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Differential evolution algorithm aided turbo channel estimation and multi-user detection for G.fast systems in the presence of FEXT

Differential evolution algorithm aided turbo channel estimation and multi-user detection for G.fast systems in the presence of FEXT
Differential evolution algorithm aided turbo channel estimation and multi-user detection for G.fast systems in the presence of FEXT
The ever-increasing demand for broadband Internet access has motivated the further development of the digital subscriber line to the G.fast standard in order to expand its operational band from 106MHz to 212MHz. Conventional farend crosstalk (FEXT) based cancellers falter in the upstream transmission of this emerging G.fast system. In this paper, we propose a novel differential evolution algorithm (DEA) aided turbo channel estimation (CE) and multi-user detection (MUD) scheme for the G.fast upstream including the frequency band up to 212MHz, which is capable of approaching the optimal Cramer- Rao lower bound of the channel estimate, whilst approaching the optimal maximum likelihood (ML) MUD’s performance associated with perfect channel state information, and yet only imposing about 5% of its computational complexity. Explicitly, the turbo concept is exploited by iteratively exchanging information between the continuous value-based DEA assisted channel estimator and the discrete value-based DEA MUD. Our extensive simulations show that 18 dB normalized mean square error gain is attained by the channel estimator and 10 dB signalto- noise ratio gain can be achieved by the MUD upon exploiting this iteration gain. We also quantify the influence of the CE error, of the copper length and of the impulse noise. Our study demonstrates that the proposed DEA aided turbo CE and MUD scheme is capable of offering near-capacity performance at an affordable complexity for the emerging G.fast systems.
2169-3536
33111-33128
Zhang, Jiankang
6add829f-d955-40ca-8214-27a039defc8a
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Zhang, Rong
3be8f78f-f079-4a3f-a151-76ecd5f378f4
Al Rawi, Anas F.
ba25fb37-b784-41d0-b014-1cc11dde7cf9
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Zhang, Jiankang
6add829f-d955-40ca-8214-27a039defc8a
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Zhang, Rong
3be8f78f-f079-4a3f-a151-76ecd5f378f4
Al Rawi, Anas F.
ba25fb37-b784-41d0-b014-1cc11dde7cf9
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Zhang, Jiankang, Chen, Sheng, Zhang, Rong, Al Rawi, Anas F. and Hanzo, Lajos (2018) Differential evolution algorithm aided turbo channel estimation and multi-user detection for G.fast systems in the presence of FEXT. IEEE Access, 6, 33111-33128. (doi:10.1109/ACCESS.2018.2847232).

Record type: Article

Abstract

The ever-increasing demand for broadband Internet access has motivated the further development of the digital subscriber line to the G.fast standard in order to expand its operational band from 106MHz to 212MHz. Conventional farend crosstalk (FEXT) based cancellers falter in the upstream transmission of this emerging G.fast system. In this paper, we propose a novel differential evolution algorithm (DEA) aided turbo channel estimation (CE) and multi-user detection (MUD) scheme for the G.fast upstream including the frequency band up to 212MHz, which is capable of approaching the optimal Cramer- Rao lower bound of the channel estimate, whilst approaching the optimal maximum likelihood (ML) MUD’s performance associated with perfect channel state information, and yet only imposing about 5% of its computational complexity. Explicitly, the turbo concept is exploited by iteratively exchanging information between the continuous value-based DEA assisted channel estimator and the discrete value-based DEA MUD. Our extensive simulations show that 18 dB normalized mean square error gain is attained by the channel estimator and 10 dB signalto- noise ratio gain can be achieved by the MUD upon exploiting this iteration gain. We also quantify the influence of the CE error, of the copper length and of the impulse noise. Our study demonstrates that the proposed DEA aided turbo CE and MUD scheme is capable of offering near-capacity performance at an affordable complexity for the emerging G.fast systems.

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Accepted/In Press date: 8 June 2018
e-pub ahead of print date: 13 June 2018
Published date: 6 July 2018

Identifiers

Local EPrints ID: 421416
URI: http://eprints.soton.ac.uk/id/eprint/421416
ISSN: 2169-3536
PURE UUID: d9fa0311-00bf-42ea-896b-3224bae51856
ORCID for Jiankang Zhang: ORCID iD orcid.org/0000-0001-5316-1711
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

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Date deposited: 11 Jun 2018 16:30
Last modified: 07 Oct 2020 04:16

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Contributors

Author: Jiankang Zhang ORCID iD
Author: Sheng Chen
Author: Rong Zhang
Author: Anas F. Al Rawi
Author: Lajos Hanzo ORCID iD

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