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Exact Bayes’ theorem based probabilistic data association for iterative MIMO detection and decoding

Exact Bayes’ theorem based probabilistic data association for iterative MIMO detection and decoding
Exact Bayes’ theorem based probabilistic data association for iterative MIMO detection and decoding
In our previous work, it was shown that the conventional approximate Bayes' theorem based probabilistic data association (PDA) algorithms output "nominal APPs", which are unsuitable for the classic architecture of iterative detection and decoding (IDD) aided receivers. To circumvent this predicament, in this paper we propose an exact Bayes' theorem based logarithmic domain PDA (EB-Log-PDA) method, whose output has similar characteristics to the true APPs, and hence it is readily applicable to the classic IDD architecture of multiple-input multiple-output (MIMO) systems using M-ary modulation. Furthermore, we demonstrate that introducing inner iterations into EB-Log-PDA, which is common practice in conventional-PDA aided uncoded MIMO systems, would actually degrade the IDD receiver's performance, despite significantly increasing the overall computational complexity of the IDD receiver. Finally, we show that the EB-Log-PDA based IDD scheme operating without any inner PDA iterations has a similar performance to that of the optimal maximum a posteriori (MAP) detector based IDD receiver, while imposing a significantly lower computational complexity in the scenarios considered.
Bayes’ theorem, iterative detection and decoding, multiple-input multiple-output, MIMO, probabilistic dataassociation, PDA, M-ary modulation
1891-1896
Yang, Shaoshi
df1e6c38-ff3b-473e-b36b-4820db908e60
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Yang, Shaoshi
df1e6c38-ff3b-473e-b36b-4820db908e60
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Yang, Shaoshi and Hanzo, Lajos (2013) Exact Bayes’ theorem based probabilistic data association for iterative MIMO detection and decoding. 56th IEEE Global Communications Conference (IEEE GLOBECOM 2013), Atlanta, United States. 09 - 13 Dec 2013. pp. 1891-1896 . (doi:10.1109/GLOCOM.2013.6831350).

Record type: Conference or Workshop Item (Paper)

Abstract

In our previous work, it was shown that the conventional approximate Bayes' theorem based probabilistic data association (PDA) algorithms output "nominal APPs", which are unsuitable for the classic architecture of iterative detection and decoding (IDD) aided receivers. To circumvent this predicament, in this paper we propose an exact Bayes' theorem based logarithmic domain PDA (EB-Log-PDA) method, whose output has similar characteristics to the true APPs, and hence it is readily applicable to the classic IDD architecture of multiple-input multiple-output (MIMO) systems using M-ary modulation. Furthermore, we demonstrate that introducing inner iterations into EB-Log-PDA, which is common practice in conventional-PDA aided uncoded MIMO systems, would actually degrade the IDD receiver's performance, despite significantly increasing the overall computational complexity of the IDD receiver. Finally, we show that the EB-Log-PDA based IDD scheme operating without any inner PDA iterations has a similar performance to that of the optimal maximum a posteriori (MAP) detector based IDD receiver, while imposing a significantly lower computational complexity in the scenarios considered.

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More information

Published date: December 2013
Venue - Dates: 56th IEEE Global Communications Conference (IEEE GLOBECOM 2013), Atlanta, United States, 2013-12-09 - 2013-12-13
Keywords: Bayes’ theorem, iterative detection and decoding, multiple-input multiple-output, MIMO, probabilistic dataassociation, PDA, M-ary modulation
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 352200
URI: http://eprints.soton.ac.uk/id/eprint/352200
PURE UUID: 8f02ffe9-91ee-4dbb-9bd0-831a58e363e5
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 07 May 2013 14:30
Last modified: 18 Mar 2024 02:35

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Contributors

Author: Shaoshi Yang
Author: Lajos Hanzo ORCID iD

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