In this paper, we propose intelligent reflecting surface (IRS) aided multi-antenna physical layer security. We present a power efficient scheme to design the secure transmit power allocation and the surface reflecting phase shift. It aims to minimize the transmit power subject to the secrecy rate constraint at the legitimate user. Due to the non-convex nature of the formulated problem, we propose an alternative optimization algorithm and the semidefinite programming (SDP) relaxation to deal with this issue. Also, the closed-form expression of the optimal secure beamformer is derived. Finally, simulation results are presented to validate the proposed algorithm, which highlights the performance gains of the IRS to improve the secure transmission.

Covert transmission is studied for an intelligent reflecting surface (IRS) aided communication system, where Alice aims to transmit messages to Bob without being detected by the warden Willie. Specifically, an IRS is used to increase the data rate at Bob under a covert constraint. For the considered model, when Alice is equipped with a single antenna, the transmission power at Alice and phase shift at the IRS are jointly optimized to maximize the covert transmission rate with either instantaneous or partial channel state information (CSI) of Willie’s link. In addition, when multiple antennas are deployed at Alice, we formulate a joint transmit beamforming and IRS phase shift optimization problem to maximize the covert transmission rate. One local optimal algorithm and two low-complexity suboptimal algorithms are proposed to solve the problem. Furthermore, for the case of imperfect CSI of Willie’s link, the optimization problem is reformulated by using the triangle and Cauchy-Schwarz inequalities. The reformulated optimization problems are solved using an alterative algorithm, semidefinite relaxation (SDR) and Gaussian randomization techniques. Finally, simulations are performed to verify our analysis. The numerical results show that an IRS can degrade the covert transmission rate when Willie is closer to the IRS than Bob.

This article investigates the intelligent reflecting surface (IRS)-aided multi-antenna covert communications. In particular, with the help of an IRS, a favorable communication environment can be established via controllable intelligent signal reflection, which facilitates the covert communication between a multi-antenna transmitter (Alice) and a legitimate full-duplex receiver (Bob) in the existence of a watchful warden (Willie). In order to shelter the desired communication, Bob generates jamming signals with a varying power to confuse Willie. The beamforming vector employed by Alice and the passive phase shifts of the IRS are optimized jointly to maximize the covert rate under the constraints of the successful detection probability at Willie and the communication outage experienced by Bob. We focus on the worst case by characterizing the minimum successful detection probability at Willie. The formulated problem is non-convex, due to the coupling between the beamforming vector of Alice and the phase shifts of the IRS, and the unit modulus constraint on the phase shifts of the IRS. To tackle the above issues, we first employ the penalty dual decomposition (PDD) method to handle the coupling effect. After that, we apply the successive convex approximation (SCA) method to develop an iterative algorithm for locating a Karush-Kuhn-Tucker (KKT) solution of the joint design problem. Moreover, we show that our proposed iterative algorithm can be adapted to handle the multi-antenna Willie case. Simulation results validate the effectiveness of the proposed iterative algorithm and show the great potential brought by the IRS for covert communications.

With the advantages of low cost and flexible deployment, low earth orbit satellite (LEO-Sat) communications have received widespread attentions, such as providing global wireless access with enhanced data rates in future 6G networks. However, due to the feature of high-mobility, LEO-Sat communications are facing severe Doppler effects, which heavily degrades the link reliability. The existing approaches for coping with Doppler effects, such as phase locked loop, mainly carry out the prediction and compensation for Doppler frequency shifts, which demands high implementation complexity, as well as accurate channel estimation. Against this background, this article portrays a new paradigm of reliable LEO-Sat communications with the aid of orthogonal time frequency space (OTFS) modulation scheme, which can average out the channel dynamics through modulating information in the delay-Doppler (DD) domain, thereby overcoming severe Doppler effects. In particular, we start with studying the Doppler effect characteristics of LEO-Sat communications, which serves as the motivations of using OTFS. Then, we conceive a case study to show the feasibility of OTFS enabled LEO-Sat communication by evaluating the reliability performance. Finally, we discuss a range of promising research opportunities and potential challenges.

This paper investigates the selection of a subset of sensors for time difference of arrival (TDOA) localization under the non-line-of-sight (NLOS) condition in wireless sensor networks (WSN). Specifically, we aim to optimize the sensor activation for the sake of minimizing the localization error in WSN when considering NLOS condition subject to energy constraints. In contrast to the existing sensor selection strategies, two independent Boolean selection vectors are utilized to determine the reference sensor and the other sensors simultaneously in TDOA localization. Upon presenting the expressions of the Cramer-Rao lower bound (CRLB) under three different scenarios, including: 1) line-of-sight (LOS), 2) Prior statistics unknown NLOS (PSU-NLOS), 3) Prior statistics known NLOS (PSK-NLOS), the optimization problems for sensor selection are formulated to minimize the CRLB based on two independent Boolean selection vectors. Analytical scheme is developed by solving the tractable semidefinite program (SDP) problems which are converted from the original nonconvex problem. Furthermore, two low-complexity heuristic algorithms, namely best option filling (BOF) and iterative swapping greedy (ISG), are proposed for the sake of practical implementation. Simulation results validate that the localization accuracy for sensors selected by the SDP with randomization algorithm and ISG algorithm achieves the exhaustive search method. Additionally, these two algorithms are stable under several random sensor network geometries.

As an important technique of enabling global access for 6G, low earth orbit satellite (LEO-Sat) communication is still facing the challenges of large path-loss, and severe Doppler effect. This paper studies the reliability performance of a downlink LEO-Sat communication system, where the orthogonal time frequency space (OTFS) scheme is employed to combat severe Doppler effect. Further, the unmanned aerial vehicle (UAV) based cooperative transmission is developed, in order to compensate for the large margin of path-loss caused by the long transmission distance. In particular, the closed-form expression for the outage probability of the OTFS based LEO-Sat transmission is derived, where the novel moment matching approach is used to closely approximate the PDF of a sum of shadowing Rician (SR) variables. Further, the condition of using UAV cooperation is obtained so that the positive reliability gain is guaranteed. Finally, both the theoretical analysis and simulation results show that, the OTFS scheme can significantly outperform the traditional OFDM scheme, while demanding to carefully address the trade-off between reliability improvement and implementation complexity determined by modulation size.