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MIMO-PLC系统中基于条件数阈值选择的信号检测算法

Signal detection algorithm based on threshold selection of conditional number in MIMO-PLC system

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【作者】 聂熊波李想林欢

【Author】 Nie Xiongbo;Li Xiang;Lin Huan;China Three Gorges Corporation;Chongqing Key Laboratory of New Generation Broadband Mobile Communication Technology,University of Posts & Telecommunications;

【机构】 中国长江三峡集团有限公司重庆邮电大学新一代宽带移动通信重点实验室

【摘要】 为了满足电力线通信(power line communication,PLC)对更大容量和更广覆盖范围的需求,多输入多输出(multiple-input multiple-output,MIMO)技术已逐渐应用于PLC中,实现了高速率的数据传输,但MIMO-PLC信道具有严重的多径效应和频率选择性衰减的特性,而且不同子载波的信道质量差异性大,使现有的信号检测算法不能获得良好的性能。提出一种基于条件数阈值选择的检测算法,利用信道矩阵的条件数来衡量信道质量的好坏,设置最佳条件数阈值,在信道条件数小于或者等于阈值时,选择CLLL-MMSE-SQRD检测算法,而在信道条件数大于阈值时,选择QRD-M检测算法。通过仿真验证,该算法能够达到最优检测算法的性能,而且在16QAM调制方式下,该算法复杂度相比于QRD-M检测算法降低了44%,且随着调制阶数的增加复杂度降低更为明显。

【Abstract】 MIMO technology has been applied to PLC to meet the demand of PLC for larger capacity and wider coverage,and it can achieve high-speed data transmission. However,the channel of MIMO-PLC system has the characteristics of serious multipath effect and frequency selective fading,and the channel quality of different subcarriers is quite different. Therefore,the existing signal detection algorithms cannot achieve good performance. This paper proposed a detection algorithm based on condition number threshold selection,and used the condition number of the channel matrix to measure the quality of the channel and set the threshold of the optimal condition number. It selected the CLLL-MMSE-SQRD detection algorithm when the condition number of channel was less than or equal to the threshold,and the selected QRD-M detection algorithm when the condition number of channel was greater than the threshold. The simulation results prove that the proposed algorithm can reach the performance of optimal detection algorithm. In the 16 QAM modulation mode,the complexity of the proposed algorithm is reduced by 44% compared with the QRD-M detection algorithm,and with the increase of modulation order,the complexity is reduced more obviously.

  • 【文献出处】 计算机应用研究 ,Application Research of Computers , 编辑部邮箱 ,2020年01期
  • 【分类号】TN913.6
  • 【网络出版时间】2018-11-05 11:44
  • 【被引频次】1
  • 【下载频次】78
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