Joint maximum likelihood and Bayesian channel estimation
联合最大似然贝叶斯信道估计

Statistical Bayesian channel estimation is effective in suppressing noise floor for high SNR, but its performance degrades due to less reliable noise estimation in low SNR region. Based on a robust nonlinear de-noising technique for small signal, a simplified joint maximum likelihood and Bayesian channel estimation is proposed and investigated. Simulation results are presented and analysis shows it is promising to improve channel estimation and joint detection performance for both low and high SNR situations.