Energy-efficient spectrum sensing for cognitive sensor networks Sina Maleki † , Ashish Pandharipande ⋆ and Geert Leus † ⋆ Philips Research Europe - Eindhoven, High Tech Campus, 5656 AE Eindhoven, The Netherlands Email: ashish.p@philips.com † Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, The Netherlands Email: {s.maleki, g.j.t.leus}@tudelft.nl Abstract—We consider a combined sleeping and censoring scheme for energy-efficient spectrum sensing in cognitive sensor networks. We analyze the detection performance of this scheme by theoretically deriving the global probabilities of detection and false-alarm. Our goal is to minimize the energy consumption incurred in distributed sensing, given constraints on the global probabilities of detection and false-alarm, by optimally designing the sleeping rate and the censoring thresholds. Using specific transceiver models for sensors based on IEEE 802.15.4/ZigBee, we show the energy savings achieved under an optimum choice of the design parameters. I. I NTRODUCTION The family of wireless networks - sensor networks, personal area networks, local area networks, cellular networks etc has seen tremendous growth recently, resulting in demand for radio spectrum. Traditionally, radio spectrum allocation has been based on exclusive, licensed use of portions of spectrum to wireless systems. This has resulted in a perceived dearth of spectrum available for use for newer wireless net- works and applications. Radio spectrum measurements [13] however indicate that large portions of spectrum licensed to wireless systems remain under-utilized. Consequently there is a growing interest in unlicensed use of empty portions in order to improve spectrum utilization [3], [5], [17]. A promising approach for such secondary spectrum access is the use of cognitive radios. A cognitive radio can alter its radio transmission parameters autonomously based on active monitoring of spectrum in order to access spectrum on a secondary basis while coexisting with licensed systems or other unlicensed systems. In this paper, we consider a cognitive sensor network that performs spectrum sensing in order to determine empty radio channels and limits its transmissions on channels that are found vacant in order to reduce harmful interference to licensed systems. Our study is motivated by recent devel- opments in regulatory and standardization bodies aimed at permitting the use of portable devices and low-power sensors to operate on a secondary basis in VHF-UHF bands licensed to television broadcasting systems. In this context, reliable spectrum sensing that is energy efficient is critical. The cognitive sensor network comprises of a fusion center (FC) and a number of cognitive sensors that carry out sensing in dedicated, periodic sensing slots. Channel sensing is done using energy detection, which is a common approach to the detection of unknown signals [3], [8]. The results of the sensing are collected at a fusion center that makes a global decision using an OR fusion rule on the occupancy of the channel. Distributed spectrum sensing aims at exploiting the inherent spatial diversity to alleviate local shadowing condi- tions that may result in unreliable detection at an individual cognitive sensor. Distributed spectrum sensing schemes based on soft and hard fusion have been considered in the past [10] (the reader is also referred to literature in distributed detection [14]). Although the global detection performance improves, so does the energy consumption in the cognitive sensor network. There is considerable literature on different distributed spectrum sensing schemes and their performance, limited attention has however been paid to schemes that are energy-efficient. A clustering-based approach to energy- efficient distributed sensing was proposed in [9]. However this approach is only suitable for tree-structured cognitive sensor networks. We propose a combination of sleeping and censoring as an energy saving mechanism in spectrum sensing. When in sleep mode, a cognitive sensor switches off its sensing transceiver and incurs no observation costs or transmission costs. Cen- soring involves transmitting detection results only when they are in a certain information region. Our goal is to minimize the average energy incurred by the cognitive sensor network to perform spectrum sensing while maintaining a global detection performance by determining the optimum sleeping rate and censoring region. The constraint on detection performance is specified by a minimum target probability of detection and a maximum permissible probability of false-alarm. We first provide a theoretical framework to analyze the combined sleeping and censoring scheme and obtain the optimum design parameters. We then consider a sensor network based on IEEE 802.15.4/ZigBee radios to validate the theoretical analysis. Simulation results show orders of magnitude in energy savings in comparison to traditional spectrum sensing schemes. In the context of wireless sensor networks, sleeping and censoring schemes have been individually shown as effective ways to achieve energy efficiency, with the exception of [16].