Partial MAP-based list detection for MIMO systems

Lin Bai; Jinho Choi

doi:10.1109/TVT.2008.2005196

Partial MAP-based list detection for MIMO systems

Lin Bai^*
, Jinho Choi

^*Corresponding author for this work

Swansea University

Research output: Contribution to journal › Article › peer-review

9 Scopus citations

Abstract

The partial maximum a posteriori probability (PMAP) principle can be applied to reduce the complexity of the multiple-input-multiple-output (MIMO) detection through the successive interference cancellation (SIC). In this paper, we apply the PMAP principle to the list detection method for MIMO detection, where the SIC is performed with a list of candidates. The PMAP principle helps to choose candidate symbol vectors in the list detection. It is shown that the proposed method outperforms the conventional list detection method with a reasonable complexity.

Original language	English
Pages (from-to)	2544-2548
Number of pages	5
Journal	IEEE Transactions on Vehicular Technology
Volume	58
Issue number	5
DOIs	https://doi.org/10.1109/TVT.2008.2005196
State	Published - 2009
Externally published	Yes

Keywords

Interference cancellation
List decoding
Maximum a posteriori probability (MAP) detection
Maximum likelihood (ML) detection
Multiple-input-multiple-output (MIMO) system
Vertical Bell Laboratories layered space-time (V-BLAST)

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10.1109/TVT.2008.2005196

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title = "Partial MAP-based list detection for MIMO systems",

abstract = "The partial maximum a posteriori probability (PMAP) principle can be applied to reduce the complexity of the multiple-input-multiple-output (MIMO) detection through the successive interference cancellation (SIC). In this paper, we apply the PMAP principle to the list detection method for MIMO detection, where the SIC is performed with a list of candidates. The PMAP principle helps to choose candidate symbol vectors in the list detection. It is shown that the proposed method outperforms the conventional list detection method with a reasonable complexity.",

keywords = "Interference cancellation, List decoding, Maximum a posteriori probability (MAP) detection, Maximum likelihood (ML) detection, Multiple-input-multiple-output (MIMO) system, Vertical Bell Laboratories layered space-time (V-BLAST)",

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AB - The partial maximum a posteriori probability (PMAP) principle can be applied to reduce the complexity of the multiple-input-multiple-output (MIMO) detection through the successive interference cancellation (SIC). In this paper, we apply the PMAP principle to the list detection method for MIMO detection, where the SIC is performed with a list of candidates. The PMAP principle helps to choose candidate symbol vectors in the list detection. It is shown that the proposed method outperforms the conventional list detection method with a reasonable complexity.

KW - Interference cancellation

KW - List decoding

KW - Maximum a posteriori probability (MAP) detection

KW - Maximum likelihood (ML) detection

KW - Multiple-input-multiple-output (MIMO) system

KW - Vertical Bell Laboratories layered space-time (V-BLAST)

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JO - IEEE Transactions on Vehicular Technology

JF - IEEE Transactions on Vehicular Technology

IS - 5

ER -

Partial MAP-based list detection for MIMO systems

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Keywords

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