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Research on Low Complexity K-best Sphere Decoding Algorithm for MIMO Systems

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Abstract

In order to reduce the complexity of hard-output K-best decoding algorithm in multiple-input multiple-output (MIMO) systems and guarantee performance of the system, we propose a bit-sort (BS) strategy based on bit counting operation in hardware implementation for the K-best decoder. The proposed BS K-best algorithm finds out the smallest \(K\) paths by scanning and counting the bits of every candidate, which is much simpler than the pairwise comparison operation in conventional K-best algorithm. Moreover, we proposed a dynamic bit-sort (DBS) strategy for the K-best decoder based on the BS strategy. The DBS K-best algorithm further reduces the complexity of BS K-best algorithm by selecting a dynamic \(K\) value that depends on the candidates. The complexity analysis shows the complexity of bit counting operations in proposed BS K-best algorithm is much less than that of the pairwise comparisons in conventional K-best algorithm, and the DBS K-best algorithm can further reduce about 50 % counting complexity of BS K-best algorithm. The simulation results show both the BS K-best decoder and DBS K-best decoder can achieve the same performance as that of hard-output sphere decoding algorithm if a proper \(K\) is selected.

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Authors and Affiliations

  1. School of Information Engineering, China Jiliang University, Hangzhou, 310018, Zhejiang, China

    Xizhong Lou, Qian Zhou, Yanmin Chen & Daorong Wu

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  1. Xizhong Lou
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  2. Qian Zhou
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  3. Yanmin Chen
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  4. Daorong Wu
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Correspondence to Xizhong Lou.

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Lou, X., Zhou, Q., Chen, Y. et al. Research on Low Complexity K-best Sphere Decoding Algorithm for MIMO Systems. Wireless Pers Commun 84, 547–563 (2015). https://doi.org/10.1007/s11277-015-2648-z

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  • DOI: https://doi.org/10.1007/s11277-015-2648-z

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