联合最大似然贝叶斯信道估计(英文)

Joint maximum likelihood and Bayesian channel estimation

在高信噪比情况下统计贝叶斯估计是一种有效的信道估计方法,但是在低信噪比时由于噪声估计不准确,其性能逐渐下降。研究了基于鲁棒的非线性降噪方法,提出了一个简化的联合最大似然贝叶斯信道估计。计算机仿真结果和分析表明这种方法在较高和较低的信噪比情况下,提高了信道估计和联合检测的性能。

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 resuits are presented and analysis shows it is promising to improve channel estimation and joint detection performance for both low and high SNR situations.