Showing papers on "Communications system published in 2021"
TL;DR: A channel estimation framework based on the parallel factor decomposition to unfold the resulting cascaded channel model is proposed and it is demonstrated that the sum rate using the estimated channels always reach that of perfect channels under various settings, thus, verifying the effectiveness and robustness of the proposed estimation algorithms.
Abstract: Reconfigurable Intelligent Surfaces (RISs) have been recently considered as an energy-efficient solution for future wireless networks due to their fast and low-power configuration, which has increased potential in enabling massive connectivity and low-latency communications. Accurate and low-overhead channel estimation in RIS-based systems is one of the most critical challenges due to the usually large number of RIS unit elements and their distinctive hardware constraints. In this paper, we focus on the uplink of a RIS-empowered multi-user Multiple Input Single Output (MISO) uplink communication systems and propose a channel estimation framework based on the parallel factor decomposition to unfold the resulting cascaded channel model. We present two iterative estimation algorithms for the channels between the base station and RIS, as well as the channels between RIS and users. One is based on alternating least squares (ALS), while the other uses vector approximate message passing to iteratively reconstruct two unknown channels from the estimated vectors. To theoretically assess the performance of the ALS-based algorithm, we derived its estimation Cramer-Rao Bound (CRB). We also discuss the downlink achievable sum rate computation with estimated channels and different precoding schemes for the base station. Our extensive simulation results show that our algorithms outperform benchmark schemes and that the ALS technique achieves the CRB. It is also demonstrated that the sum rate using the estimated channels always reach that of perfect channels under various settings, thus, verifying the effectiveness and robustness of the proposed estimation algorithms.
260 citations
TL;DR: 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 is proposed.
Abstract: 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.
236 citations
TL;DR: In this article, three practical operating protocols for simultaneously transmitting and reflecting (STAR) reconfigurable intelligent surfaces (RISs) are investigated, where the incident wireless signal is divided into transmitted and reflected signals passing into both sides of the space surrounding the surface, thus facilitating a fullspace manipulation of signal propagation.
Abstract: The novel concept of simultaneously transmitting and reflecting (STAR) reconfigurable intelligent surfaces (RISs) is investigated, where the incident wireless signal is divided into transmitted and reflected signals passing into both sides of the space surrounding the surface, thus facilitating a full-space manipulation of signal propagation. Based on the introduced basic signal model of ‘STAR’, three practical operating protocols for STAR-RISs are proposed, namely energy splitting (ES), mode switching (MS), and time switching (TS). Moreover, a STAR-RIS aided downlink communication system is considered for both unicast and multicast transmission, where a multi-antenna base station (BS) sends information to two users, i.e., one on each side of the STAR-RIS. A power consumption minimization problem for the joint optimization of the active beamforming at the BS and the passive transmission and reflection beamforming at the STAR-RIS is formulated for each of the proposed operating protocols, subject to communication rate constraints of the users. For ES, the resulting highly-coupled non-convex optimization problem is solved by an iterative algorithm, which exploits the penalty method and successive convex approximation. Then, the proposed penalty-based iterative algorithm is extended to solve the mixed-integer non-convex optimization problem for MS. For TS, the optimization problem is decomposed into two subproblems, which can be consecutively solved using state-of-the-art algorithms and convex optimization techniques. Finally, our numerical results reveal that: 1) the TS and ES operating protocols are generally preferable for unicast and multicast transmission, respectively; and 2) the required power consumption for both scenarios is significantly reduced by employing the proposed STAR-RIS instead of conventional reflecting/transmiting-only RISs.
217 citations
TL;DR: This paper designs a deep learning (DL)-enabled semantic communication system for speech signals, named DeepSC-S, developed based on an attention mechanism by utilizing a squeeze-and-excitation (SE) network, which outperforms the traditional communications in both cases in terms of the speech signals metrics.
Abstract: Semantic communications could improve the transmission efficiency significantly by exploring the semantic information. In this paper, we make an effort to recover the transmitted speech signals in the semantic communication systems, which minimizes the error at the semantic level rather than the bit or symbol level. Particularly, we design a deep learning (DL)-enabled semantic communication system for speech signals, named DeepSC-S. In order to improve the recovery accuracy of speech signals, especially for the essential information, DeepSC-S is developed based on an attention mechanism by utilizing a squeeze-and-excitation (SE) network. The motivation behind the attention mechanism is to identify the essential speech information by providing higher weights to them when training the neural network. Moreover, in order to facilitate the proposed DeepSC-S for dynamic channel environments, we find a general model to cope with various channel conditions without retraining. Furthermore, we investigate DeepSC-S in telephone systems as well as multimedia transmission systems to verify the model adaptation in practice. The simulation results demonstrate that our proposed DeepSC-S outperforms the traditional communications in both cases in terms of the speech signals metrics, such as signal-to-distortion ration and perceptual evaluation of speech distortion. Besides, DeepSC-S is more robust to channel variations, especially in the low signal-to-noise (SNR) regime.
195 citations
TL;DR: A novel, polytope-based method from the class of direct search methods (DSMs) named Nelder–Mead simplex (NMS) is used to solve the optimization problem based on its computational efficiency and yields better convergence performance than the traditional gradient-descent optimization algorithm and a lower computation time and equivalent performance for the blocklength variable as the exhaustive search.
Abstract: Upcoming fifth-generation (5G) networks need to support novel ultrareliable and low-latency (URLLC) traffic that utilizes short packets. This requires a paradigm shift as traditional communication systems are designed to transmit only long data packets based on Shannon’s capacity formula, which poses a challenge for system designers. To address this challenge, this article relies on an unmanned aerial vehicle (UAV) and a reconfigurable intelligent surface (RIS) to deliver short URLLC instruction packets between ground Internet-of-Things (IoT) devices. In this context, we perform passive beamforming of RIS antenna elements as well as nonlinear and nonconvex optimization to minimize the total decoding error rate and find the UAV’s optimal position and blocklength. In this article, a novel, polytope-based method from the class of direct search methods (DSMs) named Nelder–Mead simplex (NMS) is used to solve the optimization problem based on its computational efficiency; in terms of lesser number of required iterations to evaluate objective function. The proposed approach yields better convergence performance than the traditional gradient-descent optimization algorithm and a lower computation time and equivalent performance for the blocklength variable as the exhaustive search. Moreover, the proposed approach allows ultrahigh reliability, which can be attained by increasing the number of antenna elements in RIS as well as increasing the allocated blocklengths. Simulations demonstrate the RIS’s performance gain and conclusively show that the UAV’s position is crucial for achieving ultrahigh reliability in short packet transmission.
142 citations
TL;DR: This paper investigates a novel unmanned aerial vehicles (UAVs) secure communication system with the assistance of reconfigurable intelligent surfaces (RISs), where an UAV and a ground user communicate with each other, while an eavesdropper tends to wiretap their information.
Abstract: This paper investigates a novel unmanned aerial vehicles (UAVs) secure communication system with the assistance of reconfigurable intelligent surfaces (RISs), where a UAV and a ground user communicate with each other, while an eavesdropper tends to wiretap their information. Due to the limited capacity of UAVs, an RIS is applied to further improve the quality of the secure communication. The time division multiple access (TDMA) protocol is applied for the communications between the UAV and the ground user, namely, the downlink (DL) and the uplink (UL) communications. In particular, the channel state information (CSI) of the eavesdropping channels is assumed to be imperfect. We aim to maximize the average worst-case secrecy rate by the robust joint design of the UAV’s trajectory, RIS’s passive beamforming, and transmit power of the legitimate transmitters. However, it is challenging to solve the joint UL/DL optimization problem due to its non-convexity. Therefore, we develop an efficient algorithm based on the alternating optimization (AO) technique. Specifically, the formulated problem is divided into three sub-problems, and the successive convex approximation (SCA), $\mathcal {S}$ -Procedure, and semidefinite relaxation (SDR) are applied to tackle these non-convex sub-problems. Numerical results demonstrate that the proposed algorithm can considerably improve the average secrecy rate compared with the benchmark algorithms, and also confirm the robustness of the proposed algorithm.
137 citations
TL;DR: The state of the art of V-VLC is studied, open research questions are identified and the research community as a whole is introduced and the characteristics of the VLC channel are dug into.
Abstract: Visible Light Communications (VLC) is becoming a mature communication technology, particularly for indoor usage. The application in outdoor environments is especially interesting in the scope of Vehicular VLC (V-VLC), however, there are some critical challenges remaining. In general, VLC is a good complement to Radio Frequency (RF)-based communication. For automotive use cases, V-VLC can benefit from the huge available spectrum and the readily available Light Emitting Diode (LED)-based lighting systems of modern cars. Its Line Of Sight (LOS) characteristics, the directionality of the light, and the smaller collision domain substantially reduces interference. In this survey article, we study the state of the art of V-VLC and identify open issues and challenges. We study the V-VLC communication system as a whole and also dig into the characteristics of the VLC channel. For the beginner in the field, this review acts as a guide to the most relevant literature to quickly catch up with current trends and achievements. For the expert, we identify open research questions and also introduce the V-VLC research community as a whole.
132 citations
TL;DR: This paper addresses the receiver design for an IRS-assisted multiple-input multiple-output (MIMO) communication system via a Tensor modeling approach aiming at the channel estimation problem using supervised (pilot-assisted) methods and presents two channel estimation methods that rely on a parallel factor (PARAFAC) tensor modeling of the received signals.
Abstract: Intelligent reflecting surface (IRS) is an emerging technology for future wireless communications including 5G and especially 6 G. It consists of a large 2D array of (semi-)passive scattering elements that control the electromagnetic properties of radio-frequency waves so that the reflected signals add coherently at the intended receiver or destructively to reduce co-channel interference. The promised gains of IRS-assisted communications depend on the accuracy of the channel state information. In this paper, we address the receiver design for an IRS-assisted multiple-input multiple-output (MIMO) communication system via a tensor modeling approach aiming at the channel estimation problem using supervised (pilot-assisted) methods. Considering a structured time-domain pattern of pilots and IRS phase shifts, we present two channel estimation methods that rely on a parallel factor (PARAFAC) tensor modeling of the received signals. The first one has a closed-form solution based on a Khatri-Rao factorization of the cascaded MIMO channel, by solving rank-1 matrix approximation problems, while the second on is an iterative alternating estimation scheme. The common feature of both methods is the decoupling of the estimates of the involved MIMO channel matrices (base station-IRS and IRS-user terminal), which provides performance enhancements in comparison to competing methods that are based on unstructured LS estimates of the cascaded channel. Design recommendations for both methods that guide the choice of the system parameters are discussed. Numerical results show the effectiveness of the proposed receivers, highlight the involved trade-offs, and corroborate their superior performance compared to competing LS-based solutions.
126 citations
TL;DR: In this paper, the authors propose a federated edge intelligence based architecture for supporting resource-efficient semantic-aware networking, where each user can offload computationally intensive semantic encoding and decoding tasks to edge servers and protect its proprietary model-related information by coordinating via intermediate results.
Abstract: Existing communication systems are mainly built based on Shannon's information theory, which deliberately ignores the semantic aspects of communication. The recent iteration of wireless technology, 5G and beyond, promises to support a plethora of services enabled by carefully tailored network capabilities based on contents, requirements, as well as semantics. This has sparked significant interest in semantic communication, a novel paradigm that involves the meaning of messages in communication. In this article, we first review classic semantic communication frameworks and then summarize key challenges that hinder its popularity. We observe that some semantic communication processes such as semantic detection, knowledge modeling, and coordination can be resource-consuming and inefficient, especially for communication between a single source and a destination. We therefore propose a novel architecture based on federated edge intelligence for supporting resource-efficient semantic-aware networking. Our architecture allows each user to offload computationally intensive semantic encoding and decoding tasks to edge servers and protect its proprietary model-re-lated information by coordinating via intermediate results. Our simulation result shows that the proposed architecture can reduce resource consumption and significantly improve communication efficiency.
121 citations
TL;DR: Simulation results validate the analytical results and show the practical advantages of the proposed double-IRS system with cooperative passive beamforming designs in terms of the maximum signal-to-noise ratio (SNR) and multi-user effective channel rank, respectively.
Abstract: Intelligent reflecting surface (IRS) has emerged as an enabling technology to achieve smart and reconfigurable wireless communication environment cost-effectively. Prior works on IRS mainly consider its passive beamforming design and performance optimization without the inter-IRS signal reflection, which thus do not unveil the full potential of multi-IRS assisted wireless networks. In this paper, we study a double-IRS assisted multi-user communication system with the cooperative passive beamforming design that captures the multiplicative beamforming gain from the inter-IRS channel. Under the general channel setup with the co-existence of both double- and single-reflection links, we jointly optimize the (active) receive beamforming at the base station (BS) and the cooperative (passive) reflect beamforming at the two distributed IRSs (deployed near the BS and users, respectively) to maximize the minimum signal-to-interference-plus-noise ratio (SINR) of all users. Moreover, for the single-user and multi-user setups, we analytically show the superior performance of the double-IRS cooperative system over the conventional single-IRS system in terms of the maximum signal-to-noise ratio (SNR) and multi-user effective channel rank, respectively. Simulation results validate our analytical results and show the practical advantages of the proposed double-IRS system with cooperative passive beamforming designs.
117 citations
TL;DR: In this paper, a review describes challenges, advances, and perspectives on different aspects of the OAM-based optical communications, including (a) OAM generation/detection and (de) multiplexing, (b) classical free-space optical communication links, (c) fiber-based communication links and (d) quantum communication links.
Abstract: Structured light, especially beams carrying orbital angular momentum (OAM), has gained much interest due to its unique amplitude and phase structures. In terms of communication systems, multiple orthogonal OAM beams can be potentially utilized for increasing link capacity in different scenarios. This review describes challenges, advances, and perspectives on different aspects of the OAM-based optical communications, including (a) OAM generation/detection and (de)multiplexing, (b) classical free-space optical communication links, (c) fiber-based communication links, (d) quantum communication links, (e) OAM-based communications in different frequency ranges, (f) OAM-based communications using integrated devices, and (g) novel structured beams for communications.
TL;DR: In this article, a distributed networking protocol for mitigation of interference among FMCW-based automotive radars, including self-interference, using radar and communication cooperation is proposed.
Abstract: In the automotive sector, both radars and wireless communication are susceptible to interference. However, combining the radar and communication systems, i.e., radio frequency (RF) communications and sensing convergence, has the potential to mitigate interference in both systems. This article analyses the mutual interference of spectrally coexistent frequency modulated continuous wave (FMCW) radar and communication systems in terms of occurrence probability and impact, and introduces RadChat, a distributed networking protocol for mitigation of interference among FMCW based automotive radars, including self-interference, using radar and communication cooperation. The results show that RadChat can significantly reduce radar mutual interference in single-hop vehicular networks in less than 80 ms.
TL;DR: Simulation results demonstrate that the deployment of an intelligent reflecting surface (IRS) can help improving the performance of the DRC system in terms of the received SNR, and the proposed algorithm shows fast convergence.
Abstract: Dual-function radar and communication (DRC) system has been recently recognized as a promising approach to solve the spectrum scarcity problem. However, when the target exists within a crowded area where pathloss dominating, the performance of radar may be severely degraded. To tackle this issue, this article proposes for the first time the deployment of an intelligent reflecting surface (IRS) to help the DRC system to enhance the radar detection performance. The IRS can configure the environment around the radar by adaptively adjusting the phases of its reflecting units to strengthen the signal quality toward specific directions, mostly the target direction, and completely null-out transmissions in other directions, mostly the directions toward the communication system. Specifically, in this article, we investigate the joint optimization of the IRS passive phase-shift matrix (PSM) and precoding matrix of the radar-aided basestation for the DRC system. The optimization is carried-out through maximizing the signal-to-noise ratio (SNR) at the radar receiver under both sensing and communication constraints, which turns out to be a nonconvex problem. In order to circumvent this challenging problem, an alternation optimization approach is employed to decouple the optimization variables and split this intractable problem into two subproblems. However, it is still challenging to obtain the optimal PSM due to the high power of the objective function and the unit-modulus constraints. To solve this problem, a majorization–minimization algorithm is conceived to transform the nonconvex problem to an easy to solve quadratic constraint quadratic programming problem. Simulation results demonstrate that the IRS can help improving the performance of the DRC system in terms of the received SNR, and the proposed algorithm shows fast convergence.
TL;DR: In this paper, the authors considered the application of intelligent reflecting surface (IRS) in UAV-based orthogonal frequency division multiple access (OFDMA) communication systems, which exploits both the significant beamforming gain brought by the RIS and the high mobility of UAV for improving the system sum-rate.
Abstract: In this paper, we consider the application of intelligent reflecting surface (IRS) in unmanned aerial vehicle (UAV)-based orthogonal frequency division multiple access (OFDMA) communication systems, which exploits both the significant beamforming gain brought by the IRS and the high mobility of UAV for improving the system sum-rate. The joint design of UAV’s trajectory, IRS scheduling, and communication resource allocation for the proposed system is formulated as a non-convex optimization problem to maximize the system sum-rate while taking into account the heterogeneous quality-of-service (QoS) requirement of each user. The existence of an IRS introduces both frequency-selectivity and spatial-selectivity in the fading of the composite channel from the UAV to ground users. To facilitate the design, we first derive the expression of the composite channels and propose a parametric approximation approach to establish an upper and a lower bound for the formulated problem. An alternating optimization algorithm is devised to handle the lower bound optimization problem and its performance is compared with the benchmark performance achieved by solving the upper bound problem. Simulation results unveil the small gap between the developed bounds and the promising sum-rate gain achieved by the deployment of an IRS in UAV-based communication systems.
TL;DR: In this article, the authors considered a downlink IOS-assisted communication system, where a multi-antenna small base station (SBS) and an IOS jointly perform beamforming, for improving the received power of multiple MUs on both sides of the IOS, through different reflective/refractive channels.
Abstract: Intelligent reflecting surfaces (IRSs), which are capable of adjusting the propagation conditions by controlling the phase shifts of the reflected waves that impinge on the surface, have been widely analyzed for enhancing the performance of wireless systems. However, the reflective properties of widely studied IRSs restrict the service coverage to only one side of the surface. In this paper, to extend the wireless coverage of communication systems, we introduce the concept of intelligent omni-surface (IOS)-assisted communication. More precisely, an IOS is an important instance of a reconfigurable intelligent surface (RIS) that can provide service coverage to the mobile users (MUs) in a reflective and a refractive manner. We consider a downlink IOS-assisted communication system, where a multi-antenna small base station (SBS) and an IOS jointly perform beamforming, for improving the received power of multiple MUs on both sides of the IOS, through different reflective/refractive channels. To maximize the sum-rate, we formulate a joint IOS phase shift design and SBS beamforming optimization problem, and propose an iterative algorithm to efficiently solve the resulting non-convex program. Both theoretical analysis and simulation results show that an IOS significantly extends the service coverage of the SBS when compared to an IRS.
TL;DR: In this article, a fuzzy win or learn fast-policy hill-climbing (WoLF-CPHC) learning approach is proposed to jointly optimize the anti-jamming power allocation and reflecting beamforming strategy, where WoLF is capable of quickly achieving the optimal policy without the knowledge of the jamming model.
Abstract: Malicious jamming launched by smart jammers can attack legitimate transmissions, which has been regarded as one of the critical security challenges in wireless communications. With this focus, this paper considers the use of an intelligent reflecting surface (IRS) to enhance anti-jamming communication performance and mitigate jamming interference by adjusting the surface reflecting elements at the IRS. Aiming to enhance the communication performance against a smart jammer, an optimization problem for jointly optimizing power allocation at the base station (BS) and reflecting beamforming at the IRS is formulated while considering quality of service (QoS) requirements of legitimate users. As the jamming model and jamming behavior are dynamic and unknown, a fuzzy win or learn fast-policy hill-climbing (WoLF–CPHC) learning approach is proposed to jointly optimize the anti-jamming power allocation and reflecting beamforming strategy, where WoLF–CPHC is capable of quickly achieving the optimal policy without the knowledge of the jamming model, and fuzzy state aggregation can represent the uncertain environment states as aggregate states. Simulation results demonstrate that the proposed anti-jamming learning-based approach can efficiently improve both the IRS-assisted system rate and transmission protection level compared with existing solutions.
TL;DR: In this paper, the authors provided fundamental concepts across all types of free space optical (FSO) system, including system architecture comprising of single beam and multiple beams, and further expanded into the investigation of rain and haze effects toward FSO signal propagation.
Abstract: The next generation (NG) optical technologies will unveil certain unique features, namely ultra-high data rate, broadband multiple services, scalable bandwidth, and flexible communications for manifold end-users. Among the optical technologies, free space optical (FSO) technology is a key element to achieve free space data transmission according to the requirements of the future technologies, which is due to its cost effective, easy deployment, high bandwidth enabler, and high secured. In this article, we give the overview of the recent progress on FSO technology and the factors that will lead the technology towards ubiquitous application. As part of the review, we provided fundamental concepts across all types of FSO system, including system architecture comprising of single beam and multiple beams. The review is further expanded into the investigation of rain and haze effects toward FSO signal propagation. The final objective that we cover is the scalability of an FSO network via the implementations of hybrid multi-beam FSO system with wavelength division multiplexing (WDM) technology.
TL;DR: In this paper, the authors have identified full duplex operation as the key enabler for joint communication and sensing (JCAS) systems, and they have explored existing and novel solutions to these aspects from a signal processing perspective.
Abstract: The use of joint communication and sensing (JCAS) systems in efficiently utilizing the scarce RF spectrum has received increased interest in recent years. Due to the (re)use of the same resources by both functions (e.g., frequency of operation, waveforms, and hardware), various design challenges are evident in integrating communication and sensing/radar systems, and novel techniques are required to overcome them to provide both subsystems with optimal performance. We have identified full duplex operation as the key enabler for JCAS systems as discussed in this article. Furthermore, since JCAS systems usually employ large antenna arrays, novel beamforming techniques are required to efficiently manage the sensing and communication beams in addition to self-interference suppression, whereas their joint waveforms need to be optimized considering the performance metrics of both subsystems. These requirements yield design trade-offs to address; existing and novel solutions to these aspects are explored herein from a signal processing perspective. This article also presents experimental full duplex sensing results through over-the-air RF measurements, showcasing the feasibility of integrating sensing systems with communication systems.
Posted Content•
TL;DR: In this article, the authors characterize seven unique defining features of the terahertz (THz) wireless systems: 1) Quasi-opticality of the band, 2) THz-tailored wireless architectures, 3) Synergy with lower frequency bands, 4) Joint sensing and communication systems, 5) PHY-layer procedures, 6) Spectrum access techniques, and 7) Real-time network optimization.
Abstract: Wireless communication at the terahertz (THz) frequency bands (0.1-10THz) is viewed as one of the cornerstones of tomorrow's 6G wireless systems. Owing to the large amount of available bandwidth, THz frequencies can potentially provide wireless capacity performance gains and enable high-resolution sensing. However, operating a wireless system at the THz-band is limited by a highly uncertain channel. Effectively, these channel limitations lead to unreliable intermittent links as a result of a short communication range, and a high susceptibility to blockage and molecular absorption. Consequently, such impediments could disrupt the THz band's promise of high-rate communications and high-resolution sensing capabilities. In this context, this paper panoramically examines the steps needed to efficiently deploy and operate next-generation THz wireless systems that will synergistically support a fellowship of communication and sensing services. For this purpose, we first set the stage by describing the fundamentals of the THz frequency band. Based on these fundamentals, we characterize seven unique defining features of THz wireless systems: 1) Quasi-opticality of the band, 2) THz-tailored wireless architectures, 3) Synergy with lower frequency bands, 4) Joint sensing and communication systems, 5) PHY-layer procedures, 6) Spectrum access techniques, and 7) Real-time network optimization. These seven defining features allow us to shed light on how to re-engineer wireless systems as we know them today so as to make them ready to support THz bands. Furthermore, these features highlight how THz systems turn every communication challenge into a sensing opportunity. Ultimately, the goal of this article is to chart a forward-looking roadmap that exposes the necessary solutions and milestones for enabling THz frequencies to realize their potential as a game changer for next-generation wireless systems.
TL;DR: In this paper, the authors studied efficient channel estimation and passive beamforming designs for a double-intelligent reflecting surface (IRS) aided single-user communication system, where a user communicates with an access point (AP) via the cascaded user-IRS 1IRS 2-AP double-reflection link.
Abstract: In this letter, we study efficient channel estimation and passive beamforming designs for a double-intelligent reflecting surface (IRS) aided single-user communication system, where a user communicates with an access point (AP) via the cascaded user-IRS 1-IRS 2-AP double-reflection link. First, a general channel estimation scheme is proposed for the system under any arbitrary inter-IRS channel, where all coefficients of the cascaded channel are estimated. Next, for the typical scenario with a line-of-sight (LoS)-dominant inter-IRS channel, we propose another customized scheme to estimate two signature vectors of the rank-one cascaded channel with significantly less channel training time than the first scheme. For the two proposed channel estimation schemes, we further optimize their corresponding cooperative passive beamforming for data transmission to maximize the achievable rate with the training overhead and channel estimation error taken into account. Numerical results show that deploying two cooperative IRSs with the proposed channel estimation and passive beamforming designs achieves significant rate enhancement as compared to the conventional case of single IRS deployment.
TL;DR: In this paper, the authors investigated a communication system assisted by multiple UAV-mounted base stations (BSs), aiming to minimize the number of required UAVs and to improve the coverage rate by optimizing the three-dimensional (3D) positions of UAV, user clustering, and frequency band allocation.
Abstract: Recently, unmanned aerial vehicles (UAVs) have attracted lots of attention because of their high mobility and low cost. This article investigates a communication system assisted by multiple UAV-mounted base stations (BSs), aiming to minimize the number of required UAVs and to improve the coverage rate by optimizing the three-dimensional (3D) positions of UAVs, user clustering, and frequency band allocation. Compared with the existing works, the constraints of the required quality of service (QoS) and the service ability of each UAV are considered, which makes the problem more challenging. A three-step method is developed to solve the formulated mixed-integer programming problem. First, to ensure that each UAV can serve more number of users, the maximum service radius of UAVs is derived according to the required minimum power of the received signals for the users. Second, an algorithm based on artificial bee colony (ABC) algorithm is proposed to minimize the number of required UAVs. Third, the 3D position and the frequency band of each UAV are designed to increase the power of the target signals and to reduce the interference. Finally, simulation results are presented to demonstrate the superiority of the proposed solution for UAV-assisted communication systems.
TL;DR: Simulations and numerical results validate that, compared with baseline schemes, the proposed MDP model with DRL based scheme can achieve better wireless energy and data transfer strategies in terms of the higher long-term utility of the UAV.
Abstract: As a typical scenario in future generation communication network applications, UAV-assisted communication can perform autonomous data delivery for massive machine type communication (mMTC), where the data generated from Internet of Things (IoT) devices can be carried and delivered to the corresponding locations with no direct communication channels to the IoT devices. Wireless energy transfer technique can recharge the UAV when the system is in operation, assisting the UAV to continuously collect and deliver data. In this work, we formulate a Markov decision process (MDP) model to describe the energy and data transfer optimization problem for the UAV. To maximize the long-term utility of the UAV, the MDP model is solved by value iteration algorithm to obtain the optimal strategies of the UAV to collect data, deliver data, and receive transferred energy to replenish on-device battery energy storage. Furthermore, to tackle the issues of system state uncertainties, partially observable states, and large state space in UAV-assisted communication systems, we extend the MDP model and solve it by using a ${Q}$ -learning and a deep reinforcement learning (DRL) schemes. Simulations and numerical results validate that, compared with baseline schemes, the proposed MDP model with DRL based scheme can achieve better wireless energy and data transfer strategies in terms of the higher long-term utility of the UAV.
TL;DR: Light is shed on the potential use-cases of RISs in future wireless systems by means of a novel channel modeling methodology as well as a new software tool for RIS-empowered millimeter-wave communication systems.
Abstract: While researchers have set their sights on future wireless networks of 2030, communications through reconfigurable intelligent surfaces (RISs) appears as one of the potential enabling technologies for 6G wireless networking. This article aims to shed light on the potential use-cases of RISs in future wireless systems by means of a novel channel modeling methodology as well as a new software tool for RIS-empowered millimeter-wave communication systems. It is shown by the open-source, user-friendly, and widely applicable SimRIS Channel Simulator, whose 2.0 version is proposed and goes online by this article, that RISs will work under certain use-cases and communication environments. Potential future research directions are also discussed to bridge the gap between the theory and practice of RIS-empowered systems toward their standardization for 6G wireless networks.
31 Aug 2021
TL;DR: This Review examines the development of emerging semiconductor materials—organic semiconductors, colloidal quantum dots and metal halide perovskites—for light-emitting diodes, considering efforts to improve modulation performance and device efficiency, as well as potential applications in on-chip interconnects and light fidelity (Li-Fi).
Abstract: The continuing development of consumer electronics, mobile communications and advanced computing technologies has led to a rapid growth in data traffic, creating challenges for the communications industry. Light-emitting diode (LED)-based communication links are of potential use in both free space and optical interconnect applications, and LEDs based on emerging semiconductor materials, which can offer tunable optoelectronics properties and solution-processable manufacturing, are of particular interest in the development of next-generation data communications. Here we review the development of emerging LED materials—organic semiconductors, colloidal quantum dots and metal halide perovskites—for use in optical communications. We examine efforts to improve the modulation performance and device efficiency of these LEDs, and consider potential applications in on-chip interconnects and light fidelity (Li-Fi). We also explore the challenges that exist in developing practical high-speed LED-based data communication systems. This Review examines the development of emerging semiconductor materials—organic semiconductors, colloidal quantum dots and metal halide perovskites—for light-emitting diodes, considering efforts to improve modulation performance and device efficiency, as well as potential applications in on-chip interconnects and light fidelity (Li-Fi).
17 Mar 2021
TL;DR: In this paper, the authors review fundamental contributions to information security and argue for the simultaneous pivotal role of fundamental limits and coding techniques for secure communication system design, while summarizing these contributions.
Abstract: This tutorial reviews fundamental contributions to information security An integrative viewpoint is taken that explains the security metrics, including secrecy, privacy, and others, the methodology of information-theoretic approaches, along with the arising system design principles, as well as techniques that enable the information-theoretic designs to be applied in real communication and computing systems The tutorial, while summarizing these contributions, argues for the simultaneous pivotal role of fundamental limits and coding techniques for secure communication system design
TL;DR: In this article, the authors proposed an energy-efficient resource allocation (RA) problem in NOMA-backscatter communication networks with QoS guarantee, where the transmit power of the base station and the reflection coefficient of the backscatter device are jointly optimized.
Abstract: Energy efficiency (EE) is an important performance metric in communication systems. However, to the best of our knowledge, the energy-efficient resource allocation (RA) problem in non-orthogonal multiple access enabled backscatter communication networks (NOMA-BackComNet) comprehensively considering the user’s quality of service (QoS) has not been investigated. In this letter, we present the first attempt to solve the EE-based RA problem for NOMA-BackComNet with QoS guarantee. The objective is to maximize the EE of users subject to the QoS requirements of users, the decoding order of successive interference cancellation and the reflection coefficient (RC) constraint, where the transmit power of the base station and the RC of the backscatter device are jointly optimized. To solve this non-convex problem, we develop a novel iteration algorithm by using Dinkelbach’s method and the quadratic transformation approach. Simulation results verify the effectiveness of the proposed scheme in improving the EE by comparing it with the other schemes.
TL;DR: In this paper, a new RIS-aided communication system, where multiple RISs assist in the communication between a multi-antenna base station (BS) and a remote single antenna user by multi-hop signal reflection, was proposed.
Abstract: Intelligent reflecting surface (IRS) has been deemed as a transformative technology to achieve smart and reconfigurable environment for wireless communication. This letter studies a new IRS-aided communication system, where multiple IRSs assist in the communication between a multi-antenna base station (BS) and a remote single-antenna user by multi-hop signal reflection. Specifically, by exploiting the line-of-sight (LoS) link between nearby IRSs, a multi-hop cascaded LoS link between the BS and user is established where a set of IRSs are selected to successively reflect the BS’s signal, so that the received signal power at the user is maximized. To tackle this new problem, we first present the closed-form solutions for the optimal active and cooperative passive beamforming at the BS and selected IRSs, respectively, for a given beam route. Then, we derive the end-to-end channel power, which unveils a fundamental trade-off in the optimal beam routing design between maximizing the multiplicative passive beamforming gain and minimizing the multi-reflection path loss. To reconcile this trade-off, we recast the IRS selection and beam routing problem as an equivalent shortest simple-path problem in graph theory and solve it optimally. Numerical results show significant performance gains of the proposed algorithm over benchmark schemes and also draw useful insights into the optimal beam routing design.
TL;DR: The Back Propagation (BP) neural network model can be used to predict the passage time of vehicles queuing at intersections with an error of less than 10%, and the improved CAN bus communication can improve the data transmission rate.
Abstract: Intelligent control of traffic has significant influence on the scheduling efficiency of urban traffic flow. Therefore, in order to improve the efficiency of vehicles at intersections, first, the Back Propagation (BP) neural network is used to propose a vehicle passing model at the intersection, and based on the intelligent traffic control system model, the Earliest Deadline First (EDF) dynamic scheduling algorithm is used to improve the Controller Area Network (CAN) communication network. Finally, the simulation test is used to evaluate the effectiveness of the proposed model and the improved CAN bus communication network. The results show that the neural network model can be used to predict the passage time of vehicles queuing at intersections with an error of less than 10%. The improved CAN bus communication can improve the data transmission rate, and the success rate of data transmission under different load rates is above 95%. In conclusion, the application of artificial intelligence technology in intelligent traffic system can improve the efficiency of vehicle scheduling and the efficiency of communication system. This research is of great significance to improve the communication performance of the transportation system and scheduling efficiency.
TL;DR: This chapter provides a unified treatment of these bands with particular emphasis on their propagation characteristics, channel models, design and implementation considerations, and potential applications to 6G wireless.
Abstract: With the standardization of 5G, commercial millimeter wave (mmWave) communications has become a reality despite all the concerns about the unfavorable propagation characteristics of these frequencies. Even though the 5G systems are still being rolled out, it is argued that their gigabits per second rates may fall short in supporting many emerging applications, such as 3D gaming and extended reality. Such applications will require several hundreds of gigabits per second to several terabits per second data rates with low latency and high reliability, which are expected to be the design goals of the next generation 6G communications systems. Given the potential of terahertz (THz) communications systems to provide such data rates over short distances, they are widely regarded to be the next frontier for the wireless communications research. The primary goal of this chapter is to equip readers with sufficient background about the mmWave and THz bands so that they are able to both appreciate the necessity of using these bands for commercial communications in the current wireless landscape and to reason the key design considerations for the communications systems operating in these bands. Towards this goal, this chapter provides a unified treatment of these bands with particular emphasis on their propagation characteristics, channel models, design and implementation considerations, and potential applications to 6G wireless. A brief summary of the current standardization activities related to the use of these bands for commercial communications applications is also provided.
TL;DR: This article pioneers an unprecedented strategy of secure transmission, in which intelligent reflecting surface (IRS) is used as a backscatter device to form and scatter jamming signal while the transmitter (Alice) is regarded as a radio-frequency source.
Abstract: This paper pioneers an unprecedented strategy of secure transmission, in which intelligent reflecting surface (IRS) is used as a backscatter device to form and scatter jamming signal while the transmitter (Alice) is regarded as a radio frequency (RF) source. Specifically, Alice transmits confidential signal to a single-antenna legitimate user (Bob) while the transmission is overheard by multiple single-antenna illegitimate users (Eves). The beamformer at Alice is designed to align with the estimated channel vector from Alice to Bob, in order that the proposed strategy is completely compatible with the common communication system without respect to wiretap. To achieve secure transmission, IRS is deployed to modulate the received confidential signal to jamming signal and reflect it so as to deteriorate the reception at Eves. Based on this model, the reflection coefficient vector of IRS is optimized to minimize the eavesdropped information amount while guaranteeing the reliable communication at Bob. By comparing with the familiar IRS-based beamforming scheme and the cooperative jamming scheme in extensive simulations, the feasibility and secrecy performance gain are confirmed for the proposed strategy of IRS-based backscatter jamming.