OFDM系统中基于压缩感知恢复由限幅和HPA产生的非线性失真研究

Research on Recovery of Clipping and HPA Nonlinear Distortion Based on Compressive Sensing in OFDM Systems

正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)系统的主要缺点之一就是有较高的峰均功率比(Peak to Average Power Ratio,PAPR),降低了功率放大器(High Power Amplifier,HPA)的工作效率,同时HPA引入的非线性失真,恶化了系统的误比特率(Bite Error Rate,BER)性能.本文所提算法将限幅和HPA引入的非线性失真视为一个整体来考虑,利用与限幅噪声在时域上的近似稀疏性,对整个非线性过程进行建模.发送端通过限幅降低了OFDM信号的PAPR,在接收端,选取受噪声干扰小的可靠性观测向量,最小化信道噪声的影响,基于非线性模型计算得到的参数,利用压缩感知(Compressive Sensing,CS)算法能有效地恢复总的非线性失真信号,提升了系统的BER性能.

One of the main drawbacks in orthogonal frequency division multiplexing （OFDM） systems is high peak to average power ratio （PAPR） which reduces the efficiency of high power amplifier （HPA）,and the nonlinear distortion caused by HPA will degrade the bite error rate （BER） of the system.The proposed scheme of this paper considers the nonlinear distortion caused by clipping and HPA as a whole,and models the whole nonlinear process utilizing the sparsity in time domain similar to the clipping noise.The PAPR of OFDM signal is reduced by clipping at the transmitter,and for the receiver,reliable observations contaminated by less channel noise are selected to minimize the influence of channel noise,and compressive sensing （CS） algorithm is applied to effectively recover the total nonlinear distortion signal with the parameters calculated from the nonlinear model,which can improve the BER performance of the system.