| 引用本文: | 刘海滨,王梓斌,郑林华,等.基于贝叶斯原理的放大转发中继联合信道估计.[J].国防科技大学学报,2014,36(1):88-92.[点击复制] |
| LIU Haibin,WANG Zibin,ZHENG Linhua,et al.Cascade channel estimators of amplify-and-forward relaying system based on Bayesian theory [J].Journal of National University of Defense Technology,2014,36(1):88-92[点击复制] |
|
| |
|
|
| 本文已被：浏览 8487次 下载 7071次 |
| 基于贝叶斯原理的放大转发中继联合信道估计 |
| 刘海滨1, 王梓斌2, 郑林华1, 袁福1 |
|
(1.国防科技大学 电子科学与工程学院， 湖南 长沙 410073;2.北京系统工程研究所 信息系统安全技术国防重点实验室， 北京 100101)
|
| 摘要: |
| 在贝叶斯原理的框架下，依据放大转发中继联合信道等价于两段瑞利信道相叠加的特征，将其概率密度分布这一先验知识与接收端的训练序列相结合，得到了最小均方和最大后验两种估计方法。由于两种方法的准确贝叶斯CRB难以求解获得闭合表达式，从最大熵原理出发，结合复高斯分布性质，推导了MLE准则下的CRB相对应的近似贝叶斯CRB，以衡量不同方法的估计精度。仿真结果表明相比于原有的MLE方法，最大后验估计方法在低信噪比下性能改善明显。 |
| 关键词: 放大转发 联合信道估计 贝叶斯原理 |
| DOI：10.11887/j.cn.201401016 |
| 投稿日期：2013-04-28 |
| 基金项目: |
|
| Cascade channel estimators of amplify-and-forward relaying system based on Bayesian theory |
| LIU Haibin1, WANG Zibin2, ZHENG Linhua1, YUAN Fu1 |
|
(1. College of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China;2. Science and Technology on Information System Security Laboratory, Beijing Institute of System Engineering, Beijing 100101, China)
|
| Abstract: |
| The cascade channel estimation of Amplify-and-Forward (AF) relay system was dealt with by using Bayesian framework. According to the maximum a posteriori (MAP) and the minimum mean of square error (MMSE) rules, two estimators were derived combining the received training signal with the probability distribution function (PDF) knowledge that cascade channel comprises two independent Rayleigh channels. Due to the intractability of exact Bayesian Cramer-Rao Bound (CRB), alternatively, the approximated Bayesian one was obtained based on the principle of maximum entropy to compare with the CRB of MLE. The numeral simulation demonstrates that the new MAP estimator can bring about significantly improved performance, especially in the low signal-to-noise ratio regime. |
| Keywords: amplify-and-forward cascade channel estimation Bayesian theory |
|
|
|
|
|
