改进的压缩感知限幅噪声消除方案

Improved clipping noise elimination scheme for compressed sensing

限幅引入非线性失真即限幅噪声,使正交频分复用系统误码率性能显著下降。为消除限幅噪声,本文提出了基于预估计限幅噪声位置的稀疏自适应匹配追踪方案。首先,在发送端信号送入信道之前,根据信号幅度值,预先估计被限幅采样点的位置,使落在该采样点范围的限幅噪声作为压缩感知的观测值向量,其次再对噪声进行重构。该预估计方案成功避免了信道对限幅噪声分布位置及幅值的干扰,提高了重构精度。仿真结果表明,与传统压缩感知算法相比,所提方案对系统的误码率性能及算法计算复杂度均有改善。

The introduction of nonlinear distortion,also known as clipping noise,makes the bit error rate of OFDM system significantly lower.In order to eliminate the clipping noise,a sparse adaptive matching tracking scheme based on advance estimation of the clipping noise position is proposed.Before the signal is sent to the channel,the position of the clipped sampling point is estimated in advance according to the amplitude value of the signal,so that the clipped noise falling in the range of the sampling point is taken as the observation value vector of the compressed perception.Then the noise is reconstructed.The advance estimation scheme can avoid the interference of channel to the location and amplitude of the noise and improve the reconstruction accuracy.The simulation results show that compared with the traditional compressed sensing algorithm,the scheme proposed in this paper improves the bit error rate of the system and the computational complexity of the algorithm.