Adaptive multiple symbol decision feedback for non-coherent detection.

Non-coherent detection is a simple form of signal detection and demodulation for digital communications. The main drawback of this detection method is the performance penalty incurred, since the channel state information is not known at the receiver. Multiple symbol detection (MSD) is a technique em...

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Main Author: Govender, Nishkar Balakrishna.
Other Authors: Xu, Hong-Jun.
Language:en
Published: 2006
Subjects:
Online Access:http://hdl.handle.net/10413/1562
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spelling ndltd-netd.ac.za-oai-union.ndltd.org-ukzn-oai-http---researchspace.ukzn.ac.za-10413-15622014-02-08T03:49:07ZAdaptive multiple symbol decision feedback for non-coherent detection.Govender, Nishkar Balakrishna.Digital communications.Theses--Electrical engineering.Signal detection.Theses--Electrical engineering.Non-coherent detection is a simple form of signal detection and demodulation for digital communications. The main drawback of this detection method is the performance penalty incurred, since the channel state information is not known at the receiver. Multiple symbol detection (MSD) is a technique employed to close the gap between coherent and non-coherent detection schemes. Differentially encoded JW-ary phase shift keying (DM-PSK) is the classic modulation technique that is favourable for non-coherent detection. The main drawback for standard differential detection (SDD) has been the error floor incurred for frequency flat fading channels. Recently a decision feedback differential detection (DFDD) scheme, which uses the concept of MSD was proposed and offered significant performance gain over the SDD in the mobile flat fading channel, almost eliminating the error floor. This dissertation investigates multiple symbol decision feedback detection schemes, and proposes alternate adaptive strategies for non-coherent detection. An adaptive algorithm utilizing the numerically stable QR decomposition that does not require training symbols is proposed, named QR-DFDD. The QR-DFDD is modified to use a simpler QR decomposition method which incorporates sliding windows: QRSW-DFDD. This structure offers good tracking performance in flat fading conditions, while achieving near optimal DFDD performance. A bit interleaved coded decision feedback differential demodulation (DFDM) scheme, which takes advantage of the decision feedback concept and iterative decoding, was introduced by Lampe in 2001. This low complexity iterative demodulator relied on accurate channel statistics for optimal performance. In this dissertation an alternate adaptive DFDM is introduced using the recursive least squares (RLS) algorithm. The alternate iterative decoding procedure makes use of the convergence properties of the RLS algorithm that is more stable and achieves superior performance compared to the DFDM.Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2006.Xu, Hong-Jun.Takawira, Fambirai.20062006Thesishttp://hdl.handle.net/10413/1562en
collection NDLTD
language en
sources NDLTD
topic Digital communications.
Theses--Electrical engineering.
Signal detection.
Theses--Electrical engineering.
spellingShingle Digital communications.
Theses--Electrical engineering.
Signal detection.
Theses--Electrical engineering.
Govender, Nishkar Balakrishna.
Adaptive multiple symbol decision feedback for non-coherent detection.
description Non-coherent detection is a simple form of signal detection and demodulation for digital communications. The main drawback of this detection method is the performance penalty incurred, since the channel state information is not known at the receiver. Multiple symbol detection (MSD) is a technique employed to close the gap between coherent and non-coherent detection schemes. Differentially encoded JW-ary phase shift keying (DM-PSK) is the classic modulation technique that is favourable for non-coherent detection. The main drawback for standard differential detection (SDD) has been the error floor incurred for frequency flat fading channels. Recently a decision feedback differential detection (DFDD) scheme, which uses the concept of MSD was proposed and offered significant performance gain over the SDD in the mobile flat fading channel, almost eliminating the error floor. This dissertation investigates multiple symbol decision feedback detection schemes, and proposes alternate adaptive strategies for non-coherent detection. An adaptive algorithm utilizing the numerically stable QR decomposition that does not require training symbols is proposed, named QR-DFDD. The QR-DFDD is modified to use a simpler QR decomposition method which incorporates sliding windows: QRSW-DFDD. This structure offers good tracking performance in flat fading conditions, while achieving near optimal DFDD performance. A bit interleaved coded decision feedback differential demodulation (DFDM) scheme, which takes advantage of the decision feedback concept and iterative decoding, was introduced by Lampe in 2001. This low complexity iterative demodulator relied on accurate channel statistics for optimal performance. In this dissertation an alternate adaptive DFDM is introduced using the recursive least squares (RLS) algorithm. The alternate iterative decoding procedure makes use of the convergence properties of the RLS algorithm that is more stable and achieves superior performance compared to the DFDM. === Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2006.
author2 Xu, Hong-Jun.
author_facet Xu, Hong-Jun.
Govender, Nishkar Balakrishna.
author Govender, Nishkar Balakrishna.
author_sort Govender, Nishkar Balakrishna.
title Adaptive multiple symbol decision feedback for non-coherent detection.
title_short Adaptive multiple symbol decision feedback for non-coherent detection.
title_full Adaptive multiple symbol decision feedback for non-coherent detection.
title_fullStr Adaptive multiple symbol decision feedback for non-coherent detection.
title_full_unstemmed Adaptive multiple symbol decision feedback for non-coherent detection.
title_sort adaptive multiple symbol decision feedback for non-coherent detection.
publishDate 2006
url http://hdl.handle.net/10413/1562
work_keys_str_mv AT govendernishkarbalakrishna adaptivemultiplesymboldecisionfeedbackfornoncoherentdetection
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