基于时间相关性的梯度追踪多用户检测算法

doi:10.12305/j.issn.1001-506X.2022.09.31

Abstract

Abstract:

To reduce the complexity of multi-user detection at the base station in massive machine type communication, the correlation of active devices in adjacent slots and the gradient pursuit algorithm are used to propose a correlation-assisted gradient pursuit multi-user detection (CAGP-MUD) algorithm. The CAGP-MUD algorithm not only avoids the process of matrix inversion, but also reduces the number of iterations of other slots except the first slot. To reduce the multi-user detection complexity even further, the idea of stage wise weak is introduced into the framework of the CAGP-MUD algorithm, and a correlation-assisted group gradient pursuit multi-user detection algorithm is proposed. This algorithm uses the weakening of the maximum gradient as a threshold to select multiple active devices in each iteration, so that the iteration number can be reduced. Theoretical analysis and experimental results show that, compared with similar algorithms, the computational cost of these two algorithms is reduced by more than 60%.

Key words: massive machine type communication, time correlation, gradient pursuit, multi-user detection

CLC Number:

TN929.5

Fang JIANG, Yaqing YANG, Guoliang ZHENG, Yi WANG, Yaohua XU, Xiangqing WU. Gradient pursuit multi-user detection algorithm based on time correlation[J]. Systems Engineering and Electronics, 2022, 44(9): 2955-2962.

Figures/Tables 6

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References 30

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Gradient pursuit multi-user detection algorithm based on time correlation

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