Channel allocation scheme for cellular networks using evolutionary computing. (1st January 2014)

• Record Type: Journal Article
• Authors: Rajagopalan, Narendran; Mala, C.
• Is Part Of: International journal of artificial intelligence and soft computing. Volume 4:Number 2/3(2014)
• Page Start: 212
• Page End: 227
• Publication Date: 2014-01-01
• Subjects: genetic algorithm -- channel allocation -- quality of service -- QoS -- artificial neural network -- ANN -- throughput; Artificial intelligence -- Periodicals; Soft computing -- Periodicals; 006.305
• Languages: English
• ISSNs: 1755-4950

Abstract

The usage of mobile communications systems has grown exponentially. But, the bandwidth available for mobile communications is finite. Hence, there is a desperate attempt to optimise the channel assignment schemes. In this work, some of the quality of service parameters such as residual bandwidth, number of users, duration of calls, frequency of calls, priority, time of calls and mean opinion score are considered. Genetic algorithm and artificial neural networks is used to determine the optimal channel assignment considering the quality of service parameters. The simulation results show that genetic algorithm performs better than frequency assignment at random, a heuristic method. But application of artificial neural networks outperforms genetic algorithm and frequency assignment at random method by a considerable margin. Channel allocation can be optimised using these soft computing techniques resulting in better throughput.