基于贝叶斯压缩感知的正交频分复用信道估计改进

OFDM channel estimation algorithm based on improved Bayesian compressive sensing

为了获得理想的正交频分复用信道估计结果,针对传统算法没有充分利用无线信道时域的固有稀疏性,导致估计精度不高且频谱利用率低等难题,提出了改进贝叶斯算法感知的正交频分复用信道估计算法。首先在详细介绍本文算法的原理和步骤基础上,与传统信道估计算法进行仿真对比实验。仿真结果表明,相对于其它信道估计算法,本算法可获得更高的信道估计精度,在使用较少导频的条件下获得很好的信道估计性能。

In order to obtain good channel estimation results of orthogonal frequency division multiplexing, and the traditional channel estimation methods did not make full use of the channel sparsity which leads to low precision estimation and low frequency spectrum utilization, a novel channel estimation algorithm of orthogonal frequency division muhiplexing is proposed based on im- proved Bayesian compressive sensing. Firstly, the principle and steps of the proposed algorithm are introduced in detail, and then the simulation experiments are carried out in order to test the performance of the algorithm. The results show that compared with other channel estimation algorithm, the proposed algorithm can improve the channel estimation precision and has good performance but with less pilots.