The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Dans cet article, une détection mixte à entrées multiples et sorties multiples (MIMO) par échantillonnage de Gibbs avec recherche forcée est proposée. Dans la détection MIMO à échantillonnage Gibbs classique, le problème de décrochage se produit lorsque les rapports signal/bruit (SNR) sont élevés, ce qui dégrade les performances de détection. L'échantillonnage mixte de Gibbs (MGS) est une solution à ce problème. Dans MGS, l'échantillonnage aléatoire est effectué avec une probabilité constante, que la recherche en cours tombe ou non dans un minimum local. Dans le schéma proposé, combiné avec MGS, plusieurs symboles candidats sont modifiés de force lorsque la recherche est capturée par un minimum local. La recherche redémarre à partir du minimum local, ce qui élargit effectivement la zone de recherche dans l'espace de solution. Les résultats numériques obtenus par simulation informatique montrent que le schéma proposé permet d'obtenir de meilleures performances dans un système MIMO à grande échelle avec des signaux QPSK.
Kenji YAMAZAKI
Keio University
Yukitoshi SANADA
Keio University
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Copier
Kenji YAMAZAKI, Yukitoshi SANADA, "Forcible Search Scheme for Mixed Gibbs Sampling Massive MIMO Detection" in IEICE TRANSACTIONS on Communications,
vol. E104-B, no. 4, pp. 419-427, April 2021, doi: 10.1587/transcom.2020EBP3030.
Abstract: 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.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2020EBP3030/_p
Copier
@ARTICLE{e104-b_4_419,
author={Kenji YAMAZAKI, Yukitoshi SANADA, },
journal={IEICE TRANSACTIONS on Communications},
title={Forcible Search Scheme for Mixed Gibbs Sampling Massive MIMO Detection},
year={2021},
volume={E104-B},
number={4},
pages={419-427},
abstract={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.},
keywords={},
doi={10.1587/transcom.2020EBP3030},
ISSN={1745-1345},
month={April},}
Copier
TY - JOUR
TI - Forcible Search Scheme for Mixed Gibbs Sampling Massive MIMO Detection
T2 - IEICE TRANSACTIONS on Communications
SP - 419
EP - 427
AU - Kenji YAMAZAKI
AU - Yukitoshi SANADA
PY - 2021
DO - 10.1587/transcom.2020EBP3030
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E104-B
IS - 4
JA - IEICE TRANSACTIONS on Communications
Y1 - April 2021
AB - 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.
ER -