Title: Particle swarm optimisation-based DWT for symbol detection in MIMO-OFDM system

Authors: Asma Bouhlel; Anis Sakly; Mohamed Nejib Mansouri

Addresses: Laboratory of Electronic and Microelectronic, Faculty of Sciences Monastir, University of Monastir, Tunisia ' Industrial Systems study and Renewable Energy (ESIER), National Engineering School of Monastir, University of Monastir, Tunisia ' Laboratory of Electronic and Microelectronic, Faculty of Sciences Monastir, University of Monastir, Tunisia

Abstract: This paper proposes a new detection algorithm called particular swarm optimisation (PSO)-based discrete wavelet transform (DWT) for multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system. In all previous studies, PSO detection algorithm and DWT were separately proposed for MIMO-OFDM systems. Motivated by the performances enhancement achieved by these techniques, PSO is combined to DWT transform in this work for symbol detection in MIMO-OFDM system. The simulation results show that the proposed PSO-based DWT MIMO-OFDM system boosts the performances of zeros forcing (ZF), minimum mean square error (MMSE), and even PSO-based FFT MIMO-OFDM equaliser. The proposed detector presents near optimal performances in terms of bit error rate (BER) and a significant computational complexity reduction for different constellation diagram and number of transmitting antennas compared to maximum likelihood (ML) detector.

Keywords: multiple-input-multiple-output orthogonal frequency division multiplexing; MIMO-OFDM; discrete wavelet transform; DWT; particular swarm optimisation; PSO; maximum likelihood; ML.

DOI: 10.1504/IJNVO.2018.091581

International Journal of Networking and Virtual Organisations, 2018 Vol.18 No.2, pp.130 - 143

Received: 03 Aug 2016
Accepted: 01 Feb 2017
Published online: 08 May 2018 *

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