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Fundamental Limitations in Energy Detection for Spectrum Sensing

Nanfang College, Sun Yat-Sen Univeristy, Guangzhou 510900, China
College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China
Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada
School of Computer Science and Engineering, Kyungpook National University, Daegu 41566, Korea
Author to whom correspondence should be addressed.
J. Sens. Actuator Netw. 2018, 7(3), 25;
Received: 15 May 2018 / Revised: 27 June 2018 / Accepted: 27 June 2018 / Published: 28 June 2018
PDF [425 KB, uploaded 28 June 2018]


A key enabler for Cognitive Radio (CR) is spectrum sensing, which is physically implemented by sensor and actuator networks typically using the popular energy detection method. The threshold of the binary hypothesis for energy detection is generally determined by using the principles of constant false alarm rate (CFAR) or constant detection rate (CDR). The CDR principle guarantees the CR primary users at a designated low level of interferences, which is nonetheless subject to low spectrum usability of secondary users in a given sensing latency. On the other hand, the CFAR principle ensures secondary users’ spectrum utilization at a designated high level, while may nonetheless lead to a high level of interference to the primary users. The paper introduces a novel framework of energy detection for CR spectrum sensing, aiming to initiate a graceful compromise between the two reported principles. The proposed framework takes advantage of the summation of the false alarm probability Pfa from CFAR and the missed detection probability (1Pd) from CDR, which is further compared with a predetermined confidence level. Optimization presentations for the proposed framework to determine some key parameters are developed and analyzed. We identify two fundamental limitations that appear in spectrum sensing, which further define the relationship among the sample data size for detection, detection time, and signal-to-noise ratio (SNR). We claim that the proposed framework of energy detection yields merits in practical policymaking for detection time and design sample rate on specific channels to achieve better efficiency and less interferences. View Full-Text
Keywords: fundamental limitations; SNR; energy detection; noise variance; spectrum sensing fundamental limitations; SNR; energy detection; noise variance; spectrum sensing

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Hu, X.-L.; Ho, P.-H.; Peng, L. Fundamental Limitations in Energy Detection for Spectrum Sensing. J. Sens. Actuator Netw. 2018, 7, 25.

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