Integrated sensing and communication(ISAC) systems can enhance security and reliability in full-duplex( FD) networks.This paper studies the resource allocation problem in FD networks based on ISAC.We formulate an opti...Integrated sensing and communication(ISAC) systems can enhance security and reliability in full-duplex( FD) networks.This paper studies the resource allocation problem in FD networks based on ISAC.We formulate an optimization problem that jointly considers beamforming,radar waveform,and reflection coefficient of a hybrid reconfigurable intelligent surface,aiming to maximize the beampattern gain of the concealed target while maintaining the quality of service of communication users.A two-stage algorithm is designed to solve this problem: the first stage optimizes the radar waveform and beamforming,and the second focuses on the reflection coefficient design.We acquire the feasible solution using semidefinite programming relaxation.The optimality of the feasible solution for radar waveform and beamforming subproblem is ensured through Cauchy-Schwartz inequality.For the reflection coefficient design,an approximate optimal solution is acquired through successive convex approximation.Numerical results demonstrate that the proposed algorithm can achieve a superior performance trade-off between communication and radar sensing compared to the benchmarks.展开更多
基金Supported by the National Science and Technology Major Project of China (No.C6-3416-M01)。
文摘Integrated sensing and communication(ISAC) systems can enhance security and reliability in full-duplex( FD) networks.This paper studies the resource allocation problem in FD networks based on ISAC.We formulate an optimization problem that jointly considers beamforming,radar waveform,and reflection coefficient of a hybrid reconfigurable intelligent surface,aiming to maximize the beampattern gain of the concealed target while maintaining the quality of service of communication users.A two-stage algorithm is designed to solve this problem: the first stage optimizes the radar waveform and beamforming,and the second focuses on the reflection coefficient design.We acquire the feasible solution using semidefinite programming relaxation.The optimality of the feasible solution for radar waveform and beamforming subproblem is ensured through Cauchy-Schwartz inequality.For the reflection coefficient design,an approximate optimal solution is acquired through successive convex approximation.Numerical results demonstrate that the proposed algorithm can achieve a superior performance trade-off between communication and radar sensing compared to the benchmarks.
