NDLI: Bee colony optimization aided adaptive resource allocation in OFDMA systems with proportional rate constraints

Content Provider	Springer Nature Link
Author	Sharma, Nitin Anpalagan, Alagan
Copyright Year	2014
Abstract	Orthogonal frequency division multiple access (OFDMA) is a promising technique, which can provide high downlink capacity for the emerging wireless systems. The total capacity of OFDMA can be maximized by adaptively assigning subcarriers to the users with the best gains for those subcarriers, with power subsequently distributed by water-filling. In this paper, we propose the use of artificial bee colony (ABC) algorithm combined with Deb’s selection mechanism to handle the constraints. In this scheme, a probabilistic selection scheme assigns probability values to feasible solutions based on their fitness values and to infeasible individuals based on their violations, to allocate the resources to the users in downlink OFDMA system. Specifically we propose two approaches for resource allocation in downlink OFDMA systems using ABC algorithm. In the first approach, ABC algorithm is used for subcarrier allocation only, while in second approach the ABC algorithm is used for joint subcarrier and power allocation. It is shown that both these approaches obtain higher sum capacities as compared to that obtained by previous works, with comparable computational complexity. It is also shown that the joint subcarrier and power allocation approach provides near optimal results at the cost of slightly higher computational cost.
Starting Page	1699
Ending Page	1713
Page Count	15
File Format	PDF
ISSN	10220038
Journal	Wireless Networks
Volume Number	20
Issue Number	7
e-ISSN	15728196
Language	English
Publisher	Springer US
Publisher Date	2014-02-21
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Orthogonal frequency division multiple access Bee colony optimization Resource allocation Sum capacity Computational complexity Communications Engineering, Networks Computer Communication Networks Electrical Engineering Business Information Systems
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Information Systems Electrical and Electronic Engineering

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