基于遗传算法的短波OFDM信道估计导频优化方案

短波信道具有时域稀疏性,压缩感知理论应用于短波OFDM信道估计可以改善估计性能以及减少导频开销。然而信道估计性能和信道的可恢复性都与导频的放置有着密切关系,为了进一步提高信道重构精度,本文以最小化测量矩阵的互相关为导频优化目标,提出一种基于遗传算法的导频优化方案,并设计了相应的交叉算子和变异算子,以产生新个体,保证种群的多样性。仿真结果表明,相比随机搜索,该方案可以得到更小的互相关值,更高的重构精度以及更高的频带利用率。

Genetic algorithms based optimization scheme of pilot pattern for HF channel estimation in OFDM system

Short wave (HF) channel is a kind of time domain sparse channels, the application of the recent theory of Compressed Sensing has proved its efficiency to both ameliorate the estimation accuracy and reduce the transmitted overhead. The performance and uniqueness guarantee of recovery remain however closely related to the pilots placement. In order to further enhance the performance of the estimation, this letter investigates the deterministic design of pilot pattern based on minimizing the coherence of the measurement matrix then it proposes a pilot design scheme based on Genetic Algorithms and designs a suitable crossover operator and mutation operator to generate new individuals. Simulation results show that compared with the random search, the proposed scheme can get a smaller cross-correlation value, higher reconstruction accuracy and higher spectral efficiency.