Energy-efficient spectrum sensing for cognitive sensor networks

Abstract

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. INTRODUCTIONThe 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 networks 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 developments 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

Overview of spectrum sensing for cognitive radio

“…In other words, the local decision is based on the locally collected energy Λ is the same for all radios, and the OR combining rule is used, [37] then gives expressions for the communication rate, and the global probabilities of false alarm and detection. In [38] and [39], the idea of [37] has been combined with sleeping and the global cost of sensing and transmission has been optimized w.r.t. the sleeping rate μ and the thresholds η e,2 , subject to a global probability of false alarm constraint P FA ≤ α and a global probability of detection constraint P D ≥ β.…”

“…Note that the considered global cost of sensing and transmission is now given by (18) multiplied by 1 − μ. The first interesting result from [38] and [39] is that the optimal lower threshold is again given by η (m) e,1 = 0 if the feasible set is not empty. In [38], it is assumed that the system is highly underutilized, i.e., Pr(H 0 )…”

“…Pr(H 1 )), whereas in [39], the more general case has been treated. Note that although [38] and [39] have considered the same thresholds η , sensing costs C s,m , and transmission costs C t,m are the same), it can be generalized to the case they are not the same.…”

“…Note that although [38] and [39] have considered the same thresholds η , sensing costs C s,m , and transmission costs C t,m are the same), it can be generalized to the case they are not the same. To conclude, the results show that the optimal sleeping rate and censoring probabilities grow with the number of cognitive radios, but the censoring probabilities saturate fairly rapidly.…”

Energy Efficient Spectrum Sensing and Accessing Scheme for Zigbee Cognitive Networks

“…In some cognitive systems, channel sharing is facilitated through periodic sensing [4]. For some system, their energy is critical in that cases it's not suitable to handoff frequently and some time the secondary user choose to wait one the same channel and stop transmission at the cost of increased delay and reduced average throughput [5]. In this paper we propose hardware system with microcontroller, based on Arduino board as to control the spectrum sensing there after the switching of the channel using Zigbee modules in the ISM band and thus to design a system with very less energy consumption.…”