless communications. Such antenna systems offer capabilities to utilize channel correlations to create beams suitable for user specific transmissions. Most of the prior research is devoted to user-specific transmission in such systems, where a narrow beam is formed towards a user to improve its reception. Meanwhile, public-channel transmission to multiple users at once by means of broad beams has been understudied. In this paper, we introduce the concept of array-size invariant (ASI) beamforming, enabling generation of broad beams from very large antenna arrays where all elements are transmitting at maximum power. The ASI technique offers the possibility to achieve a perfectly flat array factor by exploiting the additional degree of freedom coming from the dual-polarization beamforming. The proposed technique is applicable to both uniform linear and rectangular arrays. The benefits of the method are shown by means of several numerical examples. In particular, the practical usefulness of the ASI beamforming, in terms of coverage and energy efficiency, is illustrated on an example of designing a cell-specific broad beam for public-channel transmission in a realistic network deployment. [ABSTRACT FROM AUTHOR]

With the explosive growth of mobile data, the demand of high-speed railway (HSR) passengers for broadband wireless access services urgently needs the support of ultra-high-speed scenario broadband wireless communication. Millimeter-wave (mmWave) can achieve high data transmission rates, but it is accompanied by high propagation loss and vulnerability to blockage. To address this issue, developments of directional antennas and unmanned aerial vehicles (UAVs) enhance the robustness of the mmWave train-ground communication system. In this paper, we propose a UAV and MRs relay assistance (UMRA) algorithm to effectively overcome link blockage, which can maximize the number of transmission flows on the premise of meeting QoS requirements and channel qualities. First, we formulate a mixed integer nonlinear programming (MINLP) problem for UAV trajectory design and transmission scheduling in the full-duplex (FD) mode. Then, in UMRA, the relay decision algorithm and transmission scheduling algorithm based on graph theory are proposed, which make a good tradeoff between computation complexity and system performance. Extensive simulation results show that a suitable UAV position will greatly improve the performance of the UMRA algorithm and make it close to the optimal solution. Compared with the other two existing benchmark schemes, with the high channel quality requirements and large-area blockage, UMRA can greatly improve the number of completed flows and system throughput. [ABSTRACT FROM AUTHOR]

In this paper, we derive an upper bound on load-threshold of coded slotted ALOHA (CSA) for slot erasure channel (SEC) and that for packet erasure channel (PEC), respectively. In SEC, by exploiting the analogy between Gaussian elimination of solving linear equations and the iterative successive interference-cancellation (SIC) decoding procedure of CSA, we derive the upper performance bound for SEC. Subsequently, in PEC, utilizing density evolution to track the average probability of packet-decoded failure within the SIC decoding process, we obtain the upper bound for PEC. Moreover, we propose a numerical search algorithm of these bounds under a given calculating precision. The numerical results indicate that the asymptotic upper limit on load-threshold of CSA over SEC is always less than that over PEC with any given erasure probability and average transmission rate. [ABSTRACT FROM AUTHOR]

Control- and user-plane separation (CUPS) and network slicing are two key technologies to support increasing network traffic and diverse wireless services. However, the benefit of CUPS in decoupling the network coverage and data service functions has not been fully utilized to facilitate network slicing. In this paper, we present a novel CUPS-based end-to-end (CUPS-E2E) network slicing scheme. First, the base stations (BS) are classified into control BSs (CBS) that provide control plane (CP) coverage and traffic BSs (TBS) that deliver user plane (UP) traffic. Next, upon CBSs and TBSs being virtualized, we define four typical end-to-end (E2E) network slices: one for CP coverage, one for high-throughput services, one for computation-intensive services, and the other for delay-sensitive services. The utilities of the four E2E network slices are defined based on their coverage, throughput, computing capability and delay requirements, respectively. Then, a deep deterministic policy gradient (DDPG)-based algorithm is employed to maximize the long-term sum-utility of the four E2E network slices by jointly optimizing the allocation of communication and computing resources to the four network slices and the activation of virtual TBSs, while meeting the service requirements of all users. Simulation results show that our proposed CUPS-E2E network slicing scheme in conjunction with a DDPG-based sum-utility maximization algorithm can support the CP wide-coverage and massive access requirements as well as the UP high-throughput, computation-intensive and delay-sensitive services simultaneously, and outperforms the existing E2E network slicing schemes in terms of the sum-utility, coverage percentage, throughput and delay. [ABSTRACT FROM AUTHOR]

The new Fifth generation (5G) of wireless communications and beyond 5G (B5G) networks are required to provide connectivity for massive number of devices at high speed and low latency. Within this context, non-orthogonal multiple access (NOMA) has been involved and emerged in recent research since it is considered as an enabling technology for 5G and B5G networks. NOMA allows several users to share the same resources of time and frequency, making it an excellent candidate to provide impressively large connectivity with high spectral efficiency. In this paper, we study the performance of NOMA systems assuming independent but not necessarily to be identical $N$ -Nakagami-m multipath fading channels. This channel model subsumes the double Nakagami-m, which was investigated in the context of intervehicular communications and keyhole multiple input multiple output systems, as special cases. To this end, we derive exact analytical and asymptotic expressions for the probability density function of the overall signal to noise ratio, system capacity, and the pairwise error probability (PEP) for each user. Numerical results are also provided herein to show the effects of fading parameters and number of users on the capacity and the PEP of each user. [ABSTRACT FROM AUTHOR]

In this paper, an antenna synthesis process is investigated for Intelligent Transportation System (ITS) application. The wireless communication between Road Side Units (RSUs) and On Board Units (OBUs) located in the vehicles enables smart mobility. However, to support high speed vehicles and high data rates, a wider coverage area by the RSU antennas projected on the highway is required. This is defined by the radiation patterns of the RSU antennas. On a multi-lane highway, interference from the adjacent lanes is a critical issue which determines the communication reliability in terms of Single-to-Interference plus Noise Ratio (SINR). Hence, in this paper, an interference-aware antenna synthesis process is proposed and a planar array is optimized based on the objective function of obtaining a wide coverage area in terms of SINR distribution for a given modulation scheme. The proposed antenna array enhances the reliable communication area and provides improved SINR distribution across the lane for misaligned vehicles from the center of the lane. The results indicate that the proposed antenna array performs better than the existing designs in terms of communication reliability. [ABSTRACT FROM AUTHOR]

This paper studies a memoryless state-dependent multiple access channel (MAC) where two transmitters wish to convey a message to a receiver under the assumption of causal and imperfect channel state information at transmitters (CSIT) and imperfect channel state information at receiver (CSIR). In order to emphasize the limitation of transmitter cooperation between physically distributed nodes, we focus on the so-called distributed CSIT assumption, i.e., where each transmitter has its individual channel knowledge, while the message can be assumed to be partially or entirely shared a priori between transmitters by exploiting some on-board memory. Under this setup, the first part of the paper characterizes the common message capacity of the channel at hand for arbitrary CSIT and CSIR structure. The optimal scheme builds on Shannon strategies, i.e., optimal codes are constructed by letting the channel inputs be a function of current CSIT only. For a special case when CSIT is a deterministic function of CSIR, the considered scheme also achieves the capacity region of a common message and two private messages. The second part addresses an important instance of the previous general result in a context of a cooperative multi-antenna Gaussian channel under i.i.d. fading operating in frequency-division duplex mode, such that CSIT is acquired via an explicit feedback of perfect CSIR. The capacity of the channel at hand is achieved by distributed linear precoding applied to Gaussian codes. Surprisingly, we demonstrate that it is suboptimal to send a number of data streams bounded by the number of transmit antennas as typically considered in a centralized CSIT setup. Finally, numerical examples are provided to evaluate the sum capacity of the binary MAC with binary states as well as the Gaussian MAC with i.i.d. fading. [ABSTRACT FROM AUTHOR]

This paper presents a part of our ground-breaking work on evaluation of buildings in terms of wireless friendliness at the building-design stage. The main goal is to devise building design practices that provide for a good performance of wireless networks deployed in buildings. In this paper, the interference gain (IG) and power gain (PG) are defined as two figures of merit (FoM) of the wireless performance of buildings. The FoMs bridge the gap between building design and wireless communications industries. An approach to derive exact closed-form equations for these FoMs is proposed for the first time. The derived analytic expressions facilitate straightforward and more computationally efficient numerical evaluation of the proposed FoMs as compared to Monte Carlo simulations for well-known indoor propagation models. It is shown that the derived closed-form expression can be readily employed to evaluate the impact of building properties, such as the sizes and the aspect ratios (ARs) of rooms, on the wireless performance. The proposed approach sheds light to architects on evaluation and design of wireless-friendly building layouts. [ABSTRACT FROM AUTHOR]

In this paper, two new families of asynchronous channel-hopping (CH) sequences—Symmetric Maximum-Length CH (SML-CH) Sequences and Relaxed Difference Set (RDS) of Maximum-Length CH (RDSML-CH) Sequences—are constructed. For the first time, the maximum-length sequences (also called as m-sequences) are used to create 2-D CH matrices with a reduced number of “jump” columns. The two new constructions carry the desirable properties of maximum rendezvous diversity (MRD) and even channel use (ECU) and, more importantly, have the shortest periods in their categories of constructions. Another contribution is on the embedment of optical orthogonal codes (OOCs) to eliminate “stay” columns in the RDSML-CH matrices, thus resulting in the first and only family of the asynchronous CH sequences that can asymptotically achieve the theoretical period lower bound. To support the RDSML-CH construction, a new shortened RDS algorithm for creating the OOCs with smaller weight-to-length ratios than the existing ones is proposed. Numerical and simulation analyses show that the two new constructions have a good balance of short period, MRD, ECU, short time-to-rendezvous (TTR) mean, small TTR variance, and short maximum-TTR, thus more suitable for practical CR wireless networks than the existing constructions. [ABSTRACT FROM AUTHOR]

The efficiency of link adaptation in wireless communications relies greatly on the accuracy of channel knowledge and transmission mode selection. In this paper, a novel deep learning based link adaptation framework is proposed for the orthogonal frequency-division multiplexing (OFDM) systems with compressed-sensing-assisted index modulation, termed as OFDM-CSIM, communicating over millimeter-wave (mmWave) channels. To achieve link adaptation, a novel multi-layer sparse Bayesian learning (SBL) algorithm is proposed for accurately and instantaneously providing the required channel state information. Meanwhile, a deep neural networks (DNN)-assisted adaptive modulation algorithm is proposed to choose the best possible transmission mode to maximize the achievable throughput. Simulation results show that the proposed multi-layer SBL algorithm enables more accurate channel estimation than the conventional techniques. The DNN-based adaptive modulator is capable of achieving a higher throughput than the learning-assisted solution based on the $k$ nearest neighbor ($k$ -NN) algorithm, and also the classic average signal-to-noise ratio (SNR)-based solutions. Moreover, analysis shows that both the multi-layer SBL algorithm and the DNN-assisted adaptive modulator achieve better performance than their respective conventional counterparts while at a significantly lower computational complexity cost. [ABSTRACT FROM AUTHOR]

In this paper, we propose a reference-modulated permutation index differential chaos shift keying (RM-PI-DCSK) over multipath fading channels. Due to quasi-orthogonal property between different permutated chaotic signals, the proposed scheme can remarkably suppress the inter-sequence interference to recover the desired information. Moreover, the proposed RM-PI-DCSK has one more modulation bit in the reference segment than the conventional permutation index differential chaos shift keying (PI-DCSK). Both the reference signal in the first time-slot and a permuted replica of the reference in the second time-slot are modulated for efficient transmission. The theoretical bit-error-rate (BER) performance and the highly consistent simulation results demonstrate that the proposed RM-PI-DCSK can achieve a performance gain 3 dB over the conventional PI-DCSK at a BER of $10^{-4}$ , and this gain becomes larger in a high-delay-spread channel. In particular, the performance superiority of the RM-PI-DCSK is further demonstrated in a typical ultra-wideband (UWB) channel with narrow-band interference. Therefore, this proposed scheme can be deemed as an efficient transmission alternative for chaotic-based wireless communications, such as in wireless local area network (WLAN) applications and indoor applications of the transmitted-reference UWB. [ABSTRACT FROM AUTHOR]

In this paper, a pervasive wireless channel modeling theory is first proposed, which uses a unified channel modeling method and a unified equation of channel impulse response (CIR), and can integrate important channel characteristics at different frequency bands and scenarios. Then, we apply the proposed theory to a three dimensional (3D) space-time-frequency (STF) non-stationary geometry-based stochastic model (GBSM) for the sixth generation (6G) wireless communication systems. The proposed 6G pervasive channel model (6GPCM) can characterize statistical properties of channels at all frequency bands from sub-6 GHz to visible light communication (VLC) bands and all scenarios such as unmanned aerial vehicle (UAV), maritime, (ultra-)massive multiple-input multiple-output (MIMO), reconfigurable intelligent surface (RIS), and industry Internet of things (IIoT) scenarios. By adjusting channel model parameters, the 6GPCM can be reduced to various simplified channel models for specific frequency bands and scenarios. Also, it includes standard fifth generation (5G) channel models as special cases. In addition, key statistical properties of the proposed 6GPCM are derived, simulated, and verified by various channel measurement results, which clearly demonstrates its accuracy, pervasiveness, and applicability. [ABSTRACT FROM AUTHOR]

In future wireless communication systems, intelligent reflecting surface (IRS) plays an important role since it is capable of dynamically reconfiguring the channel conditions. In this paper, we apply IRS to facilitate the communication of an uplink multiple-input multiple-output non-orthogonal multiple access system. The objective is to maximize the system energy-efficiency (EE), requiring a joint optimization of the active beamforming at the base station, passive beamforming at the IRS, and power allocation. An iterative method is proposed to solve the formulated multi-variable non-convex optimization problem. Moreover, a low-complexity user ordering method is provided. Numerical results verify the rapid convergence of the iterative optimization scheme and the effectiveness of the user ordering. In addition, a substantial gain can be obtained by employing the proposed scheme over the benchmark schemes without IRS and with orthogonal multiple access. [ABSTRACT FROM AUTHOR]

Objective: This paper aims to introduce a wearable solution and a low-complexity algorithm for real-time continuous ambulatory respiratory monitoring. Methods: A wearable chest patch is designed using a bioimpedance (BioZ) sensor to measure the changes in chest impedance caused by breathing. Besides, a medical-grade infrared temperature sensor is utilized to monitor body temperature. The computing algorithm implemented on the patch enables computation of breath-by-breath respiratory rate and chest temperature in real-time. Two wireless communication protocols are included in the system, namely Bluetooth and Long Range (LoRa), which enable both short-range and long-range data transmission. Results: The breathing rate measured in static (i.e., standing, sitting, supine, and lateral lying) and dynamic (i.e., walking, running, and cycling) positions by our device yielded an accuracy of more than 97.8% and 98.5% relative to the ground truth, respectively. Additionally, the device’s performance is evaluated in real-world scenarios both indoors and outdoors. Conclusion: The proposed system is capable of measuring breathing rate throughout a variety of daily activities. To the best of our knowledge, this is the first BioZ-based wearable patch capable of detecting breath-by-breath respiratory rate in real-time remotely under unrestricted ambulatory conditions. Significance: This study establishes a strategy for continuous respiratory monitoring that could aid in the early detection of cardiopulmonary disorders in everyday life. [ABSTRACT FROM AUTHOR]

The differential chaos shift keying with code index modulation (CIM-DCSK) using Walsh codes can increase the data rate, but error rate performance degrades over practical multipath channel with high delay spread. To tackle this drawback, this paper proposes a parallel CIM-DCSK (PT-CIM-DCSK), where the first time slot is used to transmit the chaotic reference sequence, and the second slot is used to transmit the multiple sequences carrying data bits. In particular, multiple $q$ chaotic sequences are added for data transmission in parallel, and each sequence is modulated by CIM-DCSK with $m_{c}$ bits. By exploiting the quasi-orthogonal characteristics of permuted chaotic signals, the interference between $q$ sequences can be remarkably suppressed. In this way, given the data rate, PT-CIM-DCSK can achieve a larger length of Walsh segment than the CIM-DCSK, since its parallel transmission compensates the rate. In addition, the error performance of the proposed scheme over the multipath Rayleigh fading channel is theoretically analyzed. The theoretical and consistent simulation results demonstrate that the PT-CIM-DCSK can obtain significant performance gains over the conventional CIM-DCSK, and the gain can be up to 5 dB in multipath fading channel with high delay. This is because the larger Walsh segment of PT-CIM-DCSK provides the enhanced robustness against multipath effect. The performance superiority of the proposed scheme is further verified in practical ultra-wideband (UWB) wireless industrial scenarios, which suggests promising for low-cost and low-complexity wireless communication applications. [ABSTRACT FROM AUTHOR]

Let $n$ be a positive integer and $p$ a prime. The power mapping $x^{p^{n}-3}$ over ${\mathbb {F}}_{p^{n}}$ has desirable differential properties, and its differential spectra for $p=2,\,3$ have been determined. In this paper, for any odd prime $p$ , by investigating certain quadratic character sums and some equations over ${\mathbb {F}}_{p^{n}}$ , we determine the differential spectrum of $x^{p^{n}-3}$ with a unified approach. The obtained result shows that for any given odd prime $p$ , the differential spectrum can be expressed explicitly in terms of $n$. Compared with previous results, a special elliptic curve over ${\mathbb {F}}_{p}$ plays an important role in our computation for the general case $p \ge 5$. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surface (IRS)-enhanced wireless communication is one of the critical technologies of the sixth generation mobile communication, which has recently emerged as an innovative solution to the realization of intelligent transportation. It can meet the increasing demand for high-speed railway (HSR) communications services. In this paper, we consider a train-ground TDD wireless mobile communication paradigm to deploy two IRSs on the roadside and the train roof to assist the wireless transmission for the HSR communication system. To achieve the more significant performance gain, in the uplink transmission phase, we propose the practical channel estimation framework of the MIMO system aided by double IRSs to acquire reliable channel state information (CSI) of each channel. To facilitate the processing of the three-dimension tensor, we leverage the trilinearity of the parallel factor decomposition to decompose the received signal into a two-dimensional matrix. The Doppler frequency offset compensating scheme and channel tracking scheme based on Kalman-Filter are proposed to further decrease the pilot overheads. Then, in the downlink phase, a block coordinate descent (BCD) algorithm is proposed to handle the data rate maximization problem of double IRSs communication system with the estimated CSI. We reformulate the original problem and decouple the double IRSs phase optimization problem into two single IRS phase optimization non-convex problems under the unit-modulus constraint. The Majorization-Minimization (MM) algorithm is proposed to approximate the optimal solution of the two optimization subproblems. Simulation results corroborate the effectiveness of the proposed channel estimation and phase shifts optimization scheme. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) are widely deployed to enhance the wireless network capacity and to provide communication services to mobile users beyond the infrastructure coverage. Recently, with the help of a promising technology called network virtualization, multiple service providers (SPs) can share the infrastructures and wireless resources owned by the mobile network operators (MNOs). Then, they provide specific services to their mobile users using the resources obtained from MNOs. However, wireless resource sharing among SPs is challenging as each SP wants to maximize their utility/profit selfishly while satisfying the QoS requirement of their mobile users. Therefore, in this paper, we propose joint users association and wireless resource sharing problem in the cell-free UAVs-assisted wireless networks with the objective of maximizing the total network utility of the SPs while ensuring QoS constraints of their mobile users and the resource constraints of the UAVs deployed by MNOs. To solve the proposed mixed-integer non-convex problem, we decompose the proposed problem into two subproblems: users association, and resource sharing problems. Then, a two-sided matching algorithm is deployed in order to solve users association problem. We further deploy the whale optimization and Lagrangian relaxation algorithms to solve the resource sharing problem. Finally, extensive numerical results are provided in order to show the effectiveness of our proposed algorithm. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surface (IRS) is a promising new technology that is able to create a favorable wireless signal propagation environment by collaboratively reconfiguring the passive reflecting elements yet with low hardware and energy cost. In IRS-aided wireless communication systems, channel modeling is a fundamental task for communication algorithm design and performance optimization, which however is also very challenging since in-depth domain knowledge and technical expertise in radio signal propagations are required, especially for modeling the high-dimensional cascaded base station (BS)-IRS and IRS-user channels (also referred to as the reflected channels). In this paper, we propose a model-driven generative adversarial network (GAN)-based channel modeling framework to autonomously learn the reflected channel distribution, without complex theoretical analysis or data processing. The designed GAN (also named as IRS-GAN) is trained to reach the Nash equilibrium of a minimax game between a generative model and a discriminative model. For the single-user case, we propose to incorporate the special structure of the reflected channels into the design of the generative model. While for the multiuser case, we extend the IRS-GAN and present a multiuser IRS-GAN (abbreviated as IRS-GAN-M), where the distributions of the reflected channels associated with different users are learned simultaneously with reduced number of network parameters (as compared to the naive scheme that assigns a dedicated IRS-GAN for each user). Moreover, theoretical analysis is presented to prove that the minimax game in the IRS-GAN-M framework has a global optimum if the generative and discriminative models are given with enough capacity. Simulation results are presented to validate the effectiveness of the proposed IRS-GAN framework. [ABSTRACT FROM AUTHOR]

Wireless communications are vulnerable to cyber attackers, which now have the flexibility to choose their type of attack. In this paper, combined with intelligent reflect surface (IRS), we jointly optimize base station beamforming and IRS reflected beamforming to counter smart attackers, thereby improving system security. Considering that attackers can flexibly choose their attack methods, such as jamming or eavesdropping, we make the base station intelligent by using reinforcement learning, which can predict the attack methods of attackers and choose whether to add artificial noise into the transmitted signals. At the same time, the interaction between the base station and the smart attackers are established as a non-cooperative game, the Nash equilibrium of the game is derived. Based on this, the base station anti-smart attackers strategy based on Deep Q-learning (DQN) is proposed, which can restrain the attack of the attacker to improve the security of the system. It can be verified from the simulation results that the proposed anti-smart attackers strategy can effectively enhance the secrecy rate of the wireless communication system, resist the attacker’s attack, and intelligently transmit artificial noise to improve system security. [ABSTRACT FROM AUTHOR]

Computation over multiple access channels (CoMAC) has been proposed to solve the problem of spectrum scarcity in wireless networks, which combines communication and computation efficiently using the superposition property of wireless channels. In this paper, we consider a multi-cluster CoMAC network, whose performance is affected by the inter-cluster interference and the non-uniform fading. To minimize the sum mean squared error of signals aggregated at different fusion centers (FCs), we propose a transceiver design for multi-cluster CoMAC. Specifically, we adopt a uniform-forcing transmitter design to formulate the receiver design as a quadratic sum-of-ratios problem with nonconvex quadratic constraints. Then, we propose a branch-and-bound algorithm to find its optimal solution with a given error tolerance. To solve the problem in a decentralized way, we develop a distributed algorithm based on the primal decomposition theory. Each subproblem is solved by using the successive convex approximation method. Further combining Lagrange duality, we derive the optimal solution structure of each subproblem, based on which we can find the solution with lower complexity. Simulation results demonstrate the effectiveness of the proposed distributed transceiver design. [ABSTRACT FROM AUTHOR]

We consider performance enhancement of asymmetrically-clipped optical orthogonal frequency division multiplexing (ACO-OFDM) and related optical OFDM schemes, which are variations of OFDM in intensity-modulated optical wireless communications. Unlike most existing studies on specific designs of improved receivers, this paper investigates information theoretic limits of all possible receivers. For independent and identically distributed (IID) complex Gaussian inputs, we obtain an exact characterization of information rate of ACO-OFDM with improved receivers for all SNRs. It is proved that the high-SNR gain of improved receivers asymptotically achieve 1/4 bits per channel use, which is equivalent to 3 dB in electrical SNR or 1.5 dB in optical SNR; as the SNR decreases, the maximum achievable SNR gain of improved receivers decreases monotonically to a non-zero low-SNR limit, corresponding to an information rate gain of 36.3%. For practically used constellations, we derive an upper bound on the gain of improved receivers. Numerical results demonstrate that the upper bound can be approached to within 1 dB in optical SNR by combining existing improved receivers and coded modulation. We also show that our information theoretic analyses can be extended to Flip-OFDM and PAM-DMT. Our results imply that, for the considered schemes, improved receivers may reduce the gap to channel capacity significantly at low-to-moderate SNR. [ABSTRACT FROM AUTHOR]

With the deep integration between the unmanned aerial vehicle (UAV) and wireless communication, UAV-based air-to-ground (AG) propagation channels need more detailed descriptions and accurate models. In this paper, we aim to conduct cluster-based characterization and modeling for AG channels. To our best knowledge, this is the first study that concentrates on the clustering and tracking of multipath components (MPCs) for time-varying AG channels. Based on measurement data at 6.5 GHz with a bandwidth of 500 MHz, we first estimate potential MPCs utilizing the space-alternating generalized expectation-maximization (SAGE) algorithm. Then, we cluster the extracted MPCs by employing K-Power-Means (KPM) algorithm under multipath component distance (MCD) measure. For characterizing time-variant clusters, we exploit a clustering-based tracking (CBT) method, which efficiently quantifies the survival lengths of clusters. Ultimately, we establish a cluster-based channel model, and validations illustrate the accuracy of the proposed model. This work not only promotes a better understanding of AG propagation channels but also provides a general cluster-based AG channel model with certain extensibility. [ABSTRACT FROM AUTHOR]

To commercialize wirelesselectric vehicle charging (WEVC), three critical issues must be resolved: communication between the vehicle assembly (VA) and the ground assembly (GA), metal object detection (MOD) on the GA coil, and position detection (PD) of the VA. This paper proposes a comprehensive system that integrates MOD and PD with VA-GA near-field communication (NFC). A common high-frequency aided carrier is used not only for NFC, but also for MOD and PD. In addition, an array of dual-purpose detection coils is proposed as a sensor for MOD and PD. As a result, the three functions listed above share numerous components and circuits, greatly simplifying the system structure. Furthermore, because the high-frequency aided carrier can operate with or without a power carrier, the preceding three functions are independent of system power status. The proposed method has been validated using a 3.3 kW WEVC prototype operating at 85 kHz. The experimental results show that the proposed system is capable of performing both online and offline NFC, MOD, and PD with high sensitivity while having no impact on wireless charging efficiency. [ABSTRACT FROM AUTHOR]

This paper presents a multi-user, multi-class and multi-layer edge computing-based framework for effective task offloading and computation processes. Important system requirements that were not captured in the existing multi-layer solutions such as offloading, computations and deadline requirements were captured in the system modeling, while both wireless communications and task computation constraints were considered. We considered three layers system, where each device offloads its generated tasks in each time slot to any selected layer for computation. On its arrival at such a selected layer, the task is only accepted if the queue size is below the pre-defined threshold, otherwise, such a task is offloaded to the next layer. Tasks were classified into class 1 and class 2 tasks following tasks’ quality of service requirements. We adopted stochastic geometry, parallel computing and queueing theory techniques to model the performance of the considered integrated edge-fog-cloud computing environment and obtained analysis for various performance metrics of interest. The obtained analyses demonstrate the importance of multi-layer and multi-class edge computing systems towards improving the experience of both delay-sensitive and mission-critical applications in any task offloading environment. [ABSTRACT FROM AUTHOR]

Massive multiple-input multiple-output (M-MIMO) aided positioning technologies have been recently recognized as promising solutions to fulfil the high accuracy requirement of indoor localization systems. In this paper, exploiting a distributed M-MIMO framework, we propose to employ a deep belief network (DBN) to analyze the received signal strengths (RSS) generated by a diffraction model, where the impact from interfering persons on the targeted user equipment (UE) is considered. Next, the preliminary DBN estimates are forwarded to a long-short term memory network (LSTMN), where the trajectory information of the targeted UE can be extracted based on much less historical trajectory information than existing solutions. Then, the three-dimension (3D) coordinates of the UE’s positions can be estimated with a back propagation neural network (BPNN) which combines the outputs of DBN and LSTMN. Finally, extensive simulation results are provided to demonstrate the effectiveness of the proposed BPNN scheme. [ABSTRACT FROM AUTHOR]