基于压缩感知的OFDM稀疏信道估计导频优化算法

研究了在正交频分复用（OFDM）系统中基于压缩感知信道估计的导频图案设计问题.为了优化信道估计的性能，提出了优化算法，在基于压缩感知的测量矩阵互相关最小化准则的基础上，通过增大随机生成数进行分组，分别计算每组的互相关值，再进行比较求互相关的最大值从而获得导频图案.仿真结果表明，与使用基于测量矩阵互相关最小化准则的导频图案相比，该优化算法得到的信道估计的最小均方误差要低30%. 

Optimized Pilot Placement for Compressive Sensing Based on Sparse Channel Estimation in OFDM Systems

The pilot pattern problem for sparse channel estimation in orthogonal frequency division multiplexing (OFDM) systems has been examined. To optimize the performance of sparse channel estimation, an optimized algorithm was proposed. The algorithm was based on minimizing mutual coherence of the measurement matrix in CS theory, to group with increasing the generated random number. The mutual coherence value of each group was calculated, and compared to get the maximum mutual coherence value, consequently to optimize the pilot pattern. Simulation results demonstrate that the pilot pattern obtained using the proposed algorithm can get 30%lower mean square error(MSE)compared with the original pilot pattern.