This paper investigates a downlink millimeter-Wave(mmWave)communication system equipped with multiple cooperative Intelligent Reflecting Surfaces(IRSs),aiming to extend mmWave signal coverage and maximize system throu...This paper investigates a downlink millimeter-Wave(mmWave)communication system equipped with multiple cooperative Intelligent Reflecting Surfaces(IRSs),aiming to extend mmWave signal coverage and maximize system throughput.To fully exploit the potential of IRSs within a user-centric framework,this study delves into the joint optimization problem of user multiple association,transmit beamforming,and cooperative passive beamforming.Meanwhile,the impact of IRS locations on user association is analyzed.Given the non-convexity and complexity of the joint optimization problem,a low-complexity optimization algorithm is designed.The algorithm integrates iterative optimization,Lagrangian dual decomposition,and Fractional Programming(FP)techniques.Specifically,the user association problem is optimized using the Lagrangian dual decomposition method,while the joint beamforming is solved via the FP method.Simulation results demonstrate that,compared to traditional methods,the proposed algorithm significantly improves the system sum rate,validating its effectiveness and superiority.展开更多
基金supported in part by the National Natural Science Foundation of China(U23A20279,62561008)in part by the Natural Science Foundation of Chongqing under Grant CSTB2024NSCQMSX0535+1 种基金in part by the Science and Technology Development Fund(001/2024/SKL)the State Key Laboratory of Internet of Things for Smart City(University of Macao)Open Research Project(Ref.No.:SKL-Io TSC(UM)/ORP03/2026)。
摘要This paper investigates a downlink millimeter-Wave(mmWave)communication system equipped with multiple cooperative Intelligent Reflecting Surfaces(IRSs),aiming to extend mmWave signal coverage and maximize system throughput.To fully exploit the potential of IRSs within a user-centric framework,this study delves into the joint optimization problem of user multiple association,transmit beamforming,and cooperative passive beamforming.Meanwhile,the impact of IRS locations on user association is analyzed.Given the non-convexity and complexity of the joint optimization problem,a low-complexity optimization algorithm is designed.The algorithm integrates iterative optimization,Lagrangian dual decomposition,and Fractional Programming(FP)techniques.Specifically,the user association problem is optimized using the Lagrangian dual decomposition method,while the joint beamforming is solved via the FP method.Simulation results demonstrate that,compared to traditional methods,the proposed algorithm significantly improves the system sum rate,validating its effectiveness and superiority.