1 Abstract— Spectrum scarcity is considered an impediment to the growth of wireless technologies. However, studies reveal a significant underutilization of the frequency spectrum apportioned to licensed users. An intelligent radio technology platform, termed Cognitive Radio was conceived to solve this imminent challenge by shifting the paradigm of a static spectrum allocation policy to that of dynamic (opportunistic) spectrum access. A foremost part of this technology is spectrum sensing. Among the methods espoused, Energy Detection possesses an advantage of low implementation and low computational complexity; compared to the other methods that require prior information and specific features of the signal to be detected. This study evaluates the performance of the energy detection based spectrum sensing technique in noisy and fading environments. Both single user detection and cooperative detection situations were investigated. Closed form solutions for the probabilities of detection and false alarm were derived. Analytical results were verified by numerical computations using Monte Carlo method in MATLAB. The performance of the energy detection technique was evaluated by use of Receiver Operating Characteristics (ROC) curves over AWGN and fading (Rayleigh & Nakagami-m) channels. Results show that for both single user detection and cooperative detection, the energy detection technique performs better in AWGN than in fading environment. The performance of cooperative detection in fading environment on the other hand, outperforms that of the single user detector. Index Terms— Cognitive Radio, Energy Detection, Spectrum Sensing, Wireless Communication. I. INTRODUCTION By convention, licensed spectrum is allocated over long time periods, and is meant to be used only by licensees. A government agency apportions license for spectrum use; referred to as the Fixed Spectrum Allocation (FSA) scheme. With this, the radio spectrum is split into bands allocated to distinct technology based services, e.g. mobile telephony, radio and TV broadcast on absolute basis. The FSA model guarantees exclusive use of the frequency spectrum by licensed users (i.e. the primary user (PU)) [1]. As a consequence of transition from regular voice-only communication to multimedia type applications demanding higher data rates, this plan will not have the capacity for this emerging applications. Records from the FCC frequency Manuscript received July 09, 201. (Please Fill Below Details) Oyibo, A. Michael, Electrical/Electronics Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana, +233541208968. (mikeoyibo@gmail.com). James D. Gadze, PhD. Electrical/Electronics Engineering, Kwame Nkrumah University of Science and Technolgy, Kumasi, Ghana, +233206891515. (jdgadze@gmail.com). allocation chart depict near occupation of useable spectrum by government and commercial operators, leaving little bandwidth for future wireless systems [2]. However, studies [3] show spectrum use is intense on certain portions while a significant amount remain underutilized. This is due, in part, to the fact that most carriers (i.e. license owners) do not transmit at all times in all geographic locations where the license covers. Records from the FCC indicate spectrum allocated in the bands below 3GHz have a utilization range of 15% to 85% [4]. Presented with the restrictions of the frequency spectrum, ground-breaking techniques that provide new ways of exploiting the available spectrum are required. As a result, Dynamic Spectrum Access (DSA) was proposed to solve this inefficiency challenge. With this concept, the licensed radio spectrum is optimized by secondary users that employ opportunistic spectrum access (OSA) of the frequency bands not occupied by the primary or licensed user. The enabling technology for this Next Generation (xG) network is the Cognitive Radio (CR). Cognitive Radio is an intelligent radio platform with the ability to exploit its environment to increase spectral efficiency and capacity. To this end, the CR technology is envisaged to enable the identification, use and management of vacant spectrum, known as Spectrum Holes or whitespaces [5]. To keep this effect at an acceptable level, secondary users will sense the spectrum to detect whether it is available or not. Reliable spectrum sensing is the most integral function, upon which the entire process of the cognitive radio rests [6]. The challenge then is that the procedure needs to have as little delay as possible so that once channels are available transmissions should occur immediately. Consequently, few false detections and false no-detections would be expected. There exist three spectrum sensing (SS) techniques in literature. These are the matched filter, cyclostationary detection and energy detection. Both the matched filter detection and the cyclostationary based detection concern the knowledge of a signal which is not obtainable in practical scenarios [7]. More so, these two techniques require a significant amount of time to detect a signal; adding complexity in the detection process. Among them, the energy detection scheme is widely feasible, since it does not require a priori knowledge of the primary signals and has lower complexity than the other two schemes. The ED method Prince Anokye, Electrical/Electronics Engineering, Kwame Nkrumah University of Science and Technolgy, Kumasi, Ghana, +233244976438. (princeanokye@yahoo.com). A Performance Study of Energy Detection Based Spectrum Sensing for Cognitive Radio Networks Oyibo, A. Michael, James D. Gadze, Prince Anokye