Probabilistic Approach for Channel Selection in Centralized Cognitive Scheme Utilizing Invasive Weed Optimization

Abstract

Devices of cognitive Radio (CR) help Secondary Users (SU) to locate a vacant channel licensed to Primary Users (PU). SU vacates the channel by doing a handoff on condition when PU enters that channel. Now SU seeks a different channel to proceed further. This paper narrates an algorithm of an evolutionary type called Invasive Weed Optimization (IWO) that solves the issue of Spectrum Handoff (SHO). The fixed and Probabilistic method of hybrid spectrum handoff utilizes the algorithm of IWO. The prime limitation of SUs' prolonging the time in data delivery gets minimal by optimizing the period in the network of CR. The centralized Cognitive Device (CCD) is minimizing delay in handoff, monitoring the balancing of the load as well as improving efficiency. The proposed method is verified and validated with the existing Genetic algorithm (GA) and Particle Swarm Optimization (PSO) methods. Apart from that the pre-emptive resume priority MG/1 model for queuing too is employed. This leads the IWO method's accuracy of channel selection to an improvement of 97.6%. There is a greater reduction in handoff delay. This excels in the schemes of traditional type in practice now.