RIS辅助的通感性能联合优化研究OA

Integrated sensing and communication(ISAC)is one of the major 6G scenarios.In order to solve the problem of reduced performances of communication and sensing in an area under non-line-of-sight transmission due to obstacles,a joint optimization approach is proposed for the reconfigurable intelligent surface(RIS)-assisted ISAC performance.Firstly,the area performance joint optimization problem is formulated to minimize squared position error bound(SPEB)and maximize the average coverage signal strength.Then an improved dung beetle optimizer(DBO)algorithm is proposed to quickly obtain the deployment position and phase parameters of RISs.Furthermore,the impacts of detection demand factor and RIS size on the area ISAC performance are analyzed.The simulation results show that compared with merely optimizing desired angle of reflection of RIS,jointly optimizing its deployment location and the desired angle of reflection can reduce the regional average SPEB by about 80%.Meanwhile,the improved DBO algorithm has a faster convergence speed and a better fitness compared with traditional optimization algorithms such as particle swarm optimization,sparrow search algorithm and the original DBO algorithm.