Wireless Powered Cooperative Jamming for Secrecy Multi-AF Relaying Networks

This paper studies secrecy transmission with the aid of a group of wireless energy harvesting (WEH)-enabled amplify-and-forward (AF) relays performing cooperative jamming (CJ) and relaying. The source node in the network does simultaneous wireless information and power transfer (SWIPT) with each relay employing a power splitting (PS) receiver in the first phase; each relay further divides its harvested power for forwarding the received signal and generating artificial noise (AN) for jamming the eavesdroppers in the second transmission phase. In the centralized case with global channel state information (CSI), we provide closed-form expressions for the optimal and/or suboptimal AF-relay beamforming vectors to maximize the achievable secrecy rate subject to individual power constraints of the relays, using the technique of semidefinite relaxation (SDR), which is proved to be tight. A fully distributed algorithm utilizing only local CSI at each relay is also proposed as a performance benchmark. Simulation results validate the effectiveness of the proposed multi-AF relaying with CJ over other suboptimal designs.Comment: 29 pages (single column), 9 figures, submitted for possible journal publicatio

Enabling Secure Wireless Communications via Intelligent Reflecting Surfaces

In this paper, we propose to utilize intelligent reflecting surfaces (IRSs) for enhancing the physical layer security of wireless communications systems. In particular, an IRS-assisted secure wireless system is considered, where a multi-antenna transmitter communicates with a single-antenna receiver in the presence of an eavesdropper. To maximize the secrecy rate, both the beamformer at the transmitter and the IRS phase shifts are jointly optimized. Based on the block coordinate descent (BCD) and minorization maximization (MM) techniques, two efficient algorithms are developed to solve the resulting non-convex optimization problem for small- and large-scale IRSs, respectively. Simulation results show that IRSs can significantly improve physical layer security if the proposed algorithms are employed. Furthermore, we reveal that deploying large-scale IRSs is more efficient than enlarging the antenna array size of the transmitter for both boosting the secrecy rate and enhancing the energy efficiency.Comment: 7 pages, 5 figures, in Proc. IEEE Global Commun. Conf. (GLOBECOM), Waikoloa, HI, USA, Dec. 201

Reconfigurable Intelligent Surfaces: Principles and Opportunities

Reconfigurable intelligent surfaces (RISs), also known as intelligent reflecting surfaces (IRSs), or large intelligent surfaces (LISs), have received significant attention for their potential to enhance the capacity and coverage of wireless networks by smartly reconfiguring the wireless propagation environment. Therefore, RISs are considered a promising technology for the sixth-generation (6G) of communication networks. In this context, we provide a comprehensive overview of the state-of-the-art on RISs, with focus on their operating principles, performance evaluation, beamforming design and resource management, applications of machine learning to RIS-enhanced wireless networks, as well as the integration of RISs with other emerging technologies. We describe the basic principles of RISs both from physics and communications perspectives, based on which we present performance evaluation of multi-antenna assisted RIS systems. In addition, we systematically survey existing designs for RIS-enhanced wireless networks encompassing performance analysis, information theory, and performance optimization perspectives. Furthermore, we survey existing research contributions that apply machine learning for tackling challenges in dynamic scenarios, such as random fluctuations of wireless channels and user mobility in RIS-enhanced wireless networks. Last but not least, we identify major issues and research opportunities associated with the integration of RISs and other emerging technologies for application to next-generation networks.Comment: 66 pages, 18 figures, 8 table

Robust AN-Aided Beamforming and Power Splitting Design for Secure MISO Cognitive Radio With SWIPT

A multiple-input single-output cognitive radio downlink network is studied with simultaneous wireless information and power transfer. In this network, a secondary user coexists with multiple primary users and multiple energy harvesting receivers. In order to guarantee secure communication and energy harvesting, the problem of robust secure artificial noise-aided beamforming and power splitting design is investigated under imperfect channel state information (CSI). Specifically, the transmit power minimization problem and the max-min fairness energy harvesting problem are formulated for both the bounded CSI error model and the probabilistic CSI error model. These problems are non-convex and challenging to solve. A one-dimensional search algorithm is proposed to solve these problems based on ${\cal S}\text{-Procedure}$ under the bounded CSI error model and based on Bernstein-type inequalities under the probabilistic CSI error model. It is shown that the optimal robust secure beamforming can be achieved under the bounded CSI error model, whereas a suboptimal beamforming solution can be obtained under the probabilistic CSI error model. A tradeoff is elucidated between the secrecy rate of the secondary user receiver and the energy harvested by the energy harvesting receivers under a max-min fairness criterion.Comment: 30 pages, 8 figures, submitted to IEEE Transactions on Wireless Communication

Secure Beamforming Design in Relay-Assisted Internet of Things

A secure downlink transmission system which is exposed to multiple eavesdroppers and is appropriate for Internet of Things (IoT) applications is considered. A worst case scenario is assumed, in the sense that, in order to enhance their interception ability all eavesdroppers are located close to each other, near the controller and collude to form joint receive beamforming. For such a system, a novel cooperative non-orthogonal multiple access (NOMA) secure transmission scheme for which an IoT device with a stronger channel condition acts as an energy harvesting relay in order to assist a second IoT device operating under weaker channel conditions, is proposed and its performance is analyzed and evaluated. A secrecy sum rate (SSR) maximization problem is formulated and solved under three constraints: i) Transmit power; ii) Successive interference cancellation; iii) Quality of Service. By considering both passive and active eavesdroppers scenarios, two optimization schemes are proposed to improve the overall system SSR. On the one hand, for the passive eavesdropper scenario, an artificial noise-aided secure beamforming scheme is proposed. Since this optimization problem is nonconvex, instead of using traditional but highly complex, bruteforce two-dimensional search, it is conveniently transformed into a convex one by using an epigraph reformulation. On the other hand, for the active multi-antennas eavesdroppers' scenario, the orthogonal-projection-based beamforming scheme is considered, and by employing the successive convex approximation method, a suboptimal solution is proposed. Furthermore, since for single antenna transmission the orthogonal-projection-based scheme may not be applicable a simple power control scheme is proposed.Comment: IEEE Internet of Things Journal, Accepte

Robust and Secure Sum-Rate Maximization for Multiuser MISO Downlink Systems with Self-sustainable IRS

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, 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.Comment: arXiv admin note: text overlap with arXiv:2005.1166

Power-Efficient Resource Allocation for Multiuser MISO Systems via Intelligent Reflecting Surfaces

Intelligent reflecting surfaces (IRSs) are regarded as key enablers of next-generation wireless communications, due to their capability of customizing the wireless propagation environment. In this paper, we investigate power-efficient resource allocation for IRS-assisted multiuser multiple-input single-output (MISO) systems. To minimize the transmit power, both the beamforming vectors at the access point (AP) and phase shifts at the IRS are jointly optimized while taking into account the minimum required quality-of-service (QoS) of the users. To tackle the non-convexity of the formulated optimization problem, an inner approximation (IA) algorithm is developed. Unlike existing designs, which cannot guarantee local optimality, the proposed algorithm is guaranteed to converge to a Karush-Kuhn-Tucker (KKT) solution. Our simulation results show the effectiveness of the proposed algorithm compared to baseline schemes and reveal that deploying IRSs is more promising than leveraging multiple antennas at the AP in terms of energy efficiency.Comment: 6 pages, 4 figures, submitted to IEEE Global Commun. Conf. (GLOBECOM), Taiwan, Dec. 202

Robust and Secure Wireless Communications via Intelligent Reflecting Surfaces

In this paper, intelligent reflecting surfaces (IRSs) are employed to enhance the physical layer security in a challenging radio environment. In particular, a multi-antenna access point (AP) has to serve multiple single-antenna legitimate users, which do not have line-of-sight communication links, in the presence of multiple multi-antenna potential eavesdroppers whose channel state information (CSI) is not perfectly known. Artificial noise (AN) is transmitted from the AP to deliberately impair the eavesdropping channels for security provisioning. We investigate the joint design of the beamformers and AN covariance matrix at the AP and the phase shifters at the IRSs for maximization of the system sum-rate while limiting the maximum information leakage to the potential eavesdroppers. To this end, we formulate a robust nonconvex optimization problem taking into account the impact of the imperfect CSI of the eavesdropping channels. To address the non-convexity of the optimization problem, an efficient algorithm is developed by capitalizing on alternating optimization, a penalty-based approach, successive convex approximation, and semidefinite relaxation. Simulation results show that IRSs can significantly improve the system secrecy performance compared to conventional architectures without IRS. Furthermore, our results unveil that, for physical layer security, uniformly distributing the reflecting elements among multiple IRSs is preferable over deploying them at a single IRS.Comment: 16 pages, 9 figures, submitted to IEEE Journal on Selected Areas in Communications (JSAC), Special Issue on Wireless Networks Empowered by Reconfigurable Intelligent Surface

Symbol-level and Multicast Precoding for Multiuser Multiantenna Downlink: A Survey, Classification and Challenges

Precoding has been conventionally considered as an effective means of mitigating the interference and efficiently exploiting the available in the multiantenna downlink channel, where multiple users are simultaneously served with independent information over the same channel resources. The early works in this area were focused on transmitting an individual information stream to each user by constructing weighted linear combinations of symbol blocks (codewords). However, more recent works have moved beyond this traditional view by: i) transmitting distinct data streams to groups of users and ii) applying precoding on a symbol-per-symbol basis. In this context, the current survey presents a unified view and classification of precoding techniques with respect to two main axes: i) the switching rate of the precoding weights, leading to the classes of block- and symbol-level precoding, ii) the number of users that each stream is addressed to, hence unicast-/multicast-/broadcast- precoding. Furthermore, the classified techniques are compared through representative numerical results to demonstrate their relative performance and uncover fundamental insights. Finally, a list of open theoretical problems and practical challenges are presented to inspire further research in this area.Comment: Submitted to IEEE Communications Surveys & Tutorial

Multi-antenna Wireless Legitimate Surveillance Systems: Design and Performance Analysis

To improve national security, government agencies have long been committed to enforcing powerful surveillance measures on suspicious individuals or communications. In this paper, we consider a wireless legitimate surveillance system, where a full-duplex multi-antenna legitimate monitor aims to eavesdrop on a dubious communication link between a suspicious pair via proactive jamming. Assuming that the legitimate monitor can successfully overhear the suspicious information only when its achievable data rate is no smaller than that of the suspicious receiver, the key objective is to maximize the eavesdropping non-outage probability by joint design of the jamming power, receive and transmit beamformers at the legitimate monitor. Depending on the number of receive/transmit antennas implemented, i.e., single-input single-output, single-input multiple-output, multiple-input single-output and multiple-input multiple-output (MIMO), four different scenarios are investigated. For each scenario, the optimal jamming power is derived in closed-form and efficient algorithms are obtained for the optimal transmit/receive beamforming vectors. Moreover, low-complexity suboptimal beamforming schemes are proposed for the MIMO case. Our analytical findings demonstrate that by exploiting multiple antennas at the legitimate monitor, the eavesdropping non-outage probability can be significantly improved compared to the single antenna case. In addition, the proposed suboptimal transmit zero-forcing scheme yields similar performance as the optimal scheme