Aiming at the impulsive noise occurring in OFDM systems, an impulsive noise mitigation algorithm based on compressed sensing theory was proposed. The proposed algorithm firstly treated the channel impulse response and the impulsive noise as a joint sparse vector by exploiting the sparsity of both them. Then the sparse Bayesian learning framework was adopted to jointly estimate the channel impulse response, the impulsive noise and the data symbols, in which the data symbols were regarded as unknown parameters. Compared with the existing impulsive noise mitigation methods, the proposed algorithm not only utilized all subcarriers but also did not use any a priori information of the channel and impulsive noise. The simulation results show that the proposed algorithm achieves significant improvement on the channel estimation and bit error rate performance.%针对 OFDM 系统中的脉冲噪声问题,提出一种基于压缩感知技术的脉冲噪声抑制方法.该方法将信道脉冲响应和脉冲噪声联合视作一个稀疏向量,将发射数据符号视作未知参数,利用稀疏贝叶斯学习理论联合估计信道、脉冲噪声和数据符号.与现有脉冲噪声抑制方法相比,该方法不仅能够充分利用全部子载波信息,而且不需要信道和脉冲噪声的先验统计信息.仿真结果表明,所提方法在信道估计及误比特率性能上有明显改善.
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