基于联合稀疏模型的OFDM压缩感知信道估计

针对正交频分多路复用（OFDM）系统，比较了基于压缩感知的不同导频设计方案及相应信道估计性能. 基于信道响应的时域稀疏和缓变特征，提出了基于联合稀疏模型的压缩感知信道估计方法，进一步提高了信道估计的性能. 该方法将连续若干个OFDM符号的信道估计问题转化为联合稀疏模型下的压缩感知问题，充分利用信道的稀疏特性和时间相关性进行信道估计. 结合短波OFDM系统，比较了几种信道估计方法的性能. 仿真结果表明，与传统的最小平方误差信道估计方法和逐符号的压缩感知信道估计方法相比，基于联合稀疏特征的信道估计方法可进一步改善估计性能，对时变信道具有更好的适应性.

Joint Sparse Model Based OFDM Compressed Sensing Channel Estimation

Pilot design schemes and their corresponding channel estimation methods for orthogonal frequency division multiplexing(OFDM)system based on compressed sensing theory are studied. With the channel sparse impulse response and slow varying character, a joint sparse model (JSM) for the channel estimation in OFDM system is proposed. With such joint sparse model, the channel estimations of continuous OFDM symbol periods are converted into a sparse vectors recovery problem with joint sparse model, which improves the estimation performance. Different channel estimation methods for shortwave OFDM system are compared. Simulation shows that the proposed compressed sensing based channel estimation scheme brings out better performance compared with conventional least square channel estimation method and symbol-by-symbol compressed sensing channel estimation method. Simulation also shows that the proposed method has better estimation performance under time-variant channel.