基于压缩感知和虚警概率的电力线脉冲噪声抑制方法

针对OFDM电力线通信中噪声抑制方法依赖于脉冲噪声特征参数及脉冲噪声稀疏度的问题,提出一种基于压缩感知和虚警概率的宽带电力线脉冲噪声抑制算法.该算法利用OFDM零子载波观测脉冲噪声投影,采用基追踪降噪方法对脉冲噪声进行粗估计,并设计基于虚警概率的自适应脉冲噪声检测门限,根据门限得到粗估计的脉冲噪声支撑集,在支撑集上通过最小二乘方法对脉冲噪声幅度进行重构,接收信号减去估计的脉冲噪声可得到去噪的OFDM信号.仿真结果表明,提出的算法在未知脉冲噪声稀疏度的情况下可以对噪声信号进行重构,算法的性能优于传统压缩感知及非线性去噪方法,能可靠有效的对宽带电力线脉冲噪声进行抑制.

Impulse Noise Mitigation Method Based on Compressive Sensing and False-alarm Probability in Power Line Communication

In terms of the problem that the suppression of impulse noise (IN) in orthogonal frequency division multiplexing (OFDM) based power line communication depends on the characteristic parameters and sparsity of IN, this paper proposed a suppression algorithm based on compressive sensing (CS) and False-Alarm probability. In this approach, the projection of IN is observed using OFDM zero carriers, and the rough estimation of IN is carried out by using the method of base pursuit denoise (BPDN). Then, an adaptive impulse noise detection threshold based on false alarm probability is designed, and the support set of IN is obtained according to the designed threshold. Finally, the IN in power line communication is reconstructed by the least square method. The original OFDM signal can be derived by subtracting the estimated IN from the received OFDM signal. The simulation results show that the proposed algorithm can reconstruct the IN well even if the sparsity conditions of IN is unknown, the performance of the algorithm is superior to the traditional compressed sensing and the nonlinear denoising methods, and this algorithm is reliable and effective for mitigating IN in broadband power line communication.