| AAF-MH协作方案下的PARAFAC盲信号检测方法 |
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| 引用本文： | 韩曦,袁超伟,胡紫巍. AAF-MH协作方案下的PARAFAC盲信号检测方法[J]. 北京邮电大学学报, 2013, 36(1): 82-85 |
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| 作者姓名： | 韩曦 袁超伟 胡紫巍 |
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| 作者单位： | 北京邮电大学 信息与通信工程学院, 北京 100876 |
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| 基金项目： | 国家自然科学基金项目(60872149) |
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| 摘 要： | 多跳Alamouti放大转发(AAF-MH)协作方案的译码通常需要获取信道状态信息(CSI),在实际系统中,CSI的获取比较困难.针对此问题,提出了一种基于平行因子(PARAFAC)的盲信号检测方法.该方法将接收信号构建为包含信道、信号信息的PARAFAC模型,并使用双线性最小二乘算法进行拟合,以保证结果的全局收敛性.与恒模方法相比,该方法的拟合结果具有稳定性,并能实现参数估计的唯一性,在检测性能方面更具优势.仿真结果验证了理论分析的正确性.
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| 关 键 词： | 平行因子 盲检测 多跳Alamouti放大转发 唯一性 |
| 收稿时间： | 2012-05-23 |
A PARAFAC Blind Signal Detection Algorithm for AAF-MH Cooperative Scheme |
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| HAN Xi,YUAN Chao-wei,HU Zi-wei. A PARAFAC Blind Signal Detection Algorithm for AAF-MH Cooperative Scheme[J]. Journal of Beijing University of Posts and Telecommunications, 2013, 36(1): 82-85 |
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| Authors: | HAN Xi YUAN Chao-wei HU Zi-wei |
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| Affiliation: | School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China |
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| Abstract: | The decoding of multi-hop Alamouti amplify and forward (AAF-MH) cooperation scheme usually needs channel state information, which is difficult to acquire in practical systems. To solve this problem, a parallel factor (PARAFAC)-based blind signal detection algorithm is proposed. This algorithm transforms received signals into a PARAFAC model which contains channel and signal information, and uses the bilinear alternating least square for the global convergence. Compared with constant modulus algorithm, the proposed algorithm is with better performance, such as more stable fitting results, and can realize uniqueness of parameter estimation. Simulation is given to support the analysis. |
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| Keywords: | parallel factor blind detection multi-hop Alamouti amplify and forward uniqueness |
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