Genetic Algorithms and Fuzzy Logic For Dynamic Channel Allocation in Cellular Radio Networks

Author

An, J. ; Hines, E.L. ; Leeson, M.S. ; Sun, L. ; Ren, W. ; Iliescu, D.D.

Author_Institution

Sch. of Eng., Warwick Univ.

fYear

2007

fDate

9-11 Jan. 2007

Firstpage

19

Lastpage

22

Abstract

An integrated artificial intelligence optimised cellular radio channel allocation and call dropping algorithm is presented. The components of the system comprise a new genetic algorithm (GA) based channel allocation scheme, and a novel application of fuzzy logic to call dropping technique. The new method is compared to both random allocation and to a conventional allocation approach. The results show improvements of 30% in the signal-to-interference ratio and 10% in the uniformity of the traffic across the cells in the system. Furthermore, up to 80% fewer calls are dropped using the new methodology

Keywords

cellular radio; channel allocation; fuzzy logic; genetic algorithms; telecommunication traffic; call dropping algorithm; cellular radio channel allocation; cellular radio networks; dynamic channel allocation; fuzzy logic; genetic algorithms; integrated artificial intelligence optimised channel allocation; random allocation; signal-to-interference ratio; traffic uniformity; Channel allocation; Frequency; Fuzzy logic; Genetic algorithms; Genetic engineering; Interference constraints; Land mobile radio cellular systems; Quality of service; Radio spectrum management; Sun; Mobile communication; fuzzy logic; genetic algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Radio and Wireless Symposium, 2007 IEEE

Conference_Location

Long Beach, CA

Print_ISBN

1-4244-0444-4

Electronic_ISBN

1-4244-0445-2

Type

conf

DOI

10.1109/RWS.2007.351779

Filename

4160639