Communication-Efficient Decentralized Change Detection for Cognitive Wireless Networks

Abstract

Spectrum sensing constitutes a key functionality of a cognitive radio (CR), and sensing devices are required to detect a change in spectrum occupancy as quickly as possible. A new decentralized change detection framework is developed for cognitive wireless networks, where local sensors are memoryless, receive independent observations, and no feedback from the fusion center. In addition to traditional criteria of detection delay and false alarm rate, we introduce a new constraint: the number of communications between local sensors and the fusion center. This communication metric is able to reflect both the cost of establishing communication links as well as overall energy consumption over time. The proposed detection scheme minimizes detection delay with constraints on both false alarm rate and number of communications. Simulation results are investigated to explore the tradeoffs in parameter choices of the proposed algorithm.