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Coded Full-Duplex MIMO with Iterative Detection and Decoding

Lookup NU author(s): Mohamad Ahmed, Dr Charalampos Tsimenidis

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Abstract

© 2015 IEEE.In this paper, we investigate the performance of a coded full-duplex multiple-input multiple-output (FD-MIMO) bi-directional transceiver. To mitigate self-interference (SI), iterative detection and decoding (IDD) are proposed that utilize soft parallel interference cancellation (SPIC) with adaptive Minimum Mean-Squared-Error (MMSE) filtering. Furthermore, Space-Time Bit-Interleaved Coded Modulation (ST-BICM) based channel coding schemes are considered, i.e. convolutional or turbo code based, and the system performance is evaluated in the presence of additive white Gaussian noise (AWGN) over MIMO Rayleigh fading channels. The proposed near-optimal IDD scheme performs cancellation of SI by iteratively exchanging the soft information of the desired and SI signals between the detector, which comprises adaptive MMSE filtering with log-likelihood ratio (LLR) demapping, and the soft-in soft-out (SISO) decoder implementing linear to logarithmic approximation of the maximum a posteriori algorithm. Performance results are presented to demonstrate the Bit-Error-Rate (BER) performance of the proposed coded FD-MIMO as a function of the signal to noise ratio (SNR). Furthermore, a comparison of the proposed IDD system with relevant state-of-the-art approaches is given which shows a significant improvement in performance as a result of the introduced iterative processing that reduces SI considerably.


Publication metadata

Author(s): Ahmed MA, Tsimenidis CC

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: IEEE International Conference on Communications 2015

Year of Conference: 2015

Pages: 4859-4864

Online publication date: 10/09/2015

Acceptance date: 01/01/1900

Publisher: Institute of Electrical and Electronics Engineers Inc.

URL: http://doi.org/10.1109/ICC.2015.7249092

DOI: 10.1109/ICC.2015.7249092

Library holdings: Search Newcastle University Library for this item

ISBN: 9781467364324


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