In this paper, a hybrid IRS-aided amplify-and-forward (AF) relay wireless network is put forward, where the hybrid IRS is made up of passive and active elements. For maximum signal-to-noise ratio (SNR), a low-complexity method based on successive convex approximation and fractional programming (LC-SCA-FP) is proposed to jointly optimize the beamforming matrix at AF relay and the reflecting coefficient matrices at IRS. Simulation results verify that the rate achieved by the proposed LC-SCA-FP method surpass those of the benchmark schemes, namely the passive IRS-aided AF relay and only AF relay network.

翻译：本文提出了一种混合智能反射面辅助的放大转发（AF）中继无线网络，其中混合智能反射面由无源和有源元件组成。为最大化信噪比（SNR），提出了一种基于逐次凸逼近与分数规划的低复杂度方法（LC-SCA-FP），用于联合优化AF中继处的波束成形矩阵以及智能反射面处的反射系数矩阵。仿真结果表明，所提出的LC-SCA-FP方法实现的速率超过了基准方案（即无源智能反射面辅助的AF中继网络与仅AF中继网络）的速率。