Cognitive Radio and Its Impact of Throughput with Channel Optimization Techniques
B. Suseela, D. Sivakumar · Journal of Computational and Theoretical Nanoscience · 2017
Spectrum scarcity has gained a great challenge in the current scenarios of wireless communication. In order to optimize the spectrum usage on the other hand cognitive networks has shown a considerable growth. This paper tries to focus on optimization with particle swarm optimization in cognitive networks (PSO-CN) and tree seed algorithm in cognitive networks (TSA-CN) which are multichannel based. The algorithm is based on higher probability of detection and throughput with lower probability of false alarm. The lower probability of false alarm has been achieved without compromising on the transmission rate with TSA-CN. The convergence time is found to be quicker with TSA-CN. Results with matlab based simulator shows there is an increase in throughput and decrease in false alarm with TSA algorithm than the PSO algorithm.