基于压缩感知的放大转发双向中继信道估计

Channel estimation based on compressive sensing in two-way amplify-and-forward relay channel

为了更有效地对放大转发双向中继信道进行估计,对级联卷积信道的稀疏特性进行了分析,并基于其稀疏性,采用压缩感知技术,通过合理地设计导频将合成级联卷积信道分解成2个独立的级联卷积信道分别进行信道估计。研究分析和仿真结果表明,级联卷积信道具有稀疏性且其稀疏度在一定范围内变化。所提的方案只需在端节点对级联卷积信道进行估计就可以完成双向信息的交换,提高了频谱效率,降低了信道估计误差,并且无需信道稀疏度的先验信息。

The sparsity of concatenated convolutional channel in two-way amplify-and-forward relay was analyzed. Through the appropriate design of the pilot, the synthetic concatenated convolutional channels could be decomposed into two independent concatenated convolutional channels for channel estimation. Theoretical analysis and simulation results show that the concatenated convolutional channel possesses sparsity which varies within a range. The proposed scheme completes the two-way exchange of information by finishing concatenated convolutional channel estimation in end nodes Without the priori information of the channel sparsity, this scheme improves the utilization of spectrum resources and the performance of channel estimation.