The University of Southampton
University of Southampton Institutional Repository

A probabilistic data association based MIMO detector using joint detection of consecutive symbol vectors

Record type: Conference or Workshop Item (Paper)

A new probabilistic data association (PDA) approach is proposed for symbol detection in spatial multiplexing multiple-input multiple-output (MIMO) systems. By designing a joint detection (JD) structure for consecutive symbol vectors in the same transmit burst, more a priori information is exploited when updating the estimated posterior marginal probabilities for each symbol per iteration. Therefore the proposed PDA detector (denoted as PDA-JD detector) outperforms the conventional PDA detectors in the context of correlated input bit streams. Moreover, the conventional PDA detectors are shown to be a special case of the PDA-JD detector. Simulations and analyses are given to demonstrate the effectiveness of the new method.

PDF pda_iccs.pdf - Version of Record
Download (133kB)

Citation

Yang, Shaoshi, Lv, Tiejun, Yun, Xiang, Su, Xinghui and Xia, Jinhuan (2008) A probabilistic data association based MIMO detector using joint detection of consecutive symbol vectors At 11th IEEE Singapore International Conference on Communication Systems (IEEE ICCS 2008), China. 19 - 21 Nov 2008. , pp. 436-440. (doi:10.1109/ICCS.2008.4737221).

More information

Published date: November 2008
Venue - Dates: 11th IEEE Singapore International Conference on Communication Systems (IEEE ICCS 2008), China, 2008-11-19 - 2008-11-21
Keywords: gaussian approximation, mimo detection, maximum likelihood detection, ml detection, probabilistic data association, pda
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 272119
URI: http://eprints.soton.ac.uk/id/eprint/272119
PURE UUID: e1765906-900a-4f86-8751-6d31a57e53de

Catalogue record

Date deposited: 26 Mar 2011 04:20
Last modified: 18 Jul 2017 06:34

Export record

Altmetrics

Contributors

Author: Shaoshi Yang
Author: Tiejun Lv
Author: Xiang Yun
Author: Xinghui Su
Author: Jinhuan Xia

University divisions


Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×