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In this paper, we study how to achieve network utility maximization (NUM) in flow-level wireless networks, which can be characterized by the random arrivals and departures of flow-level traffic in such networks. Existing work in this area has mainly concentrated on finding the stability region in such networks while achieving the NUM objective. In this paper, we propose a fully distributed adaptive CSMA based flow-level cross-layer resource allocation algorithm (FLRA), which achieves the NUM goal while satisfying desired delay requirement via optimized link scheduling at the MAC layer and optimal flow-level admission control at the transport layer. Detailed algorithm design is presented. We analyze the convergence property of FLRA and its optimality in terms of network utility while meeting desired delay requirement. We further reveal the relationship among maximum network utility, desired delay, and number of active flows when a network reaches stability. We conduct extensive simulations and the results validate the effectiveness of our analytical results. [ABSTRACT FROM AUTHOR]

There has been much increased interest in the academic and industrial research communities on vehicular ad-hoc networks (VANETs). In this paper, we present an analytical model to study the end-to-end delay in a one-way VANET. This paper proposes an analytical formula for the end-to-end delay probability distribution. Using the derived probability distribution, the probability that the end-to-end delay is lower than a given threshold may be calculated. In addition, one can straightforwardly study the impact of parameters such as wireless communication range, vehicular densities, distance between source the destination, and minimum and maximum vehicle speeds on the end-to-end delay. This can help to better understand data dissemination in VANETs. Moreover, closed forms for lower and upper bounds on the end-to-end delay probability distribution are obtained. Extensive simulation results demonstrate the accuracy of our analysis. [ABSTRACT FROM AUTHOR]

The future connectivity landscape, and notably, the 5G wireless systems will feature Ultra-Reliable Low Latency Communication (URLLC). The coupling of high reliability and low latency requirements in URLLC use cases makes the wireless access design very challenging, in terms of both the protocol design and of the associated transmission techniques. This paper aims to provide a broad perspective on the fundamental tradeoffs in URLLC, as well as the principles used in building access protocols. Two specific technologies are considered in the context of URLLC: massive MIMO and multi-connectivity, also termed interface diversity. This paper also touches on the importance of the proper statistical methodology for designing and assessing extremely high-reliability levels. [ABSTRACT FROM AUTHOR]

Nowadays, wireless communication has become a fabric of our daily life, and it has been a universal demand for higher capacity and longer battery lifetime. For the sake of solving these problems, this paper considers taking the advantage of cooperative communication with the assistance of green relays. So, in this paper, we design an auction market that is composed of one base station (acts as the auctioneer), multiple green relays (act as sellers), and multiple mobile terminals (act as buyers). The terminals need to pay for the cooperative service, and the relays sell it for revenue. In addition, the terminals can raise their bid according to their residual energy; thus the terminals that lack energy have more opportunities to get cooperative service to avoid energy exhaustion. At the same time, the relays can reduce the price based on their instantaneous energy harvesting amount, and, hence, the relays can serve more terminals when they can harvest more energy from the environment. This paper also proposes three different auction rules to show the effect of relay selection. Furthermore, power allocation among relays and terminals is adopted to minimize the power consumption of terminals under the SNR requirement. Simulation results show that the three relay selection rules perform diversely and have their own advantages and disadvantages, but all of them can improve system capacity and prolong the lifetime of the mobile terminals effectively. And, with power allocation, the terminal can utilize the least energy to achieve its SNR requirement. [ABSTRACT FROM AUTHOR]

In wireless communication systems, the correlation among the antennas of diversity systems can hardly be neglected. To the best of our knowledge, no previous studies have attended to address, thoroughly, this problem for the cross-correlation-based detectors. This will be the topic of this paper. Namely, in this paper, we consider the performance assessment of a second-order decision metric that is based on the cross correlation of antenna's output. The detector performance analysis has been made concerning the receiver operating characteristic curves, the robustness to estimation uncertainty, and the design parameters. This last introduces the minimum required sample number that guarantees a given detection performance. To this end, the probability distribution of the inner product of two complex non-zero-mean partially correlated random vectors is investigated. Next, we exhibited the relevance of our results through the analytical performance derivation of the cross-correlation-assisted sensing approach in terms of design parameters, spectral efficiency, and decision reliability. Monte Carlo simulations are achieved to prove the tightness of our derived results. [ABSTRACT FROM AUTHOR]

High-speed digital signals may generate significant radiated emission and affect nearby wireless communication devices. The undesirable electromagnetic interference (EMI) of USB 3.0 to the 2.4-GHz ISM band is a well-known example. Common solutions such as shielding or layout improvement usually focus on controlling the coupling path, while few works considered the possibility of using data encoding. Based on our previous work, this paper presents a new coding method to reduce EMI at the source, with a key feature of being compatible with the conventional 8b/10b line code. In particular, the control symbols in 8b/10b are used to achieve spectrum suppression at specific target frequencies. By properly inserting preselected control symbols constantly to the output stream, a single band 7–15 dB, or dual band near 10 dB, spectrum reduction can be achieved, hence opening a window in spectrum suitable for wireless communication. The proposed coding demands a new encoder at the transmitter side, but only a slightly modified 8b/10b decoder is required at the receiver side. Various simulation and measurement validations are presented in this paper, and a real-time encoder implemented on a field programmable gate array is demonstrated. [ABSTRACT FROM AUTHOR]

A novel approach is here presented to superimpose a low-priority data stream on a high-priority data stream for OFDM systems. The main improvement with respect to conventional hierarchical modulation, which is included with the same purpose in various wireless technologies, is that the low-priority data stream can be decoded from the received subcarrier symbols without any previous equalization for multipath fading channels. As a consequence, the expected performance is nearly invariant of the channel estimation method used to equalize the channel. The low-priority stream is inserted adopting a gain-invariant dirty paper coding based on Rational Dither Modulation, which was proposed for data hiding applications. In this paper an analysis of the developed system is presented and several simulations have been carried out using DVB-T system parameters to verify the validity of the proposed approach. The experimental results show the better performance of the proposed method with respect to that of a conventional hierarchical modulation, particularly when the accuracy of the estimated channel response decreases. [ABSTRACT FROM PUBLISHER]

Ultra-Reliable and Low-Latency Communications (URLLC) has attracted considerable attention because of its potential applications in factory automation, automated driving, and telesurgery anticipated for the era of the sixth-Generation (6G) networks. In URLLC with random channel gains and a hard delay constraint, the scheduling of backlogged queues and finite blocklength coding in the physical layer will make it very challenging to specify its performance limits. In this paper, we focus our attention on the asymptotic cross-layer analysis of URLLC when the Signal-to-Noise Ratio (SNR) is sufficiently high. More specifically, we find that a fundamental tradeoff exists among the service capability, latency, and error probability in the high SNR regime, which is characterized by a gain conservation equation. The main result of this work reveals that the sum of our defined service rate gain, real-time gain, and reliability gain is equal to one under the optimal policy. Numerical simulations are also exploited to validate that the derived gain conservation equation holds even with bounded random arrival. [ABSTRACT FROM AUTHOR]

To expedite research progress on terahertz (THz) communications, we analyze the outage performance of THz communication systems by a compound channel model in this paper. Different from existing models, the compound channel model incorporates the effects of spreading loss, molecular absorption loss, shadowing, and multi-path fading via a composite distribution. By using this model, we maintain an equilibrium of the outage performance analysis between mathematical tractability and the fidelity of realistic THz channels. Specifically, by utilizing the compound channel model, outage performance analysis can get rid of sophisticated case-specific channel modeling relying on field measurement and the ray-tracing assessment. To facilitate the application of the proposed channel model, we also design a maximum likelihood estimation (MLE) based channel parameter estimation approach for the compound channel model. The analytical results of outage performance by using the compound channel model are given in closed form and verified by numerical results. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surfaces (RISs) are envisioned to be a disruptive wireless communication technique that is capable of reconfiguring the wireless propagation environment. In this paper, we study a free-space RIS-assisted multiple-input single-output (MISO) communication system in far-field operation. To maximize the received power from the physical and electromagnetic nature point of view, a comprehensive optimization, including beamforming of the transmitter, phase shifts of the RIS, orientation and position of the RIS is formulated and addressed. After exploiting the property of line-of-sight (LoS) links, we derive closed-form solutions of beamforming and phase shifts. For the non-trivial RIS position optimization problem in arbitrary three-dimensional space, a dimensional-reducing theory is proved. The simulation results show that the proposed closed-form beamforming and phase shifts approach the upper bound of the received power. The robustness of our proposed solutions in terms of the perturbation is also verified. Moreover, the RIS significantly enhances the performance of the mmWave/THz communication system. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a secure mobile edge computing (MEC) network in the presence of multiple eavesdroppers, where multiple users can offload parts of their tasks to the computational access point (CAP). The multiple eavesdroppers may overhear the confidential task offloading, which leads to information leakage. In order to address this issue, we present the minimization problem of the secrecy outage probability (SOP), by jointly taking into account the constraints from the latency and energy consumption. With the aim to improve the system secrecy performance, we then introduce three user selection criteria to choose the best user among multiple ones. Specifically, criterion I maximizes the locally computational capacity, while criterion II and III maximize the secrecy capacity and data rate of main links, respectively. For these criteria, we further analyze the system secrecy performance by deriving analytical and asymptotic expressions for the SOP, from which we can conclude important insights for the system design. Finally, simulation and analytical results are provided to verify the proposed analysis. The results show that the three criteria can efficiently safeguard the MEC networks, compared to the traditional local computing and fully offloading, especially with a large value of user number. [ABSTRACT FROM AUTHOR]

With the rapid development of wireless communication techniques, Internet of Things (IoT) has enabled a host of innovative services by deploying numerous distributed nodes to observe diverse phenomena. There are massive observations of phenomena at distributed nodes that need to be sent. Due to the low spectrum efficiency, it is a great challenge for orthogonal multi-access (OMA) schemes to transmit such enormous observations in time. To cope with this challenge, in this paper, we propose a joint compressed sensing (CS) measurement scheme for wireless networks to achieve the efficient observation of multiple phenomena. Specifically, all nodes are divided into multiple groups to observe different phenomena, and their observations are sequentially transmitted to the fusion center (FC) through the coherent multiple access channel (MAC). To evaluate the performance, we derive the total achievable rate, which is heavily influenced by the design of coherent transmission and joint CS measurement. Moreover, we compare the joint CS measurement scheme with the traditional scheme based on OMA by deriving the performance gain. It demonstrates the superiority of the proposed scheme.v To maximize the total achievable rate, we study a non-convex optimization problem of the common-component allocation and the time allocation. To solve this intractable problem, we equivalently convert it into a convex optimization problem by studying the non-convex constraint and propose a low-complexity algorithm to provide the optimal solution. Finally, simulation results are provided to verify the correctness of the theoretical analysis and demonstrate the superior performance of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, we introduce channel prediction to wireless communications aided by intelligent reflecting surface (IRS) in order to reduce the overhead brought by full channel estimation. Hopefully, fine-grained control of reflection coefficients on IRS can still be maintained with sufficiently accurate channel prediction. Innovatively, we consider channel prediction as an analogy to image super-resolution in computer vision since elements on an IRS are normally two-dimensionally arranged, which makes the popular deep learning techniques efficient solution. To this end, we first solve the element control problem via semi-definite relaxation (SDR) and then design an end-to-end deep-learning model for channel prediction. With estimation for only part of the entire channel state information (CSI), the total channel estimation overhead can be significantly reduced. We visually show that the purposed deep-learning model maintains considerably high accuracy for channel prediction, which makes the proposed channel-prediction method outperforms the existing group-based method in terms of achievable rate. Moreover, the tradeoff between channel estimation overhead and channel prediction accuracy is also investigated with numerical results. [ABSTRACT FROM AUTHOR]

This paper investigates covert communications with finite blocklength in the presence of multiple randomly distributed wardens, which are modeled as a Poisson point process (PPP). Specifically, the protection area, which is guarded by the transmitter against the wardens, is introduced in order to enhance the covert communication performance. First, the closed-form expressions of covert communication constraint are derived under both the non-colluding and colluding detection strategies over the channels suffering both path-loss and small scaling fading. Then, considering the constraint of maximum available blocklength, the transmit power and the blocklength are jointly optimized to maximize the average effective covert throughput (AECT). Differing from the existing literature with only one warden, it is demonstrated that the increasing of maximum available blocklength causes the improvement of maximum AECT only when the density of warden is small. In addition, our examinations show that the expansion of the protection area indeed improves the maximum AECT, and the improvement under the non-colluding detection strategy is more significant than that under the colluding detection strategy. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) and ambient backscatter communication (AmBC) have gained a lot of interest as key enabling technologies in wireless communications systems. NOMA is a key player for enhancing spectrum utilization either by multiplexing multiple messages for the same user or allowing multi-users access, while AmBC shows great potential for enhancing both spectrum and energy efficiency for battery-limited devices. In this paper, the performance of a downlink NOMA multiplexing based symbiotic-radio ($SR$) AmBC system is analyzed over Nakagami-m fading channels. New closed-form expressions for the exact and asymptotic outage probabilities are derived. Moreover, we analyze the diversity order and the influence of the system parameters on the outage performances. Besides, we proposed a power allocation optimization technique to achieve an outage-optimal performance. Through representative Monte-Carlo simulations, we have verified the analytical results. Finally, we compared the performance of the proposed system against a benchmark OMA-based system. [ABSTRACT FROM AUTHOR]

This paper studies the integration of the newly-emerged intelligent reflecting surface (IRS) technology into non-orthogonal multiple access (NOMA)-based wireless powered communication networks (WPCNs). We consider two WPCNs which communicate with a common hybrid access point (HAP), where there exists two types of devices in each WPCN, namely information receiving device (IRD) and harvest-then-transmit device (HTTD). Downlink communication from the HAP to IRDs, downlink energy transfer (ET) from the HAP to HTTDs, and uplink information transmission (IT) from the HTTDs to the HAP are assisted by two IRSs, one in each WPCN. Under this setup, we propose efficient algorithms to optimize reflection coefficients, beamforming vectors, and resource allocation for the sake of uplink sum-rate maximization, taking into account the minimum rate requirement at the IRDs. Numerical results show the considerable performance gain of the proposed NOMA-based scheme as compared to the conventional orthogonal multiple access (OMA)-based counterpart. [ABSTRACT FROM AUTHOR]

Deployment of unmanned aerial vehicles (UAVs) as flying base stations to provide specific geographical area with air-to-ground wireless communications is expected to increase dramatically in the coming decades, owing to its flexibility, mobility and autonomy. Moreover, mobile edge computing (MEC) promises significant reduction in latency by caching popular contents at the mobile edge. In this paper, we propose a method to apply mobile edge caching on UAVs in wireless communication systems. By investigating the user request preference with the aid of latent Dirichlet allocation (LDA), the caching strategy can be optimized. In the proposed system, we consider the design of intelligent caching strategies when a number of UAVs are deployed to serve ground users, where each UAV has a limited storage capacity for caching useful user contents. We use LDA to extract the user request preferences in order to intelligently cache data in the UAVs, while we utilize $k$ -means clustering to classify users and to help deploy UAVs. Besides, we consider three user-UAV association criteria, namely the user received signal to noise ratio (SNR), user preferences and the delay. Our simulation results show that, when compared to random caching, the average caching efficiency could be significantly improved from $\text{50}\%$ to $\text{70}\%$ , while the latency of our proposed system can also be greatly reduced. [ABSTRACT FROM AUTHOR]

Terahertz (THz) communication is foreseen to be a key technology for the 6G wireless communications. In this paper, the performance of downlink Terahertz (THz) communication systems with low-resolution digital-to-analog converters (DACs) at the Access Point (AP) and/or finite-bit analog-to-digital converters (ADCs) at the user sides are investigated. Array-of-subarrays architecture is assumed at the AP, where each RF chain uniquely activates a disjoint subset of antennas, each of which is connected to an exclusive phase shifter. Hybrid precodings including maximum ratio transmission (MRT) and zero-forcing (ZF) precoding are considered. The best beamsteering direction for the phase shifters in the large subarray antenna regime is first proved to be the direction of the line-of-sight (LOS) path. Subsequently, the closed-form expression of the lower-bound of the achievable rate in the large subarray antenna regime is derived, which is the same for both MRT and ZF and is independent of the transmit power. Moreover, numerical results show that the rate loss caused by the phase uncertainties can be negligible in large subarray antenna regime and moderate resolution DACs and ADCs can achieve performance close to the infinite-resolution one. Numerical results validating the analysis are provided as well. Overall, the impact of finite-bit precoding and finite-bit ADCs on the achievable rate of indoor THz communication systems is characterized. [ABSTRACT FROM AUTHOR]

This paper investigates a novel intelligent reflecting surface (IRS)-based symbiotic radio (SR) system architecture consisting of a transmitter, an IRS, and an information receiver (IR). The primary transmitter communicates with the IR and at the same time assists the IRS in forwarding information to the IR. Based on the IRS’s symbol period, we distinguish two scenarios, namely, commensal SR (CSR) and parasitic SR (PSR), where two different techniques for decoding the IRS signals at the IR are employed. We formulate bit error rate (BER) minimization problems for both scenarios by jointly optimizing the active beamformer at the base station and the phase shifts at the IRS, subject to a minimum primary rate requirement. Specifically, for the CSR scenario, a penalty-based algorithm is proposed to obtain a high-quality solution, where semi-closed-form solutions for the active beamformer and the IRS phase shifts are derived based on Lagrange duality and Majorization-Minimization methods, respectively. For the PSR scenario, we apply a bisection search-based method, successive convex approximation, and difference of convex programming to develop a computationally efficient algorithm, which converges to a locally optimal solution. Simulation results demonstrate the effectiveness of the proposed algorithms and show that the proposed SR techniques are able to achieve a lower BER than benchmark schemes. [ABSTRACT FROM AUTHOR]

In this paper, the concept of opportunistic bits (OBs) is developed in short-packet communications and investigated from a finite blocklength perspective. In the OB-based transmission, the data unit of a packet is divided into two parts: OBs and conventional bits (CBs). The OBs are not physically transmitted but used to indicate the index of the time slot (TS) when the packet containing CBs is transmitted. The loading of a bulk of OB-based packets into multiple TSs can be modelled as a Repeated Balls-into-Bins process with a multi-queue storage. If the bulk is not large enough, certain combination(s) of OBs will not appear, which leaves certain TS(s) empty and hence reduces the TS load efficiency. To evaluate the OB-based transmission performance, we formulate its maximal payload rate and TS load efficiency. With the aid of these two formulations, the energy gain, the goodput, and the latency of OB-based short-packet communications are derived and obtained in analytical forms. For achieving further insights, illustrative numerical results on the resource utilisation efficiency and the performance not only substantiate the advantages of the OB-based transmission over the conventional but also provide useful tools and specifications for its design in massive short-packet communications. [ABSTRACT FROM AUTHOR]

Covert wireless communications aim to hide the existence of transmission behavior from watchful adversaries to enhance security. In this paper, we propose a spectrum mask based covert communication strategy in Internet of Things (IoT) networks, where the overt channels are leveraged to enhance the covertness. Specifically, the legitimate IoT transmitter superimposes its own message on the overt channel to avoid being detected by the warden. We assume that proper Gaussian signaling (PGS) is adopted at the overt channel, and improper Gaussian signaling (IGS) is adopted at the legitimate transmitter to improve the covert transmission performance. To maximize the covert rate of the legitimate IoT system, a joint transmit power and IGS factor optimization problem is formulated under the constraints of covertness requirement. The metric of minimum error detection probability, that represents the worst-case for the legitimate transmitter, is utilized to measure the covertness. By exploiting the piece-wise monotonic properties of the objective function and the constraints, we derive the optimal transmit power and IGS factor pairs in both the IGS and PGS schemes. Finally, extensive numerical results are presented to demonstrate that the IGS scheme can improve the covert rate compared to the PGS scheme under a given covertness constraint. [ABSTRACT FROM AUTHOR]

In maritime wireless communications, unmanned surface vehicles (USVs) can improve coverage and transmission performance due to their agile maneuverability and flexible deployment. This paper considers a USV-enabled maritime wireless network, where a USV is employed to assist the communication between the terrestrial base station and ships. Considering the maritime environment characteristics and earth curvature, we establish the systematic USV kinetics and information transmission models. To guarantee fairness, we aim to maximize the minimum expected throughput overall ships by jointly optimizing the trajectory and communication resource allocation, subject to the constraints of the USV kinetics, safe sailing, breakpoint distances, line-of-sight links, resource allocation, and information-causality. Due to the complexity of the maritime two-ray signal propagation model, we propose a channel approximation method to find an upper bound of the throughput for the original problem. By the problem decomposition, two sub-problems are derived and solved iteratively using successive convex approximation and interior-point methods. Simulation results confirm the effectiveness of the proposed method and show that USV can significantly improve transmission performance in maritime wireless networks. [ABSTRACT FROM AUTHOR]

TeraHertz (THz) wireless communication constitutes a promising technique of satisfying the ever-increasing appetite for high-rate services. However, the ultra-wide bandwidth of THz communications requires high-speed, high-resolution analog-to-digital converters, which are hard to implement due to their high complexity and power consumption. In this paper, a deep learning-assisted THz receiver is designed, which relies on single-bit quantization. Specifically, the imperfections of THz devices, including their in-phase/quadrature-phase imbalance, phase noise and nonlinearity are investigated. The deflection ratio of the maximum-likelihood detector used by our single-bit-quantization THz receiver is derived, which reveals the effect of phase offset on the demodulation performance, guiding the architecture design of our proposed receiver. To combat the performance loss caused by the above-mentioned distortions, a twin-phase training strategy and a neural network based demodulator are proposed, where the phase offset of the received signal is compensated before sampling. Our simulation results demonstrate that the proposed deep learning-assisted receiver is capable of achieving a satisfactory bit error rate performance, despite the grave distortions encountered. [ABSTRACT FROM AUTHOR]

In this paper, we study an unmanned aerial vehicle (UAV)-enabled wireless powered communication network, where a UAV serves multiple energy constrained wireless sensor nodes (WSNs). In such a network, a UAV transmits wireless power to a group of WSNs which exploits the harvested power to transfer their own information towards the UAV in the uplink. For practical scenarios, a nonlinear energy harvesting saturation model is considered at WSNs. We aim to design resource allocation which maximizes the achievable sum rate in the uplink and minimizes the downlink transmit power simultaneously. The design is formulated as a multi-objective optimization problem (MOOP) which optimizes the UAV's 3D position, its transmit power, the time splitting ratio, the uplink transmission time and the beamwidth angle of the UAV. The formulated problem is a non-convex problem which is generally intractable. To address the MOOP, a weighted Tchebycheff method is proposed. The numerical results show a trade-off between the minimum power in the downlink and the maximum rate as well as energy efficiency in the uplink. [ABSTRACT FROM AUTHOR]

Optical wireless networks, particularly free-space optical (FSO) in outdoor environments and visible light communication (VLC) in indoor environments, suffer from severe deterioration in signal quality due to various factors such as the availability of line-of-sight link, the turbulence of the atmosphere, or pointing errors. To enable high-quality service point-to-point transmission through optical wireless communication, an efficient and reliable backhaul link is essential. Towards this objective, this paper proposes a novel optical backhauled non-orthogonal multiple access (NOMA) in VLC systems. Unlike earlier works, our model considers the effects of various transmission parameters in a mixed cooperative FSO/radio over a fiber backhaul link with NOMA-VLC to serve two users. The closed-form expressions of outage probability, sum throughput, ergodic sum capacity, and average bit error rate are delivered for a variety of channel conditions using Meijer's G and Gaussian hypergeometric functions. More specifically, both the theoretical and simulation results demonstrate that the performance gain of the proposed optical-based NOMA systems can improve the performance of the users in comparison with the conventional OMA systems at medium to high SNR ranges. Furthermore, a deep learning-based framework is proposed to accurately estimate the ergodic capacity of the proposed system and significantly reduce the complexity cost of the theoretical analysis. [ABSTRACT FROM AUTHOR]

Pilot spoofing attack brings new challenges to physical layer secure transmission. However, this method will not work without any knowledge about the pilot sequence and active eavesdropping can be detected by constructing random pilot sequence. Intelligent reflecting surface (IRS), with the real-time programmable features for wireless channels, provides new possibilities for effective pilot spoofing. In this paper, the IRS is deployed near the legitimate users and the legitimate signal can always be passively reflected. Then the control strategy is embedded into the communication process under time-division duplex mode to assist eavesdroppers to conduct pilot spoofing. By setting different phase shifts at the IRS during the uplink phase and downlink phase, the channel reciprocity disappears, and thus secure beamforming vector is biased towards the eavesdropper. Furthermore, in order to overhear more information, the average secrecy rate minimization problem based on statistical channel state information is established by carefully designing the phase shifts, which is non-trivial to solve. With alternating optimization and Charnes-Cooper transformation technique, the original problem is transformed into convex form and a near optimal solution is achieved. Finally, simulation results show that our proposed scheme can pose serious secure threat without any energy footprint. What's more, if the IRS is not utilized by the internal users properly, it will bring more threat. [ABSTRACT FROM AUTHOR]

IEEE 802.11p standard defines wireless technology protocols that enable vehicular transportation and manage traffic efficiency. A major challenge in the development of this technology is ensuring communication reliability in highly dynamic vehicular environments, where the wireless communication channels are doubly selective, thus making channel estimation and tracking a relevant problem to investigate. In this paper, a novel deep learning (DL)-based weighted interpolation estimator is proposed to accurately estimate vehicular channels especially in high mobility scenarios. The proposed estimator is based on modifying the pilot allocation of the IEEE 802.11p standard so that more transmission data rates are achieved. Extensive numerical experiments demonstrate that the developed estimator significantly outperforms the recently proposed DL-based frame-by-frame estimators in different vehicular scenarios, while substantially reducing the overall computational complexity. [ABSTRACT FROM AUTHOR]

Driven by the massively growing applications in Internet of Things (IoT) and the new requirements of the six generation (6G) wireless network, the amount of terrestrial mobile devices (TMDs) and data traffic in wireless communications have increased explosively. Consequently, the integrated terrestrial-satellite relay networks (ITSRNs) have emerged to address the issue of the huge wireless traffic with limited allocated resources, which attracts extensive research attention to the field of IoT. Limited improvement of system throughput is realized by configuring terrestrial relays (TR) in the previous works. In this paper, by introducing an aerial relay (AR), we propose a novel structure of ITSRN and investigate the system throughput maximization and energy consumption minimization problems by jointly optimizing power allocation and AR altitude. Specifically, the system implementation includes two periods: satellite to relay (S-R) period and satellite to devices (S-D) period. To maximize the overall system throughput, we propose a joint optimization scheme of the power allocation and altitude of AR. Due to its non-convexity, a bilevel programming method is proposed to obtain the global optimal solution, where the closed-form expressions of power allocation and the optimal altitude of AR are derived. Subsequently, we investigate the energy consumption minimization problem during S-R period, which is formulated as a convex problem. We propose a low complexity algorithm and derive the optimal closed-form solution based on the rigorous mathematical analysis. The effectiveness of the proposed algorithms and solutions are verified by extensive simulations. [ABSTRACT FROM AUTHOR]

Terahertz (THz) communication is now being considered as one of possible technologies for the sixth generation (6G) wireless communication systems. In this paper, a novel three-dimensional (3D) space-time-frequency non-stationary theoretical channel model is first proposed for 6G THz wireless communication systems employing ultra-massive multiple-input multiple-output (MIMO) technologies with long traveling paths. Considering frequency-dependent diffuse scattering, which is a special property of THz channels different from millimeter wave (mmWave) channels, the relative angles and delays of rays within one cluster will evolve in the frequency domain. Then, a corresponding simulation model is proposed with discrete angles calculated using the method of equal area (MEA). The statistical properties of the proposed theoretical and simulation models are derived and compared, showing good agreements. The accuracy and flexibility of the proposed simulation model are demonstrated by comparing the simulation results of the relative angle spread and root mean square (RMS) delay spread with corresponding measurements. [ABSTRACT FROM AUTHOR]

Orbital angular momentum (OAM) at radio frequency (RF) provides a novel approach of multiplexing a set of orthogonal modes on the same frequency channel to achieve high spectral efficiencies (SEs). However, the existing research on OAM wireless communications is mainly focused on point-to-point transmission in the line-of-sight (LoS) scenario. In this paper, we propose an overall scheme of the downlink multi-user OAM (MU-OAM) wireless backhaul based on uniform circular arrays (UCAs) for broadcasting networks, which can achieve the joint spatial division and coaxial multiplexing (JSDCM). A salient feature of the proposed downlink MU-OAM wireless backhaul systems is that the channel matrices are completely characterized by the position of each small base station (SBS), independent of the numbers of subcarriers and antennas, which avoids estimating large channel matrices required by the traditional downlink multi-user multiple-input multiple-output (MU-MIMO) wireless backhaul systems. Thereafter, we propose an OAM-based multi-user distance and angle of arrival (AoA) estimation method, which is able to simultaneously estimate the positions of multiple SBSs with a flexible number of training symbols. With the estimated distances and AoAs, a MU-OAM preprocessing scheme is applied to eliminate the co-mode and inter-mode interferences in the downlink MU-OAM channel. At last, the proposed methods are extended to the downlink MU-OAM-MIMO wireless backhaul system equipped with uniform concentric circular arrays (UCCAs), for which much higher spectral efficiency (SE) and energy efficiency (EE) than traditional MU-MIMO systems can be achieved. Both mathematical analysis and simulation results validate that the proposed scheme can effectively eliminate both interferences of the practical downlink MU-OAM channel and approaches the performance of the ideal MU-OAM channel. [ABSTRACT FROM AUTHOR]

Integrating the wireless power transfer (WPT) technology into the wireless communication system has been important for operational cost saving and power-hungry problem solving of electronic devices. In this paper, we propose a resonant beam simultaneous wireless information and power transfer (RB-SWIPT) system, which utilizes a gain medium and two retro-reflecting surfaces to enhance and retro-reflect energy, and allows devices to recharge their batteries and exchange information from the resonant beam wirelessly. To reveal the SWIPT mechanism and evaluate the SWIPT performance, we establish an analytical end-to-end (E $\mathscr{2}$ E) transmission model based on a modular approach and the electromagnetic field propagation. Then, the intra-cavity power intensity distribution, transmission loss, output power, and E $\mathscr{2}$ E efficiency can be obtained. The numerical evaluation illustrates that the exemplary RB-SWIPT system can provide about 4.20 W electric power and 12.41 bps/Hz spectral efficiency, and shorter transmission distance or larger retro-reflecting surface size can lead to higher E $\mathscr{2}$ E efficiency. The RB-SWIPT presents a new way for high-power, long-range WPT, and high-rate communication. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS), a recently introduced technology for future wireless communication systems, enhances the spectral and energy efficiency by intelligently adjusting the propagation conditions between base stations (BSs) and mobile equipments (MEs). An RIS consists of many low-cost passive reflecting elements that are optimized to improve the quality of the received signal. In this paper, we study the problem of power control at the BS and RIS optimization for application to physical-layer broadcasting. Our goal is to minimize the transmit power at the BS by jointly designing the transmit beamforming at the BS and the phase shifts of the passive elements at the RIS. Furthermore, to help validate the proposed optimization methods, we derive lower bounds to quantify the average transmit power at the BS as a function of the number of MEs, the number of RIS elements, and the number of antennas at the BS. The simulation results demonstrate that the average transmit power at the BS is close to the lower bound in an RIS-aided system, and is significantly lower than the average transmit power in conventional schemes without an RIS. [ABSTRACT FROM AUTHOR]

This paper considers the multiaccess coded caching systems formulated by Hachem et al., including a central server containing $N$ files connected to $K$ cache-less users through an error-free shared link, and $K$ cache-nodes, each equipped with a cache memory size of $M$ files. Each user has access to $L$ neighbouring cache-nodes with a cyclic wrap-around topology. The coded caching scheme proposed by Hachem et al. suffers from the case that $L$ does not divide $K$ , where the needed number of transmissions (a.k.a. load) is at most four times the load expression for the case where $L$ divides $K$. Our main contribution is to propose a novel transformation approach to smartly extend the schemes satisfying some conditions for the well known shared-link caching systems to the multiaccess caching systems. Then we can get many coded caching schemes with different subpacketizations for multiaccess coded caching system. These resulting schemes have the maximum local caching gain (i.e., the cached contents stored at any $L$ neighbouring cache-nodes are different such that the number of retrieval packets by each user from the connected cache-nodes is maximal) and the same coded caching gain as the original schemes. Applying the transformation approach to the well-known shared-link coded caching scheme proposed by Maddah-Ali and Niesen, we obtain a new multiaccess coded caching scheme that achieves the same load as the scheme of Hachem et al. but for any system parameters. Under the constraint of the cache placement used in this new multiaccess coded caching scheme, our delivery strategy is approximately optimal when $K$ is sufficiently large. Finally, we also show that the transmission load of the proposed scheme can be further reduced by compressing the multicast message. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS) has recently received extensive research interest due to its capability to intelligently change the wireless propagation environment. For RIS-aided wireless communications in frequency division duplex (FDD) mode, channel feedback at the user equipment (UE) is essential for the base station (BS) to acquire the downlink channel state information (CSI). In this paper, a dimension reduced channel feedback scheme is proposed to reduce the channel feedback overhead by exploiting the single-structured sparsity of BS-RIS-UE cascaded channel. Since different UEs share the same sparse BS-RIS channel but have their respective RIS-UE channels, there are only limited non-zero column vectors in the BS-RIS-UE cascaded channel matrix, and different UEs share the same indexes of the non-zero columns. Thus, the downlink CSI can be decomposed into user-independent channel information (i.e., the indexes of non-zero columns) and user-specific channel information (i.e., the non-zero column vectors), where the former for all UEs can be fed back by only one UE, while the latter can be fed back with a fairly low overhead by different UEs, respectively. Simulation results show that, compared with the conventional method, the proposed scheme can reduce channel feedback overhead by more than 80% for RIS-aided wireless communications. [ABSTRACT FROM AUTHOR]

Channel estimation is challenging for the reconfigurable intelligent surface (RIS)-aided wireless communications. Since the number of coefficients of the cascaded channel among the base station (BS), the RIS, and the user equipment (UE), is the product of the number of BS antennas, the number of RIS elements, and the number of UEs, the pilot overhead can be prohibitively high. In this paper, we propose a two-timescale channel estimation framework to exploit the property that the BS-RIS channel is high-dimensional but quasi-static, while the RIS-UE channel is mobile but low-dimensional. Specifically, to estimate the quasi-static BS-RIS channel, we propose a dual-link pilot transmission scheme, where the BS transmits downlink pilots and receives uplink pilots reflected by the RIS. Then, we propose a coordinate descent-based algorithm to recover the BS-RIS channel. Since the quasi-static BS-RIS channel is estimated less frequently than the mobile channel is, the average pilot overhead can be reduced from a long-term perspective. Although the mobile RIS-UE channel has to be frequently estimated in a small timescale, the associated pilot overhead is low thanks to its low dimension. Simulation results show that the proposed two-timescale channel estimation framework can achieve accurate channel estimation with low pilot overhead. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surface (IRS) has been recently emerged as an effective way for improving the performance of wireless networks by reconfiguring the propagation environment through a large number of passive reflecting elements. This game-changing technology is especially important for stepping into the Internet of Everything (IoE) era, where high performance is demanded with very limited available resources. In this paper, we study a backscatter-assisted wireless powered communication network (BS-WPCN), in which a number of energy-constrained users, powered by a power station (PS), transmit information to an access point (AP) via backscatter and active wireless information transfer, with their communication being aided by an IRS. Using a practical energy harvesting (EH) model which is able to capture the characteristics of realistic energy harvesters, we investigate the maximization of total network throughput. Specifically, IRS reflection coefficients, PS transmit and AP receive beamforming vectors, power and time allocation are designed through a two-stage algorithm, assuming minimum mean square error (MMSE) receiver at the AP. The effectiveness of the proposed algorithm is confirmed via extensive numerical simulations. We also show that our proposed scheme is readily applicable to practical IRS-aided networks with discrete phase shift values. [ABSTRACT FROM AUTHOR]

In this paper, novel ergodic capacity (EC) performance evaluation results of a power beacon (PB)-assisted multi-input multi-output (MIMO) wireless powered communication network are presented. In the considered system, the energy harvesting node harvests energy from the radio-frequency signals sent by the dedicated PB and uses this energy to communicate with the destination node. To accurately model the combined effect of multi-path fading and shadowing, it is assumed that the energy transfer link is subject to $\kappa$ - $\mu$ shadowed fading. Performance evaluation results are presented for two cases, depending upon the availability of channel state information (CSI) at the PB, namely, $no$ CSI and $full$ CSI. In the former case, equal power allocation is assumed, whereas, in the later case, energy beamforming is employed to increase energy transfer efficiency. For the performance evaluation of EC under $full$ CSI, a closed-form approximation for the probability density function of the maximum eigenvalue of a $\kappa$ - $\mu$ shadowed distributed random matrix is derived. For both $no$ CSI and $full$ CSI cases, lower and upper bounds on the achievable EC are derived in closed-form. Moreover, in order to obtain further insights on the impact of key parameters on the system performance, asymptotic EC expressions which become very tight at low- and high-signal-to-noise ratio regimes, are obtained. Using the proposed EC lower bound as well as these asymptotic results, simple closed-form expressions for the optimal time split that maximize the achievable EC are derived. Numerically evaluated results accompanied with Monte-Carlo simulations are further presented to corroborate the theoretical analysis. [ABSTRACT FROM AUTHOR]

The development of unmanned aerial vehicles (UAVs) is one of the driving forces for revolutionizing wireless communications in the modern era. Although there are many unique features of UAV networks, their widespread use is still hampered by the short battery life. As a result, most of the research efforts in this domain mainly have focused on the efficient use of energy through trajectory planning and cooperative communication. While there have been a few proposals to use energy harvesting techniques for UAV networks, a complete understanding of the performance limits of such networks is still missing in the literature and needs further investigations. Within this context, our paper provides a comprehensive performance evaluation of UAV relay networks (UAVRNs) employing non-orthogonal multiple access (NOMA) technique. Specifically, a cooperative communication system, where a UAV serves as a mobile relay, is fully considered. The UAV relay is considered to be wirelessly-powered and harvests energy from the radio signals received from a nearby base station. For the sake of comparison, both amplify-and-forward (AF) and decode-and-forward (DF) relaying protocols are considered. Subsequently, the closed-form expressions of outage probabilities and ergodic capacities are provided for each UAV relaying protocol. Extensive simulations are performed to verify the accuracy of the derived closed-form expressions. The results provided in this work characterize the outage and ergodic capacity performance of NOMA-enabled UAVRNs. [ABSTRACT FROM AUTHOR]

Thanks to its low transceiver complexity, mode division multiplexing (MDM) using orbital angular momentum (OAM) has been recently investigated as a new physical layer wireless transmission technique. This is due to the fact that different OAM modes are spatially orthogonal to each other, thus, perfectly suitable for spatial multiplexing and/or diversity. The orthogonality amongst different OAM modes is achieved in the absence of any mode offset between the transceivers’ phase-shifting feeding networks. However, the inherent presence of OAM mode offset destroys the orthogonality between different modes, which gives rise to inter-mode interference (IMI). Therefore, in this paper, in order to theoretically analyze the negative impact of OAM mode offset of MDM-OAM systems on the spectral efficiency of line-of-sight free-space wireless communication systems, an explicit signal-to-interference-plus-noise ratio expression for each OAM mode is derived, through which the spectral efficiency degradation is evaluated. Furthermore, in order to support our theoretical analysis, a $9\times 9$ MDM-OAM practical communication experiment for different OAM mode settings is carried out at a microwave frequency of 5.8 GHz. In addition, by leveraging the fact that all circulant matrices always have the same eigendirections, regardless of the entries of the matrix, a low-complexity optimal OAM mode selection scheme is proposed which significantly improves the spectral efficiency of the system. Finally, in order to completely null-out the impact of OAM mode offset, a baseband zero-forcing stage is embedded at the receiver. [ABSTRACT FROM AUTHOR]

Due to transmission of train control and dispatch commands, the ultra high reliability is required for railway wireless communication systems (RWCS). However, the quality of service (QoS) of RWCS is affected by external interference and jamming seriously in railway transportation. The external interference and jamming generated from intentional and/or unintentional sources can disturb the transmission of RWCS and be extremely dangerous for the trains’ safety. In this paper, a reconfigurable intelligent surface (RIS) approach is proposed to suppress the interference and jamming in RWCS. By taking the signal-to-interference-plus-noise (SINR) as the QoS metrics, the interference suppression problem with RIS is transformed into a maximizing receiving SINR problem. Two optimum solutions, which one is based on Charnes-Cooper transformation and the other is based on single linear programming, are provided. In order to deploy the RIS in RWCS practically, two low-complexity sub-optimum solutions, which one is to bypass the channel estimation for interference links and the other is to maximize the receiving desired power, are also discussed. The simulations results show that the RIS can be employed in RWCS with considerable anti-interference gain. [ABSTRACT FROM AUTHOR]

Owing to the flexible mobility and convenient deployment, unmanned aerial vehicle (UAV) aided networks can facilitate many applications. However, the open accessibility of wireless communication brings a great risk of privacy to UAV-based networks. Thus, in this paper, we propose a UAV-aided covert communication scheme assisted by a multi-antenna jammer to maximize the transmission rate between a ground transmitter and a UAV receiver against several randomly distributed wardens. The transmitter adopts the maximum ratio transmission, while the jammer zero-forces its transmitted signal at the UAV to disturb the monitoring at wardens without interfering the legitimate transmission. First, we analyze the detection performance and derive the optimal threshold for each warden to minimize its detection outage probability (DOP). Then, with the worst situation in which all wardens set their respective optimal thresholds to achieve the minimum global DOP, the location and the transmit power of the jammer are optimized to maximize the DOP. The location of UAV and the transmit power of the ground transmitter are also optimized to maximize the transmission rate with the minimum DOP requirement satisfied. Numerical results are provided to demonstrate the effectiveness of the proposed UAV-aided covert communication scheme. [ABSTRACT FROM AUTHOR]

A simple signaling method for broadcast channels with multiple-transmit multiple-receive antennas is proposed. In this method, for each user, the direction in which the user has the maximum gain is determined. The best user in terms of the largest gain is selected. The corresponding direction is used as the modulation vector (MV) for the data stream transmitted to the selected user. The algorithm proceeds in a recursive manner where in each step, the search for the best direction is performed in the null space of the previously selected MVs. It is demonstrated that with the proposed method, each selected MV has no interference on the previously selected MVs. Dirty-paper coding is used to cancel the remaining interference. For the case that each receiver has one antenna, the presented scheme coincides with the known scheme based on Gram-Schmidt orthogonalization (QR decomposition). To analyze the performance of the scheme, an upper bound on the cumulative distribution function (CDF) of each subchannel is derived which is used to establish the diversity order and the asymptotic sum-rate of the scheme. It is shown that using fixed rate codebooks, the diversity order of the jth data stream, 1 ≤ j ≤ M, is equal to N(M - j + 1)(K - j + 1), where M, N, and K indicate the number of transmit antennas, the number of receive antennas, and the number of users, respectively. Furthermore, it is proven that the throughput of this scheme scales as M log log(K) and asymptotically (K → ∞) tends to the sum--capacity of the multiple-input multiple-output (MIMO) broadcast channel. The simulation results indicate that the achieved sum--rate is close to the sum--capacity of the underlying broadcast channel. [ABSTRACT FROM AUTHOR]

Huge overhead of beam training imposes a significant challenge in millimeter-wave (mmWave) wireless communications. To address this issue, in this paper, we propose a wide beam based training approach to calibrate the narrow beam direction according to the channel power leakage. To handle the complex nonlinear properties of the channel power leakage, deep learning is utilized to predict the optimal narrow beam directly. Specifically, three deep learning assisted calibrated beam training schemes are proposed. The first scheme adopts convolution neural network to implement the prediction based on the instantaneous received signals of wide beam training. We also perform the additional narrow beam training based on the predicted probabilities for further beam direction calibrations. However, the first scheme only depends on one wide beam training, which lacks the robustness to noise. To tackle this problem, the second scheme adopts long-short term memory (LSTM) network for tracking the movement of users and calibrating the beam direction according to the received signals of prior beam training, in order to enhance the robustness to noise. To further reduce the overhead of wide beam training, our third scheme, an adaptive beam training strategy, selects partial wide beams to be trained based on the prior received signals. Two criteria, namely, optimal neighboring criterion and maximum probability criterion, are designed for the selection. Furthermore, to handle mobile scenarios, auxiliary LSTM is introduced to calibrate the directions of the selected wide beams more precisely. Simulation results demonstrate that our proposed schemes achieve significantly higher beamforming gain with smaller beam training overhead compared with the conventional and existing deep-learning based counterparts. [ABSTRACT FROM AUTHOR]

Low-latency and energy-efficient wireless communication holds the potential of enabling the industrial internet of things (IIoT), automatic driving, and telesurgery. Cross-layer scheduling, which is aware of both the channel and queue states, has attracted considerable attention recently because it is capable of reducing the average delay substantially while meeting a given average power constraint. As a result, there has been considerable work, in which joint channel and buffer aware scheduling is formulated as a constrained Markov decision process (CMDP). In general, the optimal solution to a CMDP problem is characterized by the stationary probability of actions, yielding probabilistic cross-layer scheduling with possibly high complexity in practice. In this paper, we are interested in the low-latency and energy-efficient stationary cross-layer scheduling policy for wireless channels with continuous channel states, e.g. Rayleigh fading. It is interestingly shown that a deterministic cross-layer scheduling policy can achieve the optimal tradeoff between the average delay and power. In other words, the signaling complexity of cross-layer scheduling can be significantly reduced without causing sub-optimality. Simulation results also demonstrate that our work provides a low-complexity solution for low-latency and energy-efficient wireless communications. [ABSTRACT FROM AUTHOR]

The Terahertz band is envisioned to meet the demanding 100 Gbps data rates for 6G wireless communications. Aiming at combating the distance limitation problem with low hardware-cost, ultra-massive MIMO with hybrid beamforming is promising. However, relationships among wavelength, array size and antenna spacing give rise to the inaccuracy of planar-wave channel model (PWM), while an enlarged channel matrix dimension leads to excessive parameters of applying spherical-wave channel model (SWM). Moreover, due to the adoption of hybrid beamforming, channel estimation (CE) needs to recover high-dimensional channels from severely compressed channel observation. In this paper, a hybrid spherical- and planar-wave channel model (HSPM) is investigated and proved to be accurate and efficient by adopting PWM within subarray and SWM among subarrays. Furthermore, a two-phase HSPM CE mechanism is developed. A deep convolutional-neural-network (DCNN) is designed in the first phase for parameter estimation of reference subarrays, while geometric relationships of the remaining channel parameters between reference subarrays are leveraged to complete CE in the second phase. Extensive numerical results demonstrate the HSPM is accurate at various communication distances, array sizes and carrier frequencies. The DCNN converges fast and achieves high accuracy with 5.2 dB improved normalized-mean-square-error compared to literature methods, and owns substantially low complexity. [ABSTRACT FROM AUTHOR]

This paper investigates robust and secure multiuser multiple-input single-output (MISO) downlink communications assisted by a self-sustainable intelligent reflection surface (IRS), which can simultaneously reflect and harvest energy from the received signals. We study the joint design of beamformers at an access point (AP) and the phase shifts as well as the energy harvesting schedule at the IRS for maximizing the system sum-rate. The design is formulated as a non-convex optimization problem taking into account the wireless energy harvesting capability of IRS elements, secure communications, and the robustness against the impact of channel state information (CSI) imperfection. Subsequently, we propose a computationally-efficient iterative algorithm to obtain a suboptimal solution to the design problem. In each iteration, $\mathcal {S}$ -procedure and the successive convex approximation are adopted to handle the intermediate optimization problem. Our simulation results unveil that: 1) there is a non-trivial trade-off between the system sum-rate and the self-sustainability of the IRS; 2) the performance gain achieved by the proposed scheme is saturated with a large number of energy harvesting IRS elements; 3) an IRS equipped with small bit-resolution discrete phase shifters is sufficient to achieve a considerable system sum-rate of the ideal case with continuous phase shifts. [ABSTRACT FROM AUTHOR]

Symbiotic radio (SR) is a promising technology for energy- and spectrum-efficient wireless communication, which exploits passive communication for Internet-of-Things (IoT) transmission and achieves a mutualistic spectrum sharing between the passive and active transmissions. In this paper, we study an reconfigurable intelligent surface (RIS) empowered symbiotic radio over a broadcasting system, i.e., a base station (BS) broadcasts signals to multiple primary receivers (PRs) under the assistance of an RIS, while the RIS also transmits information to an IoT receiver (IR) by riding over the broadcasting signals. We formulate a problem to minimize the BS’s transmit power by jointly optimizing the BS’s active precoding and the RIS’s passive beamforming, under the signal-to-noise-ratio constraints of the primary and IoT transmissions. However, the problem is challenging to be solved optimally, since the variables are coupled and the constraints are non-convex. An iterative algorithm based on block coordinated descent (BCD) and semidefinite relaxation (SDR) techniques is first proposed, and its convergence together with complexity are analyzed. Then, to tackle the problem of high computational complexity caused by SDR technique, we further propose an alternative algorithm based on generalized power method (GPM) technique. Simulation results validate that the proposed system outperforms the traditional broadcasting system without RIS. The GPM-based algorithm achieves nearly the same transmit power performance as SDR-based algorithm, with a significantly reduced computational complexity. [ABSTRACT FROM AUTHOR]