基于信噪比排序的MIMO-OFDM信号检测方法

发布时间：2019-04-30 18:11

【摘要】：在多输入多输出(multiple-input multiple-output,MIMO)系统信号检测中,基于虚实分解的宽度优先检测算法(QR decomposition associated with the M-algorithm to MLD,QRD-M)通过QR分解和对每层星座点的筛选,实现了较低复杂度的检测,具有很好的应用前景。但该算法随收发天线数和调制阶数的增加而难以实现性能与复杂度的折衷。针对此缺点,提出了一种基于信噪比排序的信号检测改进方法。该方法在传统QRD-M算法的基础上,通过对不同接收天线进行信噪比(signal-noise ratio,SNR)排序,从信噪比最大的天线开始检测,避免了误差传播现象,从而加速树搜索过程,再结合动态门限树搜索,不断缩小搜索半径,直至找到最小累计度量值所在分支。仿真结果表明,与传统QRD-MLD算法相比,基于性噪比排序的动态门限信号检测算法能以较低的复杂度获得接近于最大似然检测的性能。
[Abstract]:In the signal detection of multi-input multiple-output (multiple-input multiple-output,MIMO) system, the width-first detection algorithm based on virtual-real decomposition (QR decomposition associated with the M-algorithm to MLD,QRD-M) passes the QR decomposition and the selection of each layer of star points. The low complexity detection is realized, and it has a good application prospect. However, it is difficult to achieve the tradeoff between performance and complexity with the increase of the number of receiving and transmitting antennas and the modulation order. In order to solve this problem, an improved signal detection method based on signal-to-noise ratio (SNR) ordering is proposed. Based on the traditional QRD-M algorithm, this method can detect the antenna with the largest signal-to-noise ratio (SNR) by sorting the signal-to-noise ratio (signal-noise ratio,SNR) of different receiving antennas, thus avoiding the error propagation phenomenon and speeding up the tree search process. Combined with the dynamic threshold tree search, the search radius is reduced continuously, until the branch of the minimum cumulative metric is found. The simulation results show that compared with the traditional QRD-MLD algorithm, the dynamic threshold signal detection algorithm based on the ranking of the sexual-to-noise ratio can obtain the performance close to the maximum likelihood detection with lower complexity.
【作者单位】：重庆邮电大学通信核心芯片协议及系统应用创新团队;
【基金】：国家03重大专项(2015ZX03001010-003)~~
【分类号】：TN911.23;TN919.3

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