Title: Neuro-fuzzy selection algorithm for optimal relaying in OFDM systems

Authors: M.S. Kaiser; K.M. Ahmed

Addresses: Institute of Information Technology, Jahangirnagar University, Savar, Dhaka, Bangladesh ' Telecommunication FoS, School of Engineering and Technology, Asian Institute of Technology, Thailand

Abstract: Next generation wireless networks will support cooperative communication, where relay nodes receive transmission from a source node and forward it to its destination node. The best relay selection is one of the key concerns to improve the overall performance of the cooperative networks. This paper presents a neuro-fuzzy (NF) selection algorithm for optimal relaying in OFDM-based cooperative networks. The aim is to select relay(s) based on instantaneous signal-to-noise ratio (SNR), link delay (propagation and queuing delay) and energy saving due to the cooperative diversity. This paper also provides the end-to-end outage probability analysis. The NF-based relay selection algorithm is compared with the blind search, informed search, fuzzy-based search and selection amplify-and-forward (AF) with power allocation algorithms. The simulation results and complexity analysis show that the proposed algorithm provides substantial performance improvement over the conventional algorithms.

Keywords: neuro-fuzzy; NF; learning algorithm; link delay: energy efficiency; cooperative network.

DOI: 10.1504/IJAACS.2017.10005570

International Journal of Autonomous and Adaptive Communications Systems, 2017 Vol.10 No.2, pp.213 - 235

Received: 03 Jun 2014
Accepted: 12 Oct 2014

Published online: 22 Jun 2017 *

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