College of Engineering

Title of the Seminar: AN IMPROVED PARTICLE SWARM OPTIMIZATION ALGORITHM FOR

SPECTRUM ALLOCATION IN COGNITIVE RADIO NETWORKS

Objectives or Summary:

The seriousness of the spectrum scarcity has increased dramatically due to the rapid

increase of wireless services. The key enabling technology that can be viewed as a novel

approach for utilizing the spectrum more efficiently is known as Cognitive Radio.

Therefore, assigning the spectrum opportunistically to the unlicensed users without

interfering with the licensed users, concurrently with maximizing the spectrum utilization

is addressed as a major challenge problem in cognitive radio networks. In this paper, an

improved metaheuristic optimization algorithm has been proposed to solve this problem

that contingent on a graph coloring model. The proposed approach is a hybrid algorithm

composed of a Particle Swarm Optimization algorithm with Random Neighborhood

Search. The key objective function is maximizing the spectrum utilization in the cognitive

radio networks with the subjected constraints. MATLAB R2021a was used for conducting

the simulation. The proposed hybrid algorithm improved the system utilization by 1.23%

compared to Particle Swarm Optimization algorithm, 5.57% compared to Random

Neighborhood Search, 7.9% compared to Color Sensitive Graph Coloring algorithm, and

27.33% compared to Greedy algorithm. Moreover, the system performance was evaluated

with various deployment scenarios of the primary users, secondary users, and channels for

investigating the impact of varying these parameters on the system performance.

This is a seminar about our paper that was published at Science Journal of

University of Zakho July-Sept. 2023.

Place of the Seminar:

Seminar Hall – 3 rd Floor – Electrical and Computer Engineering Department –

College of Engineering