| 支持向量机在WCDMA移动通信系统多用户检测中的应用 |
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| 引用本文： | 刘家彬,李文元. 支持向量机在WCDMA移动通信系统多用户检测中的应用[J]. 北京石油化工学院学报, 2010, 18(4): 18-21. DOI: 10.3969/j.issn.1008-2565.2010.04.005 |
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| 作者姓名： | 刘家彬 李文元 |
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| 作者单位： | 北京石油化工学院通信工程系,北京,102617;北京石油化工学院通信工程系,北京,102617 |
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| 摘 要： | 从结构风险最小化（SRM）理论发展而来的支持向量机（SVM）为模式识别提供了一种新的途径。将SVM应用于宽带码分多址（WCDMA）移动通信系统中的多用户检测（MUD）中。利用最小序列优化（SMO）算法构造基于非线性核的接收机,提出了一种适合于WCDMA系统的SVM-MUD。在同步的假设下,仿真比较了SVM-MUD和传统的去相关检测器、匹配滤波（MF）检测器和最小均方误差（MMSE）检测器的误比特（BER）性能。结果表明,在高斯信道下,SVM-MUD的性能更加稳定可靠。
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| 关 键 词： | 多用户检测 支持向量机 宽带码分多址 机器学习 移动通信 |
Application of Support Vector Machine for Multi-user Detection in WCDMA Mobile Communication Systems |
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| Liu Jiabin,Li Wenyuan. Application of Support Vector Machine for Multi-user Detection in WCDMA Mobile Communication Systems[J]. Journal of Beijing Institute of Petro-Chemical Technology, 2010, 18(4): 18-21. DOI: 10.3969/j.issn.1008-2565.2010.04.005 |
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| Authors: | Liu Jiabin Li Wenyuan |
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| Affiliation: | Liu Jiabin Li Wunyuan(Department of Communication Engineering,Beijing Institute of Petro-chemical Technology,Beijing 102617,China) |
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| Abstract: | Support vector machines(SVM) developed from the theory of structural risk minimization(SRM) provide a new approach for pattern classification.In this paper,we apply the SVM for multi-user detection(MUD) in wideband code division multiple access(WCDMA) mobile communication systems.Based on the construction of receiver with nonlinear kernel by using the sequential minimization optimization(SMO) algorithm,we propose an SVM-MUD for the systems.For the synchronous case,the bit error rate(BER) performance of the ... |
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| Keywords: | multi-user detection support vector machine WCDMA machine learning mobile communications |
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