Modelling of Spectrum Handover Scheme using Particle Swarm Intelligence in Cognitive-radio Networks
Meha Bansal1, Roopali Garg2
1Meha Bansal, Research Scholar, IT-Department, UIET-PU, Chandigarh, India.
2Dr. Roopali Garg, Associate Professor, IT-Department, UIET-PU, Chandigarh, India.
Manuscript received on 03 March 2019 | Revised Manuscript received on 09 March 2019 | Manuscript published on 30 July 2019 | PP: 3331-3336 | Volume-8 Issue-2, July 2019 | Retrieval Number: B2312078219/19©BEIESP | DOI: 10.35940/ijrte.B2312.078219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Cognitive-radio is a self-adaptive network technology, which helps in detecting idle channels within a spectrum range. Cognitive radio has four functionalities namely Spectrum sensing, decision, sharing and mobility. This research work is in the domain of spectrum mobility. Spectrum mobility deals with motion of unlicensed users in the network. Unlicensed users are the unauthorized users of cognitive radio networks who have lower priority than licensed ones. Major functionality of spectrum mobility is spectrum handover and connection management. In cognitive-radio, the method of switching channels is termed as spectrum handover. Whenever a high priority user appears to occupy its spectrum band, that is already been utilized by a low priority user, spectrum handover takes place. During this process, a lot of handover delay occurs, which results in increasing the total service time of transmission. Total service time of spectrum handover means amount of time required to perform successful handover during spectrum mobility stage in cognitive-radio-networks. To decrease this total service time of spectrum handover we have utilized the concept of Particle Swarm Intelligence and M/G/1 queuing model. The parameters used for the purpose are swarm size, arrival rate, service rate, acceleration coefficients, processing time and channel switching time. Swarm size indicates the number of particles present in a swarm. In this research work, value of swarm size is varied to see its effect on total service time of spectrum handover process. Numerical results demonstrate that by increasing the value of swarm size, total service time decreases.
Index Terms: Arrival Rate, Primary User, Secondary User, Service Rate, Swarm Size
Scope of the Article: Network Modelling and Simulation