张凯^1,,,
田瑶²,
谢云鹏¹,
刘翼¹
1.中国洛阳电子装备试验中心 ??洛阳 ??471000
2.96862部队 ??洛阳 ??471000
基金项目:国家自然科学基金(61501517)

详细信息

作者简介:张凯：男，1988年生，博士，研究方向为通信信号处理、信道估计
田瑶：女，1988年生，助理工程师，研究方向为无线通信
谢云鹏：男，1982年生，工程师，研究方向为通信对抗

通讯作者:张凯　 zk_xxgc@163.com

中图分类号:TN92; TN911.5

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文章访问数:1007
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被引次数:0

出版历程

收稿日期:2018-01-19
修回日期:2018-06-27
网络出版日期:2018-07-12
刊出日期:2018-09-01

Joint Symbol Detection Algorithm for Multi-antenna Signals over Flat-fading Channels Based on Variational Bayes

Kai ZHANG^1,,,
Yao TIAN²,
Yunpeng XIE¹,
Yi LIU¹
1. Luoyang Electronic Equipment Test Center of China, Luoyang 471000, China
2. 96862 Troops, Luoyang 471000, China
Funds:The National Natural Science Foundation of China (61501517)


摘要
摘要:该文针对平坦衰落信道下存在信道参数差异的多天线接收信号联合参数估计和符号检测问题，提出一种基于变分贝叶斯的联合处理算法。算法直接利用多个接收数据流进行信息符号的估计，抑制传统信号合成与解调解耦处理带来的性能损失。将问题建模为已知多组观测数据条件下发送符号、信道传输时延、信道增益和噪声功率的联合最大后验估计问题。基于变分贝叶斯理论对该最大后验进行近似求解，在相对熵最小化的准则下，推导得到了各个待估参数解析形式的近似后验分布——变分分布。所提算法无需计算各参数精确的点估计值，而是采用信道参数和信息符号变分分布迭代处理的方式进行联合求解。仿真结果表明，所提算法通过多信号、多参数的联合处理能够获得优于经典解耦处理和部分联合处理技术的系统误码率性能，且在接收天线数目较多和观测数据长度较短时性能优势体现更加明显。
关键词:多天线组阵/
平坦衰落/
联合处理/
变分贝叶斯
Abstract:For the issue of joint parameter estimation and symbol detection for multi-antenna signals with channel parameters difference over flat-fading channels, a new joint processing scheme is proposed based on the Variational Bayes (VB) method. The proposed scheme uses directly multiple received signals for the estimation of information symbols, restraining the information loss in conventional decoupled scheme of signals combination and demodulation. The problem is modeled as the joint Maximum A Posteriori (MAP) estimation of information symbols, time-delays, complex channel gains, and noise powers, given multiple observations, and approximately solved by means of VB approach. Based on the criterion of minimum relative entropy, analytical-form of the approximate distributions, i.e., variational distributions, for all unknown parameters are derived. There is no need to determine accurate point estimates of the parameters. Instead, the proposed scheme proceeds iteratively by alternating between the variational distributions of channel parameters and the information symbols. Simulation results show that the proposed joint processing scheme has significant performance improvements in comparison with conventional decoupled or partly joint processing schemes especially with large array sizes and short signal lengths.
Key words:Multi-antenna arraying/
Flat-fading/
Joint processing/
Variational Bayes



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