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LDPC-COFDM for PLC in Non-Gaussian Noise Using LLRs Derived from Effective Noise PDFs

Lookup NU author(s): Ghanim Al-Rubaye, Professor Harris Tsimenidis, Dr Martin Johnston



This is the authors' accepted manuscript of an article that has been published in its final definitive form by IET, 2017.

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In this paper, the performance of irregular low-density parity check (LPDC) coded orthogonalfrequency division multiplexing (COFDM) utilizing 4096 quadrature amplitude modulation (4096-QAM) is investigated over multipath power-line communication (PLC) channel. The effective complex-valued ratio distributions of the noise samples at the zero-forcing (ZF) equalizer output consideringboth frequency-selective multipath PLCs, background and impulsive noise are derived, in additionto the condition for optimum detection of 4096-QAM and the bit error rate (BER). Moreover, theperformance of the LDPC decoder is improved by computing the log-likelihood ratios (LLRs) requiredfor soft decoding based on the derived PDFs. Numerical results obtained using the newly derived LLRsdemonstrate a significant performance improvement compared to the conventional receiver that usesblanking impulsive noise mitigation method and LLRs computed based on the Gaussian distribution.Furthermore, EXtrinsic Information Transfer (EXIT) chart analysis demonstrates that the proposedapproach requires fewer iterations for convergence compared to the conventional receiver. Finally,utilizing channel bandwidth of 22.4 MHz, the proposed system offers an improvement of 111 Mbps2over the conventional system to reach a maximum data throughput of 256 Mbps for a signal to noiseratio (SNR) of 39 dB and BER of 10 −5 .

Publication metadata

Author(s): Al-Rubaye GA, Tsimenidis CC, Johnston M

Publication type: Article

Publication status: Published

Journal: IET Communications

Year: 2017

Volume: 11

Issue: 16

Pages: 2425-2432

Print publication date: 11/09/2017

Online publication date: 07/08/2017

Acceptance date: 25/07/2017

Date deposited: 08/08/2017

ISSN (print): 1751-8628

ISSN (electronic): 1751-8636

Publisher: IET


DOI: 10.1049/iet-com.2017.0265


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