基于二进制粒子群算法的OFDM稀疏信道导频优化

Pilot design based on binary particle swarm optimization in the OFDM sparse channel

在正交频分复用(orthogonal frequency division multiplexing,OFDM)稀疏信道中,合理的导频设计可以提高信道估计的性能,以测量矩阵的互相关最小化作为目标,提出一种基于二进制粒子群算法的导频优化方案,引入混沌初始化机制来保证初始粒子均匀地分散在解空间里,通过粒子变异机制来保证种群的快速收敛。根据实验和仿真结果可以看出,与随机搜索导频优化算法、逐位置导频优化算法以及最小二乘法相比,该算法能够有效节省导频的开销,提高频谱利用率,具有更好的信道估计性能。

The reasonable pilot design can improve the performance of the channel estimation in the OFDM sparse channel. With the objective to minimize the cross correlation of the measurement matrix, this paper proposed a pilot optimization al-gorithm based on the binary particle swarm optimization algorithm. In addition, the chaos initialization is to ensure that the initial particles are evenly dispersed in the solution space. The particle mutation mechanism is to ensure the rapid conver-gence of the population. Simulation results show that compared with the random pilot design algorithm, the bitwise pilot de-sign algorithm and the least squares algorithm, the proposed algorithm can effectively save the pilot overhead, improve the spectrum efficiency and provide a better channel estimation performance.