2017年2月2日
Error recovery with relaxed MAP estimation for massive MIMO signal detection
Proceedings of 2016 International Symposium on Information Theory and Its Applications, ISITA 2016
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- 開始ページ
- 478
- 終了ページ
- 482
- 記述言語
- 掲載種別
- 研究論文(国際会議プロシーディングス)
- 出版者・発行元
- IEEE
This paper proposes a maximum a posteriori (MAP) estimation-based error recovery method for massive multiple-input multiple-output (MIMO) signal detection. The error recovery is a technique to improve the estimate of transmitted signals taking advantage of the sparsity of the error signal. We formulate the error recovery problem as the MAP estimation, where not only the sparsity but also the discreteness of the error are taken into consideration explicitly. In the proposed MAP estimation, we can also use not only the hard decision of the transmitted signal vector but also the soft decision obtained before the error recovery. The problem of MAP estimation is relaxed into the sum-of-absolute-value optimization problem, which can be efficiently solved with proximal splitting methods. Simulation results show that the proposed method outperforms the conventional method in terms of bit error rate (BER) performance.
- リンク情報
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- DBLP
- https://dblp.uni-trier.de/rec/conf/isita/HayakawaH16
- Scopus
- https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85015250519&origin=inward
- Scopus Citedby
- https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85015250519&origin=inward
- URL
- http://ieeexplore.ieee.org/document/7840470/
- URL
- https://dblp.uni-trier.de/conf/isita/2016
- URL
- https://dblp.uni-trier.de/db/conf/isita/isita2016.html#HayakawaH16
- ID情報
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- DBLP ID : conf/isita/HayakawaH16
- SCOPUS ID : 85015250519