MIMO Detection with Block Parallel Gibbs Sampling and Maximum Ratio Combining
MIMO Detection with Block Parallel Gibbs Sampling and Maximum Ratio Combining
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DOI：
10.1109/tencon50793.2020.9293711
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发表时间：
2020-11
期刊：
影响因子：
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通讯作者：
Kosuke Tomura;Y. Sanada;Yutaro Kobayashi
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文献类型：
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作者：
Kosuke Tomura;Y. Sanada;Yutaro Kobayashi
提出了一种分块并行吉布斯采样（BPGS）多输入多输出（MIMO）检测算法。在传统的吉布斯采样方案中，MIMO检测是逐符号地顺序执行的。所提出的方案将符号矢量划分为块，并在块中并行更新候选发送符号，使得单位周期内的迭代总数增加。此外，本文还采用了最大比合并（MRC）的方法来提高BPGS的精度。通过计算机仿真得到的数值结果表明，在高比特能量噪声谱密度条件下的比特误码率性能的改善与所提出的计划。当天线数为16×16，迭代次数为50次时，块大小为3的算法性能最佳。
In this paper, block parallel Gibbs sampling (BPGS) multiple-input multiple-output (MIMO) detection is proposed. In a conventional Gibbs sampling scheme, MIMO detection is carried out sequentially symbol-by-symbol. The proposed scheme divides a symbol vector to blocks and updates candidate transmit symbols in parallel in a block so that the total number of iterations in a unit period increases. Furthermore, maximum ratio combining (MRC) is adopted to BPGS to improve accuracy in this paper. Numerical results obtained through computer simulations show that bit error rate performance under high bit-energy-to-noise-spectrum-density conditions improves with the proposed scheme. It is also shown that the block size of three achieves the best performance when number of antennas is 16×16 and the number of iterations is 50.