计算机工程

• 移动互联与通信技术 • 上一篇    下一篇

低复杂度的空间调制信号检测

陈发堂,龙云波,王与凡   

  1. (重庆邮电大学 重庆市移动通信技术重点实验室,重庆 400065)
  • 收稿日期:2017-06-22 出版日期:2018-03-15 发布日期:2018-03-15
  • 作者简介:陈发堂(1965—),男,研究员,主研方向为移动通信、LTE系统开发;龙云波、王与凡,硕士研究生。
  • 基金项目:
    国家科技重大专项“新一代宽带无线移动通信网”(2017ZX03001021-004)。

Low-complexity Signal Detection for Spatial Modulation

CHEN Fatang,LONG Yunbo,WANG Yufan   

  1. (Chongqing Key Lab of Mobile Communication Technology,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)
  • Received:2017-06-22 Online:2018-03-15 Published:2018-03-15

摘要: 空间调制(SM)算法在接收端常用最大释然(ML)信号检测获得发送天线编号以及调制符号,恢复发射信息比特,但是ML算法复杂度随着天线数和调制阶数的增加呈指数增长,不具有实用性。针对该难题,提出一种新的低复杂度次最优检测算法。通过设置合理的判决门限将信号矢量检测(SVD)和硬限最大似然(HL-ML)算法进行联合。蒙特卡洛仿真结果表明,该算法的误比特率检测性能比SVD算法更接近ML算法,且复杂度与ML算法相比降低了85%。

关键词: 空间调制, 多输入多输出, 最大似然, 信号矢量检测, 硬限最大似然

Abstract: At receiver,Space Modulation(SM) algorithm always uses Maximum Likelihood(ML) signal detection to obtain the transmission antenna number and the modulation signal and restore the transmitted information bit.However,the complexity of ML algorithm increases exponentially with the increase of the number of antennas and the number of modulation orders,which is not practical.To solve this problem,this paper proposes a new low complexity sub-optimal detection algorithm by setting up a reasonable decision threshold combining Signal Vector Detection(SVD) and Hard Limited-Maximum Likelihood(HL-ML) algorithm.Monte Carlo simulation results show that the detection performance of Bit Error Rate(BER) of the proposed algorithm is more close to the ML algorithm than the SVD algorithm,and the complexity of the algorithm is reduced by 85% compared with the ML algorithm.

Key words: Spatial Modulation(SM), Multiple Input Multiple Output(MIMO), Maximum Likelihood(ML), Signal Vector Detection(SVD), Hard Limiting-Maximum Likelihood(HL-ML)

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