Neuro-fuzzy based joint relay-selection and resource-allocation for cooperative networks

This article was published in Transactions on Electrical Engineering, Electronics, and Communications [© 2011] The Journal's website is at: http://www.ecti-thailand.org/assets/papers/1096_pub_34.pdf

Bibliografiset tiedot
Päätekijät: Kaiser, M. Shamim, Shah, Raza Ali, Ahmed, Kazi M.
Muut tekijät: Department of Mathematics and Natural Sciences, BRAC University
Aineistotyyppi: Artikkeli
Kieli:English
Julkaistu: © 2011 Transactions on Electrical Engineering, Electronics, and Communications 2016
Aiheet:
Linkit:http://hdl.handle.net/10361/7079
id 10361-7079
record_format dspace
spelling 10361-70792016-12-01T10:34:53Z Neuro-fuzzy based joint relay-selection and resource-allocation for cooperative networks Kaiser, M. Shamim Shah, Raza Ali Ahmed, Kazi M. Department of Mathematics and Natural Sciences, BRAC University Mamdani-adaptiveneuro-fuzzy inference system Ofdma Outage probability Relay selection Resource allocation This article was published in Transactions on Electrical Engineering, Electronics, and Communications [© 2011] The Journal's website is at: http://www.ecti-thailand.org/assets/papers/1096_pub_34.pdf This paper focuses on a joint relay-selection and resource-allocation algorithm for an Amplify-and-Forward (AF) cooperative network. In a multiuser scenario, joint relay selection and power allocation is a combinational problem for heterogeneous, i.e., real time (RT) and non-real time (NRT), users. In single relay AF (S-AF) scheme, a source-destination pair selects best relay. Thus only two channels are needed (i.e., one for source-destination direct link and other one for the source-relay-destination indirect link) between a source-destination pair. We propose a NeuroFuzzy (NF) based optimal relay selection algorithm for selecting best relay based on link's signal-to-noise ratio (SNR), link's delay and degree of mobility between a source-destination pair. The available radio resources are then allocated sub-optimally to the RT and NRT users on priority basis. The priority parameter depends on Quality-of-service (QoS) requirement of the RT and NRT users. We deduce a close form expression of the moment-generating-function (MGF) for independent and non identical Rayleigh fading channels. Performance evaluations reveal that the proposed joint scheme has lower complexity and better outage behavior as compared to the conventional schemes. Published 2016-12-01T10:32:47Z 2016-12-01T10:32:47Z 2011-02 Article Shamim Kaiser, M., Shah, R. A., & Ahmed, K. M. (2011). Neuro-fuzzy based joint relay-selection and resource-allocation for cooperative networks. Transactions on Electrical Engineering, Electronics, and Communications, 9(1), 187-194. 16859545 http://hdl.handle.net/10361/7079 en http://www.ecti-thailand.org/assets/papers/1096_pub_34.pdf © 2011 Transactions on Electrical Engineering, Electronics, and Communications
institution Brac University
collection Institutional Repository
language English
topic Mamdani-adaptiveneuro-fuzzy inference system
Ofdma
Outage probability
Relay selection
Resource allocation
spellingShingle Mamdani-adaptiveneuro-fuzzy inference system
Ofdma
Outage probability
Relay selection
Resource allocation
Kaiser, M. Shamim
Shah, Raza Ali
Ahmed, Kazi M.
Neuro-fuzzy based joint relay-selection and resource-allocation for cooperative networks
description This article was published in Transactions on Electrical Engineering, Electronics, and Communications [© 2011] The Journal's website is at: http://www.ecti-thailand.org/assets/papers/1096_pub_34.pdf
author2 Department of Mathematics and Natural Sciences, BRAC University
author_facet Department of Mathematics and Natural Sciences, BRAC University
Kaiser, M. Shamim
Shah, Raza Ali
Ahmed, Kazi M.
format Article
author Kaiser, M. Shamim
Shah, Raza Ali
Ahmed, Kazi M.
author_sort Kaiser, M. Shamim
title Neuro-fuzzy based joint relay-selection and resource-allocation for cooperative networks
title_short Neuro-fuzzy based joint relay-selection and resource-allocation for cooperative networks
title_full Neuro-fuzzy based joint relay-selection and resource-allocation for cooperative networks
title_fullStr Neuro-fuzzy based joint relay-selection and resource-allocation for cooperative networks
title_full_unstemmed Neuro-fuzzy based joint relay-selection and resource-allocation for cooperative networks
title_sort neuro-fuzzy based joint relay-selection and resource-allocation for cooperative networks
publisher © 2011 Transactions on Electrical Engineering, Electronics, and Communications
publishDate 2016
url http://hdl.handle.net/10361/7079
work_keys_str_mv AT kaisermshamim neurofuzzybasedjointrelayselectionandresourceallocationforcooperativenetworks
AT shahrazaali neurofuzzybasedjointrelayselectionandresourceallocationforcooperativenetworks
AT ahmedkazim neurofuzzybasedjointrelayselectionandresourceallocationforcooperativenetworks
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