The University of Southampton
University of Southampton Institutional Repository

Genetic Algorithm Assisted Multiuser Detection in Asynchronous CDMA Communications

Genetic Algorithm Assisted Multiuser Detection in Asynchronous CDMA Communications
Genetic Algorithm Assisted Multiuser Detection in Asynchronous CDMA Communications
The up-link transmissions of mobile stations are typically uncoordinated, which lead to asynchronous DS-CDMA systems. Provided that the propagation delay differences of users are less than one symbol duration, every bit of each user is interfered by two consecutive bits of every other user supported by the system which are overlapping with the bit of interest. This is only true, however, with the proviso of an identical channel bit rate for all the users. Hence the multiuser detector (MUD) must have knowledge of these two overlapping bits, in order to efficiently detect the desired bit (DB). Suboptimal MUDs have been proposed based on a truncated observation window, in which the overlapping 'edge' bits are tentatively estimated by some other means. Using a similar approach, a MUD is developed in this contribution which invokes genetic algorithms (GAs), in order to estimate the DBs within the truncated observation window as well as to simultaneously improve the edge bits' error probability (EBEP). Computer simulations showed that by using GAs for improving the reliability of the edge bits, our proposed MUD can achieve a near-optimum DBEP performance, while imposing a lower complexity compared to that of the optimum MUD.
826-830
Yen, K.
612372e4-f48b-4d17-8e9f-6dd57676d3e9
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1
Yen, K.
612372e4-f48b-4d17-8e9f-6dd57676d3e9
Hanzo, L.
66e7266f-3066-4fc0-8391-e000acce71a1

Yen, K. and Hanzo, L. (2001) Genetic Algorithm Assisted Multiuser Detection in Asynchronous CDMA Communications. ICC 2001: IEEE International Conference on Communications, , Helsinki, Finland. 11 - 15 Jun 2001. pp. 826-830 .

Record type: Conference or Workshop Item (Paper)

Abstract

The up-link transmissions of mobile stations are typically uncoordinated, which lead to asynchronous DS-CDMA systems. Provided that the propagation delay differences of users are less than one symbol duration, every bit of each user is interfered by two consecutive bits of every other user supported by the system which are overlapping with the bit of interest. This is only true, however, with the proviso of an identical channel bit rate for all the users. Hence the multiuser detector (MUD) must have knowledge of these two overlapping bits, in order to efficiently detect the desired bit (DB). Suboptimal MUDs have been proposed based on a truncated observation window, in which the overlapping 'edge' bits are tentatively estimated by some other means. Using a similar approach, a MUD is developed in this contribution which invokes genetic algorithms (GAs), in order to estimate the DBs within the truncated observation window as well as to simultaneously improve the edge bits' error probability (EBEP). Computer simulations showed that by using GAs for improving the reliability of the edge bits, our proposed MUD can achieve a near-optimum DBEP performance, while imposing a lower complexity compared to that of the optimum MUD.

Text
icc-yen01.pdf - Other
Download (248kB)

More information

Published date: June 2001
Additional Information: CD Rom available. Event Dates: 11-15 June 2001 Organisation: IEEE Address: Helsinki, Finland
Venue - Dates: ICC 2001: IEEE International Conference on Communications, , Helsinki, Finland, 2001-06-11 - 2001-06-15
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 255970
URI: http://eprints.soton.ac.uk/id/eprint/255970
PURE UUID: fd6ecefa-cd43-4869-b04c-a427036e0ebf
ORCID for L. Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 08 Jan 2004
Last modified: 18 Mar 2024 02:33

Export record

Contributors

Author: K. Yen
Author: L. Hanzo ORCID iD

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.

×