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A Threshold-Based Max-log-MPA Low Complexity Multiuser Detection Algorithm
by
Lu, Weidang
, Gu, Zonglin
, Zhang, Guanghua
, Zhao, Qiannan
, Ren, Jingqiu
in
maximum likelihood logarithm
/ message passing algorithm
/ multiuser detection
/ sparse code multiple access
/ threshold
2020
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A Threshold-Based Max-log-MPA Low Complexity Multiuser Detection Algorithm
by
Lu, Weidang
, Gu, Zonglin
, Zhang, Guanghua
, Zhao, Qiannan
, Ren, Jingqiu
in
maximum likelihood logarithm
/ message passing algorithm
/ multiuser detection
/ sparse code multiple access
/ threshold
2020
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A Threshold-Based Max-log-MPA Low Complexity Multiuser Detection Algorithm
Journal Article
A Threshold-Based Max-log-MPA Low Complexity Multiuser Detection Algorithm
2020
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Overview
Sparse Code Multiple Access (SCMA) technology is a new multiple access scheme based on non-orthogonal spread spectrum technology, which was proposed by Huawei in 2014. In the algorithm application of this technology, the original Message Passing Algorithm (MPA) has slow convergence speed and high algorithm complexity. The threshold-based MPA has a high Bit Error Ratio (BER) when the threshold is low. In the Maximum logarithm Message Passing Algorithm (Max-log-MPA), the approximation method is used, which will cause some messages to be lost and the detection performance to be poor. Therefore, in order to solve the above problems, a Threshold-Based Max-log-MPA (T-Max-log-MPA) low complexity multiuser detection algorithm is proposed in this paper. The Maximum logarithm (Max-log) algorithm is combined with threshold setting, and the stability of user nodes is considered as a necessary condition for decision in the algorithm. Before message updating, the user information nodes are judged whether the necessary conditions for the stability of the user node have been met, and then the threshold is determined. Only users who meet the threshold condition and pass the necessary condition of user node stability can be decoded in advance. In the whole process, the logarithm domain MPA algorithm is used to convert an exp operation and a multiplication operation into a maximum value and addition operation. The simulation results show that the proposed algorithm can effectively reduce the computational complexity while ensuring the BER, and with the increase of signal-to-noise ratio, the effect of the Computational Complexity Reduction Ratio (CCRR) is more obvious.
Publisher
MDPI,MDPI AG
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