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Multiple-symbol differential sphere detection and decision-feedback differential detection conceived for differential QAM

Multiple-symbol differential sphere detection and decision-feedback differential detection conceived for differential QAM
Multiple-symbol differential sphere detection and decision-feedback differential detection conceived for differential QAM
Multiple-Symbol Differential Sphere Detection (MSDSD) relies on the knowledge of channel correlation. More explicitly, for Differential PSK (DPSK), the transmitted symbols’ phases form a unitary matrix, which can be separated from the channel’s correlation matrix by the classic Multiple-Symbol Differential Detection (MSDD), so that a lower triangular matrix extracted from the inverted channel correlation matrix is utilized for the MSDSD’s sphere decoding. However, for Differential QAM (DQAM), the transmitted symbols’ amplitudes cannot form a unitary matrix, which implies that the MSDD’s channel correlation matrix becomes amplitude-dependent and remains unknown, unless all the data-carrying symbol amplitudes are detected. In order to tackle this open problem, in this paper, we propose to determine the MSDD’s non-constant amplitudedependent channel correlation matrix with the aid of a sphere decoder, so that the classic MSDSD algorithms that were originally conceived for DPSK may also be invoked for DQAM detection. As a result, our simulation results demonstrate that the MSDSD aided DQAM schemes substantially outperform their DPSK counterparts. However, the price paid is that the detection complexity of MSDSD is also significantly increased. In order to mitigate this, we then propose a reduced-complexity MSDSD search strategy specifically conceived for DQAM constellations, which separately map bits to their ring-amplitude index and phase index. Furthermore, the classic Decision-Feedback Differential Detection (DFDD) conceived for DQAM relies on a constant channel correlation matrix, which implies that these DFDD solutions are sub-optimal and they are not equivalent to the optimum MSDD operating in decision-feedback mode. With the advent for solving the open problem of MSDSD aided DQAM, we further propose to improve the conventional DFDD aided DQAM solutions in this paper.
decision-feedback differential detection, differential qam, multiple-symbol differential sphere detection
0018-9545
8345 - 8360
Xu, Chao
5710a067-6320-4f5a-8689-7881f6c46252
Ng, Soon
e19a63b0-0f12-4591-ab5f-554820d5f78c
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Xu, Chao
5710a067-6320-4f5a-8689-7881f6c46252
Ng, Soon
e19a63b0-0f12-4591-ab5f-554820d5f78c
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Xu, Chao, Ng, Soon and Hanzo, Lajos (2015) Multiple-symbol differential sphere detection and decision-feedback differential detection conceived for differential QAM. IEEE Transactions on Vehicular Technology, 65 (10), 8345 - 8360.

Record type: Article

Abstract

Multiple-Symbol Differential Sphere Detection (MSDSD) relies on the knowledge of channel correlation. More explicitly, for Differential PSK (DPSK), the transmitted symbols’ phases form a unitary matrix, which can be separated from the channel’s correlation matrix by the classic Multiple-Symbol Differential Detection (MSDD), so that a lower triangular matrix extracted from the inverted channel correlation matrix is utilized for the MSDSD’s sphere decoding. However, for Differential QAM (DQAM), the transmitted symbols’ amplitudes cannot form a unitary matrix, which implies that the MSDD’s channel correlation matrix becomes amplitude-dependent and remains unknown, unless all the data-carrying symbol amplitudes are detected. In order to tackle this open problem, in this paper, we propose to determine the MSDD’s non-constant amplitudedependent channel correlation matrix with the aid of a sphere decoder, so that the classic MSDSD algorithms that were originally conceived for DPSK may also be invoked for DQAM detection. As a result, our simulation results demonstrate that the MSDSD aided DQAM schemes substantially outperform their DPSK counterparts. However, the price paid is that the detection complexity of MSDSD is also significantly increased. In order to mitigate this, we then propose a reduced-complexity MSDSD search strategy specifically conceived for DQAM constellations, which separately map bits to their ring-amplitude index and phase index. Furthermore, the classic Decision-Feedback Differential Detection (DFDD) conceived for DQAM relies on a constant channel correlation matrix, which implies that these DFDD solutions are sub-optimal and they are not equivalent to the optimum MSDD operating in decision-feedback mode. With the advent for solving the open problem of MSDSD aided DQAM, we further propose to improve the conventional DFDD aided DQAM solutions in this paper.

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Accepted/In Press date: 16 December 2015
e-pub ahead of print date: 23 December 2015
Additional Information: (c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Keywords: decision-feedback differential detection, differential qam, multiple-symbol differential sphere detection

Identifiers

Local EPrints ID: 385823
URI: https://eprints.soton.ac.uk/id/eprint/385823
ISSN: 0018-9545
PURE UUID: 15a1a02a-626d-4ddf-88f9-94e959f92d4f
ORCID for Chao Xu: ORCID iD orcid.org/0000-0002-8423-0342
ORCID for Soon Ng: ORCID iD orcid.org/0000-0002-0930-7194
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 25 Jan 2016 10:16
Last modified: 20 Sep 2018 00:31

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