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Comparison of two novel heuristic dynamic channel allocation techniques in cellular systems
Author(s) -
Sandalidis Harilaos G.,
Stavroulakis Peter P.,
RodriguezTellez Joe
Publication year - 1998
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/(sici)1099-1131(199811/12)11:6<379::aid-dac379>3.0.co;2-1
Subject(s) - computer science , heuristic , mathematical optimization , resource allocation , scheme (mathematics) , field (mathematics) , computation , genetic algorithm , channel (broadcasting) , channel allocation schemes , distributed computing , algorithm , artificial intelligence , computer network , telecommunications , machine learning , mathematics , wireless , mathematical analysis , pure mathematics
Dynamic channel assignment (DCA) has been discussed in the literature as a way to achieve improved resource management in cellular networks. In the simplest dynamic allocation scheme, all channels are kept in a central pool and are used on a call‐by‐call basis. DCA is therefore a complex real time operation and various heuristic methods have been devised as mechanisms to give a fast and reliable solution to this problem. This paper examines the implementation of a DCA model using two approaches from the field of evolutionary computation. The first is the so called genetic algorithm (GA) and the second is the combinatorial evolution strategy (CES). Computer simulations evaluate and compare these proposed heuristic DCA schemes concerning their application to a cellular model for both uniform and non‐uniform traffic load conditions. © 1998 John Wiley & Sons, Ltd.