1 Abstract — In this paper, an energy-efficient scheme is proposed for cooperative spectrum sensing in cognitive sensor networks. In our scheme, we introduce a technique to select the sensing nodes and to set energy detection threshold so that energy saving can be accomplished in the nodes. Our objective is to minimize the energy consumed in distributed sensing subject to constraints on global probability of detection and probability of false alarm by determining the detection threshold and selection of the sensing nodes. The energy detector is applied to detect the primary user activity for the sake of simplicity. At first, it is assumed that the instantaneous SNR for each node is known. Then, the optimal conditions are obtained and a closed- form equation is expressed to determine the priority of nodes for spectrum sensing and also the optimum detection threshold. This problem is also solved when the average SNRs of sensors are available according to real situations. To achieve more energy saving, the problem of joint sensing node selection, detection threshold and the decision node selection (DN) is analyzed and an efficient solution is extracted based on the convex optimization framework. Simulation results show that the proposed algorithms lead to significant energy saving in cognitive sensor networks. Index Terms— Cognitive wireless sensor networks, detection probability and false alarm probability, cooperative spectrum sensing, detection threshold. I. INTRODUCTION IVEN the limitations of the natural frequency spectrum, it becomes obvious that the current static frequency allocation schemes cannot accommodate the requirements of an increasing number of higher data rate devices. As a result, innovative techniques that can offer new ways of exploiting the available spectrum are needed. Cognitive radio arises to be Manuscript received… Copyright (c) 2013 IEEE. Personal use of this material is permitted. However, permission to use this material for any other purposes must be obtained from the IEEE by sending a request to pubs-permissions@ieee.org. M. Najimi is with the Faculty of Electrical Engineering, Mazandaran University of Science & Technology (e-mail: Maryam_najimi1361@yahoo.com). A. Ebrahimzadeh and S.M.Hosseini are with the Faculty of Electrical & Computer Engineering, Babol University of Technology (e-mail:; e_zadeh@nit.ac.ir ; smh_andargoli@nit.ac.ir). A. Fallahi is with RighTel, Tehran, Iran (e-mail: a.fallahi@rightel.ir). a tempting solution to the spectral congestion problem by introducing opportunistic usage of the frequency bands that are not heavily occupied by licensed users [1]. Hence, one of the main aspects of cognitive radio is related to autonomously exploiting locally unused spectrum (spectrum holes) to provide new paths to spectrum access. In cognitive radio terminology, primary users can be defined as the users who have higher priority or legacy rights to the usage of a specific part of the spectrum. On the other hand, secondary users, who have lower priority, exploit this spectrum in such a way that they do not cause interference to primary users. Therefore, secondary users need to have cognitive radio capabilities, such as sensing the spectrum reliably to check whether it is being used by a primary user and changing the radio parameters to exploit the unused part of the spectrum. Spectrum sensing has very important role in cognitive radio networks. On the other hand, the status of the activity of the primary user is determined by spectrum sensing. In fact, spectrum sensing is employed to identify the spectrum holes. However, a secondary user may declare a spectrum hole when it has been already occupied by a primary user, that is called missing detection. Alternatively, it may confirm the presence of a primary transmission when the spectrum is not actually in use that is referred to as false alarm. The attenuation caused to the signal due to shadowing, fading or other impairments can lead to erroneous detection of the primary user signal by a single detector. It is believed that deploying multiple cognitive sensors for sensing the spectrum can result in improving the detection of primary signals [2], [3]. The method and the algorithms employing this strategy are referred to as cooperative spectrum sensing. Cooperative spectrum sensing can be done by cognitive sensor networks, such that the sensors reports their result to the Fusion Center (FC) to make a final decision about the activity of the primary user and therefore the available channels (spectrum holes) are reported to other cognitive radio networks. In this case, the sensor network acts as an advisor network which provides primary user activities information for cognitive radio networks. In cognitive sensor networks, it is also possible that the provided information through cooperative spectrum sensing is used for assigning idle channels to available sensors in the network. However, this will result in a trade-off between the sensors’ throughput and sensing accuracy. In [4] the authors studied the cooperative Sensor Selection and Optimal Energy Detection Threshold for Efficient Cooperative Spectrum Sensing Ataollah Ebrahimzadeh, Maryam Najimi, Seyed Mehdi Hosseini Andargoli and Afshin Fallahi G This is the author's version of an article that has been published in this journal. Changes were made to this version by the publisher prior to publication. The final version of record is available at http://dx.doi.org/10.1109/TVT.2014.2331681 Copyright (c) 2014 IEEE. Personal use is permitted. For any other purposes, permission must be obtained from the IEEE by emailing pubs-permissions@ieee.org.