基于压缩感知的电力线脉冲噪声抑制

Impulse Noise Suppression in Power Line Communication Based on Compressed Sensing

为提高低压电力线正交频分复用(OFDM)通信系统的传输性能,提出了一种脉冲噪声抑制算法——优化先验辅助稀疏度自适应匹配追踪(OPA-SAMP)算法。该算法将频域获取的空子载波数据作为测量向量,根据信噪比的变化关系推导出粗估计门限,并将该门限估计的脉冲噪声先验支撑集初始化算法的残差与步长,然后采用稀疏度自适应匹配追踪(SAMP)迭代算法恢复出脉冲噪声,最后在接收端对恢复的脉冲噪声进行抑制。实验结果表明,该文提出的算法能有效去除电力线信道中的脉冲噪声,与传统的压缩感知算法相比,该算法具有更低的通信误码率,算法的运行时间更短。在脉冲噪声发生概率高、传输数据量大的情况下,该算法的性能更加优良。

To enhance the transmission performance of orthogonal frequency division multiplexing(OFDM)communication system over low-voltage power line,this paper proposed a kind of impulse noise suppression algorithm-optimized prior aided sparsity adaptive matching pursuit(OPA-SAMP).The algorithm used the data on empty sub-carriers in frequency domain as the measurement vector,deduced a rough estimate threshold based on the change of signal to noise ratio(SNR),and initialized the residual and step length by the priori support set of impulse noise which derived from the estimated threshold,then recovered the impulse noise by the sparse adaptive matching tracking(SAMP)iterative algorithm,finally,the impulse noise is suppressed at the receiving end.Experimental results show that the proposed algorithm has lower communication error rate and shorter running time compare with the traditional compressed sensing algorithm.What is more,the performance of the algorithm is better in case of high probability of impulse noise and large amount of transmission data.