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Stochastic learning automata‐based channel selection in cognitive radio/dynamic spectrum access for WiMAX networks
Author(s) -
Misra Sudip,
Chatterjee Shankha Subhra,
Guizani Mohsen
Publication year - 2014
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.2704
Subject(s) - computer science , cognitive radio , learning automata , wimax , channel (broadcasting) , computer network , bandwidth (computing) , channel allocation schemes , transmission (telecommunications) , spectrum management , frequency band , telecommunications , automaton , wireless , theoretical computer science
Summary This paper proposes a cognitive radio‐based dynamic bandwidth allocation scheme for secondary users in a cluster‐based WiMAX network. It uses a learning automata‐based algorithm to find the optimal transmission channel, while ensuring minimum channel loss and a considerably high signal‐to‐noise ratio, and concurrently minimizing costly channel switching activities when primary users request licensed channels. The objective is to coordinate efficient frequency utilization and frequency reusability in each of the clusters in the network and to make data transmission possible without depleting the spectrum. The proposed scheme subsumes unforeseen channel faults into the channel feedback and decides the optimal channel. The system converges asymptotically to an ϵ ‐ optimal solution. Copyright © 2014 John Wiley & Sons, Ltd.