Interference Minimization for Hybrid Channel Allocation in Cellular Network with Swarm Intelligence

Abstract

In the wireless cellular networks in order to deal with irregular and expanding demand, channel must be allocated in such a way that spectrum is used efficiently, capacity is maximized with a minimum level of interference; this problem is called Channel/frequency Allocation Problem. The swarm intelligence category of Heuristic technique, i.e. Particle Swarm Optimization and Ant Colony Optimization for Hybrid Channel Allocation is investigated to find the optimal solution to the minimum interference. The fitness function designed is based on Graph Theory in PSO. The designing of fitness function is the probabilistic model with Sequential packing and ordering technique is explored with ACO. The interference level is represented by edges indicating co-channel and co-site. The signal to interference ratio is measured for Kunz benchmarks and the computation time is obtained. The performance of applied PSO and ACO is compared with the literature reported with Genetic algorithm (GA).