Volume IV, Issue I, January 2015 IJLTEMAS ISSN 2278 - 2540 www.ijltemas.in Page 1 Spectrum Sensing Methods for Cognitive Radio Networks: A Review O. P. Meena*, Ajay Somkuwar Department of Electronics and Communication Engineering, Maulana Azad National Institute of Technology, Bhopal-462051, India Abstract— Dynamic spectrum sensing is a challenging and necessary task in Cognitive Radio Networks (CRN). It can detect presence of primary user (PU) who is having legacy right on licensed spectrum. Secondary User (SU) continuously or periodically senses the PU’s spectrum and when it finds the spectrum idle it starts transmitting its own data. When the SU detects presence of the PU in the spectrum it stops transmission or switches to another idle frequency spectrum. The SU must maintain its transmission parameters like power level, frequency band used for data transmission etc., in such a way that it must not cause any interference in PU’s transmission. The spectrum utilization efficiency and throughput performance of SUs depend on robustness and accuracy of spectrum sensing algorithms. Hence, in this paper a survey of spectrum sensing algorithms for Cognitive Radio (CR) is presented with their merits and limitations. To improve spectrum sensing performance and accuracy, some cooperative sensing techniques have been developed where many SUs share their detected information. The cooperative sensing techniques also reduce shadowing and fading effects on spectrum sensing. Keywords— Cognitive radio, spectrum sensing algorithms, cooperative spectrum sensing. I. INTRODUCTION he huge demand of frequency spectrum to support various types of real time and non-real time services using different type of technologies has created the scarcity of the frequency spectrum. To address the scarcity of frequency spectrum and to improve frequency spectrum utilization efficiency it has been proposed that unlicensed users (Secondary user/ Cognitive user) can be allowed to use the licensed frequency bands without affecting the communication performance of licensed user (Primary user) of the frequency band [1]. To improve the frequency spectrum utilization efficiency, In 1999, Mitola proposed the concept of Cognitive Radio which is also called as Software Defined Radio (SDR) [2]. A recent study by Federal Communication Commission (FCC) show that most of the fixed licensed spectrums are underutilized varies from 15 % to 85%, which is function of geographical and temporal dimensions [3]. The FCC recognized that there is significant amount of available spectrum that is currently not being used efficiently under the current fixed spectrum allocation policy. Therefore recently it has allowed the opportunistic access of the underutilized licensed spectrum to SUs [4]. The unused spectrum is often termed as ―white space‖ and has been the focus of the IEEE 802.22 WRAN standard that aims to provide broadband wireless internet access to rural areas. Hence in order to improve spectrum utilization efficiency and throughput of SUs, the robustness and accuracy of spectrum sensing methods are the key issues in CRN. The basics of spectrum sensing methods are surveyed in [5-7], which covers basics of energy detector, Cyclostationary feature detector, matched filter detector, Interference detector, cooperative detector etc. These methods are having their merits and limitations like, Energy detector is easy to implement but can’t distinguish between PU’s and SU’s signals. The Cyclostationary feature based detector need prior knowledge of cyclic frequencies of PU and SUs to distinguish them. A matched filter based detector is a coherent detector that also need prior knowledge of PU’s signal, like operating frequency, modulation etc. To address these limitations and improve detection probability some hybrid algorithms like Cyclo- energy detector [8] has been developed. To address the challenges posed by fading environment, hidden node, shadowing effect etc., centralized and distributed cooperative sensing algorithms have been proposed in [9-24]. A malicious SU may mislead a cooperative detector by hiding true information or sharing wrong information. So the possible attacks on Cooperative CRN and mitigating solutions [22] also have been surveyed in this paper. While several general and specific [5–7] reviews of the spectrum sensing methods and cooperative spectrum sensing literature exist; this paper is intended to provide the reader with a generic and comprehensive view of spectrum sensing techniques, as well as the most recent developments and emerging trends in the field. II. SPECTRUM SENSING FRAMEWORK In CRN the SUs can access the licensed spectrum using two main approaches: (i) the SUs are allowed to access a frequency band only when it is detected idle, and (ii) the SUs coexist with the PUs under the condition of protecting the latter from harmful interference. A. Conventional spectrum sensing Architecture: The CR system divides a frame into sensing (quiet time) and data transmission time slots as shown in Fig. 1. In sensing period SUs sense presence of PU’ signal and start data transmission when they finds the spectrum idle. When the SUs detect presence of the PU in the spectrum they stop T