Dynamic Spectrum Tracking through Quickest Detection Techniques: A Clustered Approach

Abstract

Cognitive radio technology addresses the issue of spectrum scarcity and underutilization by using spectrum sensing to exploit the absence of the primary user. Sensing improvement of the secondary network can be measured by how quickly the absence or presence of a PU is determined. Delay in detection of a PU appearance causes harmful interference with the PU, whereas delay in detection of a PU disappearance reduces the spectrum access opportunity for secondary users. Thus, to achieve the quickest detection of PU appearances and disappearances, we propose a double-sided cumulative sum (DoSCuS) algorithm in a cluster-based cognitive radio network. At the SU level, the DoSCuS algorithm is used to promptly detect appearances and disappearances. At the cluster level, we propose the one-slot history (OSH)-based algorithm to maintain the history for each SU in order to consider only the SUs that observe a change in their adjacent timeslots. At the fusion center (FC), a global decision is made using a weighted decision fusion rule. By exploiting the advantages of the DoSCuS algorithm with the clustered base approach, the proposed scheme detects the status of the PU with minimum delay. The effectiveness of the proposed scheme is shown through simulations and comparisons to the conventional scheme.