Performance Comparison of Cooperative and Distributed Spectrum Sensing in Cognitive Radio

Zheng SUN, Wenjun XU, Zhiqiang HE and Kai NIU School of Information Engineering, Beijing University of Posts and Telecommunications, Beijing, China zhengs.bupt@gmail.com

Abstract—In this paper, we compare the performances of cooperative and distributed spectrum sensing in wireless sensor networks. After introducing the basic problem, we describe two strategies: 1) a cooperative sensing strategy, which takes advantage of cooperation diversity gain to increase probability of detection and 2) a distributed sensing strategy, which by passing the results in an inter-node manner increases energy efficiency and fairness among nodes. Then, we compare the performances of the strategies in terms of three criteria: agility, energy efficiency, and robustness against SNR changes, and summarize the comparison. It shows that: 1) the non-cooperative strategy has the best fairness of energy consumption, 2) the cooperative strategy leads to the best agility, and 3) the distributed strategy leads to the lowest energy consumption and the best robustness against SNR changes.

Index Terms— cooperative sensing, distributed sensing, cognitive radio networks. I. INTRODUCTION Recently the field of cognitive radio (CR) has drawn great interest, since this novel technology provides promising solution to enhance the spectrum efficiency of today’s wireless network. Studies have shown that spectrum is extremely underutilized [1]. One way to increase the utilization is to design CR networks, where wireless equipments use smart radio to detect temporal and spatial “holes” in the spectrum, thus learn from the environment and perform further functions to serve the users. A significant feature of CR networks is to allow users to operate in licensed bands without a license. However, since CR has to limit its interference to the primary network, CR users using a licensed band must vacate the band due to the presence of the primary user. Thus it is significant to detect the presence of licensed (primary) users by spectrum sensing in a very short time. Recent work considers how to take advantage of the local oscillator leakage power emitted from RF receivers to allow cognitive radios to sense and locate the primary users [2]. Some physical layer issues of spectrum sensing are discussed in [3]. For radio sensitivity of the sensing function through processing gain, the authors of [4] study three digital signal processing techniques. In this paper, we are going to discuss how to deal with spectrum sensing in wireless sensor networks (WSN). Related work includes [2], which gives a physical layer and MAC layer solution of sensor nodes but lacks further designing on network architecture. Rather, we will discuss two strategies for efficient spectrum sensing in WSN. The first is cooperative sensing. Cooperative techniques are widely studied recently ([5]-[8]) to achieve a new form of spatial diversity via the cooperation of users [5]. In [6], the authors study two-user cooperative spectrum sensing in cognitive radio and show that, by allowing the cognitive users operating in the same band to cooperate, the detection time reduces and thus the overall agility increases. In [7], light-weight cooperation in sensing based on hard decision is proposed to mitigate the sensitivity requirements on individual radios. And in [8], the cooperative situations are considered by using game theory, and the authors show how the lack of cooperation affects the performance. In this paper, the cooperative sensing is described in a multi-node WSN network, in which multi-user diversity gain is further achieved. The second strategy being discussed is distributed spectrum sensing, which is specialized from distributed learning and estimation theory [10]. To our best knowledge, distributed spectrum sensing is a rather fresh topic. The reason of adopting distributed spectrum sensing in WSN is twofold. Firstly, traditional cooperation in WSN needs node fusion center transmissions with length of → ( )1 O , while distributed sensing strategy adopts inter-node transmissions with length of only ( ) 2 log n n O [9], which therefore reduces energy costs and increases overall network longevity. Secondly, in this paper we show that by using distributed sensing strategy, the probability of detection at the fusion center is greatly increased comparing with both non-cooperative and cooperative sensing strategy.
The main purpose of this paper is to present strategies of cooperative and distributed spectrum sensing in WSN, and to compare their performances in terms of agility, energy efficiency, and robustness against SNR changes. The results drawn here may act as a reference for further researches. The rest of the paper is organized as follows. In Section II, we describe the basic problem and a non-cooperative spec

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