Traffic Pattern Based Adaptive Spectrum Handoff Strategy for Cognitive Radio Networks

Abstract

Increase in number of commodity devices using network connection raised the spectrum demand largely. The present static spectrum allocation policy gave birth to the so called spectrum scarcity problem. Cognitive Radio enhances the bandwidth usage through Dynamic Spectrum Access without affecting the allocated spectrum, therefore offers a feasible solution to the problem of spectrum scarcity. Enhancing the spectrum usage efficiently, cognitive radio technology allows secondary users to acquire underutilized licensed spectrum band. Smooth spectrum mobility in cognitive radio networks is extremely necessary to ensure the continuity and quality of service. This work aims to develop a dynamic horizontal handoff strategy that adopts according to the traffic pattern of PU. Proposed model keeps track of mobility patterns on certain primary spectrum and classifies these spectrum channels based on primary user's arrival on them. Handoff strategy decision is based on these classified patterns, which can be either proactive or reactive strategy. Analytical results demonstrate that proposed model optimizes channel utilization, minimize handoff delays while maximizing overall network capacity.