基于预处理共轭梯度法的低复杂度信号检测算法
TN929.5; 大规模多输入多输出系统中,最小均方误差信号检测算法是近似最优的,但由于其涉及矩阵求逆,计算复杂度随着天线数量增加呈指数增长.提出了低复杂度的预处理共轭梯度信号检测算法,该算法通过预处理技术降低矩阵条件数,从而加快共轭梯度信号检测算法的收敛速度.仿真结果显示,该算法在小数量的迭代中能够达到和最小均方误差检测算法相似的误码率,算法复杂度下降了一个数量级.相比直接用共轭梯度法,能够更快收敛到最佳值....
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| Published in | 电信科学 Vol. 32; no. 4; pp. 30 - 35 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
中国通信学会
01.04.2016
人民邮电出版社有限公司 西安邮电大学通信与信息工程学院,陕西 西安 710061%西安交通大学软件学院,陕西 西安,710049 西安交通大学软件学院,陕西 西安 710049 |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1000-0801 |
| DOI | 10.11959/j.issn.1000-0801.2016092 |
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| Abstract | TN929.5; 大规模多输入多输出系统中,最小均方误差信号检测算法是近似最优的,但由于其涉及矩阵求逆,计算复杂度随着天线数量增加呈指数增长.提出了低复杂度的预处理共轭梯度信号检测算法,该算法通过预处理技术降低矩阵条件数,从而加快共轭梯度信号检测算法的收敛速度.仿真结果显示,该算法在小数量的迭代中能够达到和最小均方误差检测算法相似的误码率,算法复杂度下降了一个数量级.相比直接用共轭梯度法,能够更快收敛到最佳值. |
|---|---|
| AbstractList | TN929.5; 大规模多输入多输出系统中,最小均方误差信号检测算法是近似最优的,但由于其涉及矩阵求逆,计算复杂度随着天线数量增加呈指数增长.提出了低复杂度的预处理共轭梯度信号检测算法,该算法通过预处理技术降低矩阵条件数,从而加快共轭梯度信号检测算法的收敛速度.仿真结果显示,该算法在小数量的迭代中能够达到和最小均方误差检测算法相似的误码率,算法复杂度下降了一个数量级.相比直接用共轭梯度法,能够更快收敛到最佳值. 大规模多输入多输出系统中,最小均方误差信号检测算法是近似最优的,但由于其涉及矩阵求逆,计算复杂度随着天线数量增加呈指数增长。提出了低复杂度的预处理共轭梯度信号检测算法,该算法通过预处理技术降低矩阵条件数,从而加快共轭梯度信号检测算法的收敛速度。仿真结果显示,该算法在小数量的迭代中能够达到和最小均方误差检测算法相似的误码率,算法复杂度下降了一个数量级。相比直接用共轭梯度法,能够更快收敛到最佳值。 |
| Author | 曲桦 梁静 赵季红 王伟华 |
| AuthorAffiliation | 西安交通大学软件学院,陕西西安710049 西安邮电大学通信与信息工程学院,陕西西安710061 |
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| Author_FL | ZHAO Jihong LIANG Jing QU Hua WANG Weihua |
| Author_FL_xml | – sequence: 1 fullname: QU Hua – sequence: 2 fullname: LIANG Jing – sequence: 3 fullname: ZHAO Jihong – sequence: 4 fullname: WANG Weihua |
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| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
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| DOI | 10.11959/j.issn.1000-0801.2016092 |
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| DocumentTitleAlternate | Low-complexity signal detection algorithm based on preconditioned conjugate gradient method |
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| EndPage | 35 |
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| Keywords | 最小均方误差 共轭梯度法 大规模多输入多输出 conjugate gradient method minimum mean square error large-scale multiple-input multiple-output |
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| Notes | large-scale multiple-input multiple-output; conjugate gradient method; minimum mean square error For large-scale multiple-input multiple-output system, minimum mean square error signal detection algorithm is near-optimal but involves matrix inversion, and complexity is growing exponentially. So less-complexity signal detection algorithm using preconditioned conjugate gradient method was proposed, the algorithm reduced the condition number of matrix by pretreatment technology, thus speeding up the convergence rate of conjugate gradient signal detection algorithm. The simulation results show that the proposed algorithm can achieve the near-optimal bit error rate performance of minimum mean square error detection algorithm with a small number of iterations, and computation complexity reduces a order of magnitude. Compared with the conjugate gradient method, the proposed algorithm can quickly converge to the optimum value. 11-2103/TN QU Hua, LIANG Jing, ZHAO Jihong, WANG Weihua（ 1. School of Software Engineering, Xi |
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| Publisher | 中国通信学会 人民邮电出版社有限公司 西安邮电大学通信与信息工程学院,陕西 西安 710061%西安交通大学软件学院,陕西 西安,710049 西安交通大学软件学院,陕西 西安 710049 |
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| SubjectTerms | 共轭梯度法 大规模多输入多输出 最小均方误差 |
| Title | 基于预处理共轭梯度法的低复杂度信号检测算法 |
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