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Different with the passive wireless eavesdropping technique in traditional wireless communications, this paper studied proactive eavesdropping technology at the physical layer for legitimate eavesdropper to monitor the communication between suspicious users. It equipped consider a multiple-input single-output(MISO) system model where the suspicious transmitter and legitimate jammer with multi antennas, and equipped the suspicious receiver and legitimate eavesdropper with single antenna, if the channel gain of the suspicious communication link was stronger than that of the eavesdropping link, the legitimate jammer controled the communication rate of the suspicious users via jamming them, in order for the legitimate eavesdropper to correctly decode the eavesdropped information. Considering two cases that the jammer could or couldn’t interference on the legitimate eavesdropper, respectively, it designed the optimal interference signal and power control for the legitimate jammer to maximize the eavesdropping rate. Simulation results show that the proposed interference design method for the jammer in different application scenarios has better eavesdropping performance than the existing two benchmark methods. [ABSTRACT FROM AUTHOR]

In new wireless network scenarios, such as the future Internet of Things, it is necessary to transmit information and energy simultaneously, and the communication environment is complex and variable, with high maintenance costs for communication equipment. On the one hand, IRS can improve the performance of wireless communication and wireless power transfer by intelligent adjustment of the wireless channel. On the other hand, providing power supply to IRS by wireless power transfer can solve the problem of inconvenient power supply of IRS and reduce the maintenance costs. This paper investigated the throughput optimization of a dual wireless powered IRS-assisted wireless communication system, in which the multi-antenna base station (BS) first transmitted energy to two IRS, and then transmitted information to multiple single-antenna users with the help of the IRS. For the cases without and with channel blocking between the BS and the IRS, this paper proposed two-phase and three-phase transmission modes, respectively. It maximized the throughputs of these modes by optimizing the transmit beamforming of the BS, the reflect beamforming of the IRS, and the time allocation of different phases, subject to the constraints of the maximum transmit power of the BS, the minimum rate of the users, the duration of each phase, and the unit-module reflection coefficients of the IRS. Since the resulting optimization problems were convex and the optimization variables were highly coupled, it was difficult to find their optimal solution directly. This paper proposed two optimization algorithms based on the alternating optimization, successive convex approximation, and semi-definite relaxation techniques to obtain high-quality sub-optimal solutions. Simulation results show that the proposed algorithms achieve significantly better throughput performance compared to some benchmark algorithms and demonstrate the suitable application scenarios of the two-phase and three-phase transmission modes. [ABSTRACT FROM AUTHOR]

This paper considers the physical-layer security of information transmission in an unmanned aerial vehicle (UAV) multi-user communication system, where a UAV communicates with multiple users on the ground, with the presence of an eavesdropper on the ground trying to intercept the confidential information sent from the UAV to the users. The channels between the UAV and all ground nodes are modeled as more accurate probabilistic LoS (line-of-sight) channels. This paper studies maximizing the minimum average secrecy rate of all users by jointly designing the three-dimensional (3D) trajectory of the UAV and the user scheduling, under the constraints of UAV fight conditions and the discrete user scheduling parameters. To solve the optimization design problem for the UAV secure communication system under the probabilistic LoS channel model, it first decoupled it into three sub-problem, then solved the three sub-problems one by one, by using the integer relaxation and successive convex approximation methods, and finally obtained the 3D flight trajectory of UAV by using the block coordinate descent method. Based on the instantaneous channel state information obtained during the UAV’s flight, it further proposed a real-time optimization algorithm for UAV speed and user scheduling. This algorithm formulated the optimization problem into a linear programming problem and solved it by using the interior point method. Simulation results show that compared to the existing benchmark algorithms, the trajectory optimization of UAV based on the probabilistic LoS channel model can significantly improve the secrecy rate of the system, and the proposed real-time optimization algorithm for speed and user scheduling can further improve the secrecy rate performance. [ABSTRACT FROM AUTHOR]

This paper considered a wireless communication network with multiple UAV base stations and multiple users.In the network,due to the limited spectrum resource,the backhaul links of the UAV base stations and the data links of the users shared the same spectrum.In order to use the spectrum resource efficiently and improve the communication performance of the users,this paper jointly optimized the bandwidth and power of the backhaul and data links as well as the flight trajectory of the UAV base stations,to maximize the minimum average rate of all users.This joint optimization was subject to the UAVs’ mobility,the total spectrum bandwidth,and the total transmit power,and the involved joint optimization problem was non-convex,thus it was difficult to find the optimal solution.This paper proposed an efficient algorithm to obtain a high-quality suboptimal solution of it.Simulation results show that the minimum user rate achieved by the proposed joint optimization algorithm is significantly higher than that of the benchmark schemes. [ABSTRACT FROM AUTHOR]

New wireless communication scenarios such as automated factories have stringent reliability and low latency requirements. In such wireless networks, the joint application of the intelligent reflecting surface (IRS), non-orthogonal multiple access (NOMA), and ultra-reliable and low-latency communication (URLLC) techniques has the potential to provide lower communication latency, higher reliability, and higher throughput performance, as compared to traditional wireless communication techniques. In a multi-IRS-assisted NOMA URLLC system where multiple users are divided into various clusters, it considers the problems of how to pair user clusters and IRSs and how to optimize the communication resource allocation. Specifically, it jointly investigates the user transmit power allocation, IRS reflection beamforming, and user-cluster-IRS pairing decision problems to maximize the sum of user throughputs. To solve the resulting non-convex optimization problem, it proposes an alternating iteration-based algorithm, which solves the three subproblems of power allocation optimization, IRS reflection beamforming optimization, and user cluster IRS pairing decision optimization alternately until achieving convergence by appropriately introducing slack variables and by using the semidefinite relaxation technique. Simulation results show that the proposed algorithm can significantly improve the system’s throughput and verify the necessity and effectiveness of user cluster-IRS pairing decision optimization. [ABSTRACT FROM AUTHOR]

SWIPT can effectively deal with the energy limitation problem of communication terminals, and IRS can assist in enhancing the efficiency of SWIPT. Therefore, to overcome the shortcoming of limited coverage of deploying a single IRS and further improve the time and spectrum resource utilization efficiency of SWIPT, this paper studied a double-IRS-assisted NOMA SWIPT system, where the beamforming vector of the transmitter, the phase shifts of each IRS, and the power splitting coefficients of the receivers were jointly optimized to maximize the minimum user rate. To solve the above non-convex optimization problem with highly coupled variables, this paper proposed an AO algorithm based on SDR and SCA techniques to solve it efficiently. The simulation results show that the double-IRS-assisted system can achieve a higher minimum rate than that of its single-IRS, which reveals the superiority of deploying double IRS, the effectiveness of the proposed algorithm, and the importance of jointly optimizing IRS phase shifts and power splitting coefficients in improving the user rate performance. [ABSTRACT FROM AUTHOR]

This paper proposed an iterative algorithm for resource allocations in OFDM relay systems, whose convergence had been proved. It executed the simplified algorithm in three ordered steps: subchannel assignment, transmission strategy selection and transmit power allocation at the relay, and transmit power allocation at the source. Simulation results show that both the iterative and simplified algorithms outperform the two existing resource allocation schemes. The simplified one is more suitable for practical applications. [ABSTRACT FROM AUTHOR]