DocumentCode
771043
Title
Channel assignment using genetic algorithm based on geometric symmetry
Author
Ghosh, Sasthi C. ; Sinha, Bhabani P. ; Das, Nabanita
Author_Institution
Adv. Comput. & Microelectron. Unit, Indian Stat. Inst., Kolkata, India
Volume
52
Issue
4
fYear
2003
fDate
7/1/2003 12:00:00 AM
Firstpage
860
Lastpage
875
Abstract
The paper deals with the channel assignment problem in a hexagonal cellular network with two-band buffering, where channel interference does not extend beyond two cells. Here, for cellular networks with homogeneous demands, we find some lower bounds on the minimum bandwidth required for various relative values of s0, s1, and s2, the minimum frequency separations to avoid interference for calls in the same cell, or in cells at distances of one and two, respectively. We then present an algorithm for solving the channel assignment problem in its general form using the elitist model of genetic algorithm (EGA). We next apply this technique to the special case of hexagonal cellular networks with two-band buffering. For homogeneous demands, we apply EGA for assigning channels to a small subset of nodes and then extend it for the entire cellular network, which ensures faster convergence. Moreover, we show that our approach is also applicable to cases of nonhomogeneous demands. Application of our proposed methodology to well-known benchmark problems generates optimal results within a reasonable computing time.
Keywords
adjacent channel interference; cellular radio; channel allocation; cochannel interference; frequency allocation; genetic algorithms; graph colouring; adjacent channel interference; benchmark problems; channel assignment; cochannel interference; computing time; cosite interference; elitist genetic algorithm model; frequency assignment; generalized graph-coloring problem; geometric symmetry; hexagonal cellular network; minimum bandwidth; minimum frequency separation; two-band buffering; Bandwidth; Convergence; Frequency conversion; Genetic algorithms; Interference constraints; Land mobile radio cellular systems; Microelectronics; NP-complete problem; Neural networks; Simulated annealing;
fLanguage
English
Journal_Title
Vehicular Technology, IEEE Transactions on
Publisher
ieee
ISSN
0018-9545
Type
jour
DOI
10.1109/TVT.2003.808806
Filename
1224545
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