基于压缩感知的非线性OFDM系统迭代信道估计算法

针对因非线性失真引起的正交频分复用（orthogonal frequency division multiplexing，OFDM）系统信道估计性能下降的问题，提出了一种基于压缩感知的非线性OFDM系统迭代信道估计算法。在算法实现过程中，利用信道与非线性噪声的双重稀疏性，将导频信息作为观测矩阵进行压缩感知信道估计，再将所得信道信息看作观测矩阵进行压缩感知非线性失真估计，进而对信号进行非线性补偿，并逐步循环迭代至算法收敛。仿真表明，在稀疏信道下，该算法在较少的迭代次数下即可有效减小非线性失真对信道估计的影响，且比现有方法性能更优，仿真证明了该方法在性能上的优越性。

Iterative channel estimation based on compressed sensing for nonlinearly distorted OFDM systems

An iterative channel estimation algorithm based on compressed sensing is proposed to improve the performance of channel estimation in orthogonal frequency division multiplexing(OFDM)systems caused by nonlinearly distortion.By u-sing the dual-sparsity of channel and nonlinear distortion,compressed sensing based channel estimation is firstly implemen-ted by considering the pilots as the observation matrix,and compressed sensing based nonlinear distortion estimation is then implemented by considering the estimated channel information as the observation matrix.After compensating the nonlinear distortion of the signal,the whole process repeats for iterative operation.Simulation shows that the proposed algorithm can effectively reduce the impact of nonlinear distortion on channel estimation and it has a better performance than the existing methods in sparse channels.It demonstrates that this algorithm has superior performance.