降低多用户大规模MIMO-OFDM系统PAPR的加速近端梯度算法

针对多用户大规模多输入多输出（Multiple-Input Multiple-Output，MIMO）正交频分复用（Orthogonal Frequency Division Multiplexing，OFDM）系统存在较高峰值平均功率比（Peak-to-Average Power Ratio，PAPR）问题，在系统的下行链路中利用基站大量天线提供的冗余自由度，将OFDM调制、消除多用户之间干扰及降低PAPR联合成凸优化问题，并设计加速近端梯度算法（Accelerated Proximal Gradient Method，APGM）求解上述优化问题。仿真结果表明，所提方法显著降低了发射信号的峰均比，同时获得了较好的系统误符号率。与其他相关方法对比，APGM具有更低的计算复杂度和更快的收敛速度。

Accelerated proximal gradient method for reducing PAPR of multi-user massive MIMO-OFDM systems

To solve the high peak-to-average power ratio (PAPR) in orthogonal frequency division multiplexing-based multi-user massive multiple-input multiple-output (MIMO-OFDM) downlink systems,by using the redundant degree of freedom provided by many antennas equipped at a base station,OFDM modulation,multi-user interference elimination and PAPR reduction are combined into a joint convex optimization problem.An Accelerated Proximal Gradient Method (APGM) is designed to address the convex optimization.Simulation results show that the proposed method can significantly reduce the PAPR of the transmitted signal,and obtain a better system symbol error rate.Compared with other methods,APGM has lower complexity and faster convergence.