Frequency planning of clustered cellular network using Particle Swarm Optimization

In the field of wireless communication, although significant work has been done for improving the cellular systems, however the issue of optimized bandwidth allocation and mitigation of inter-cell interference remains a challenge. To solve this problem, evolutionary algorithm Particle Swarm optimization´ (PSO) is considered. The distributed clustered cellular networks with clusters having local macrodiversity are considered and the effect of frequency planning by Particle Swarm Optimization is analyzed by observing the sum rate. The reason of considering PSO is its simple computational nature and property of quick convergence towards optimal solution. Here, PSO for discrete search space is implemented for frequency allocation, the iterative updates are performed to get optimized frequency allocation. The results of frequency allocation by PSO have shown considerable improvement in system sum rate capacity in comparison to some of the conventional allocation schemes.