IEICE Transactions on Communications
Online ISSN : 1745-1345
Print ISSN : 0916-8516

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Forcible Search Scheme for Mixed Gibbs Sampling Massive MIMO Detection
Kenji YAMAZAKIYukitoshi SANADA
著者情報
キーワード: Gibbs sampling, MIMO detection
ジャーナル 認証あり 早期公開

論文ID: 2020EBP3030

この記事には本公開記事があります。
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In this paper, mixed Gibbs sampling multiple-input multiple-output (MIMO) detection with forcible search is proposed. In conventional Gibbs sampling MIMO detection, the problem of stalling occurs under high signal-to-noise ratios (SNRs) which degrades the detection performance. Mixed Gibbs sampling (MGS) is one solution to this problem. In MGS, random sampling is carried out with a constant probability regardless of whether a current search falls into a local minimum. In the proposed scheme, combined with MGS, multiple candidate symbols are forcibly changed when the search is captured by a local minimum. The search restarts away from the local minimum which effectively enlarges the search area in the solution space. Numerical results obtained through computer simulation show that the proposed scheme achieves better performance in a large scale MIMO system with QPSK signals.

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© 2020 The Institute of Electronics, Information and Communication Engineers
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