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Least Mean Square Aided Adaptive Detection in Hybrid Direct-Sequence Time-Hopping Ultrawide Bandwidth Systems

Record type: Conference or Workshop Item (Other)

In this contribution an adaptive detection scheme based on least mean square (LMS) principles is proposed and investigated in the context of the hybrid direct-sequence time-hopping ultrawide bandwidth (DS-TH UWB) systems. The bit-error-rate (BER) performance of the hybrid DS-TH UWB system is investigated when communicating over the UWB channels modelled by the Saleh-Valenzuela (S-V) channel model. Furthermore, since both the pure DS-UWB and pure TH-UWB constitute special examples of the hybrid DS-TH UWB, their BER performance is also investigated in this contribution for the sake of comparison with that of the hybrid DS-TH UWB. Our study and simulation results show that the LMS-aided adaptive detection can be a feasible detection scheme for deployment in practical DS-, TH- or hybrid DS-TH UWB systems. It can be shown that, with the aid of a training sequence of reasonable length, the considered UWB schemes are capable of achieving a BER performance which is close to that achieved by the minimum mean-square error (MMSE) detector with perfect channel knowledge.

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Citation

Ahmed, Qasim Zeeshan, Liu, Wei and Yang, Lie-Liang (2008) Least Mean Square Aided Adaptive Detection in Hybrid Direct-Sequence Time-Hopping Ultrawide Bandwidth Systems At IEEE VTC2008-Spring, Singapore. 11 - 14 May 2008.

More information

Published date: May 2008
Additional Information: Event Dates: 11-14 May 2008
Venue - Dates: IEEE VTC2008-Spring, Singapore, 2008-05-11 - 2008-05-14
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 265941
URI: http://eprints.soton.ac.uk/id/eprint/265941
PURE UUID: 64ab099a-f3d4-4b5c-8f89-c38c584dc253
ORCID for Lie-Liang Yang: ORCID iD orcid.org/0000-0002-2032-9327

Catalogue record

Date deposited: 13 Jun 2008 10:35
Last modified: 18 Jul 2017 07:21

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Contributors

Author: Qasim Zeeshan Ahmed
Author: Wei Liu
Author: Lie-Liang Yang ORCID iD

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