IRS辅助的认知反向散射通信网络性能增强方案

Performance enhancement scheme for IRS-assisted cognitive backscatter communication network

为解决认知无线电网络(CRN)的可持续供电问题和改善其通信效率,面向Overlay场景,提出了智能反射面(IRS)辅助的高效多模式融合传输方案。特别地,次发射机(ST)可以在反向散射通信(BackCom)和收集再传输(HTT)模式间切换,IRS被用以提升ST的能量采集、信息被动反射和信息主动传输效率。为了最大化系统和速率,定义了关于IRS相移、时隙调度和发射功率的联合优化问题。由于所定义的问题是非凸的,因此通过设计基于块坐标下降(BCD)的迭代优化算法获得了次优解。仿真结果表明,相较于参照方案,所提方案最多可将系统和速率提高200%。

In order to achieve the self-sustainable cognitive radio network(CRN)and improve its communication efficiency,an efficient multi-mode switching scheme assisted by the intelligent reflecting surface(IRS)for the overlay scenario was proposed.In particular,the secondary transmitter(ST)could work in either backscatter communication(Back-Com)mode or harvest-then-transmit(HTT)mode.The IRS was exploited to enhance the energy harvesting,information backscattering,and information transmission efficiencies at the ST.To maximize the system sum-rate,an optimization problem about the phase shirts at the IRS,time scheduling,and power allocation was formulated.Since the formulated problem was non-convex,an efficient block coordinate descent(BCD)based algorithm was proposed to achieve the sub-optimal solution.Simulation results confirm that the proposed scheme can achieve up to 200%sum-rate gain over the benchmark schemes.