Sparse Channel Estimation Based on Improved BP-MF Algorithm in SC-FDE System
Chao Wang, Zhiyuan Li, Lei Huang · 2017 International Conference on Computer Systems, Electronics and Control (ICCSEC) · 2017
A low complexity sparse Bayesian channel estimation algorithm was proposed for SC-FDE receiver. The proposed algorithm firstly applies the combined belief propagation and mean field (BP-MF) algorithm to the Bayesian Hierarchical Prior Model and obtained by approximating some BP messages using generalized approximate message passing (GAMP) algorithm. Then we put the channel estimated values that are acquired from the first iteration in such an order-from big to small and further reduce the computational complexity, we eliminate some small value to achieve this goal. Finally, we applied the MF method to the Frequency Domain Equalization. Numerical results demonstrate that the proposed method has nearly the same performance as compared to the MF algorithm in estimation precision of the channel and Bit Error Rate (BER) while it has much less computational complexity as compared to the MF algorithm.