Spectrum Sensing for OFDM Cognitive Radio using Matched Filter Detection
Suresh Dannana1, Babji Prasad Chapa2, Gottapu Sasibhushana Rao3
1Suresh Dannana, Department of Electronics and Communication Engineering, GMR Institute of Technology, Rajam, Andhra Pradesh, India,
2Babji Prasad Chapa, Department of Electronics and Communication Engineering, Andhra University College of Engineering (A), Andhra University, Visakhapatnam, AP, India.
3Gottapu Sasibhushana Rao, Department of Electronics and Communication Engineering, Andhra University College of Engineering (A), Andhra University, Visakhapatnam, AP, India.
Manuscript received on 12 March 2019 | Revised Manuscript received on 16 March 2019 | Manuscript published on 30 July 2019 | PP: 1447-1448 | Volume-8 Issue-2, July 2019 | Retrieval Number: B2124078219/19©BEIESP | DOI: 10.35940/ijrte.B2124.078219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The exponentially increasing high data rate applications demand more spectrum. Conventional spectrum allocation schemes failed in providing spectrum to meet the requirement. Cognitive radio introduces dynamic spectrum allocation. Spectrum sensing plays a very important role in cognitive radio. In this paper, OFDM with sensing algorithm based on matched filter detection is presented. An Orthogonal Frequency Division Multiplexing (OFDM) with Cyclic Prefix is used to reduce Inter Block Interference between successive symbols. The Receiver Operating Characteristics (RoC), detection probability with respect to Signal to Noise Ratio (SNR) for a given False Alarm Probability (PFA) obtained and analyzed. Simulation results shows that, this algorithm achieves probability of detection values 0.38 and 0.9 for SNR values of -20dB and -15 dB respectively at PFA=10-2. Chen, Hou-Shin, considered Time Domain Symbol Cross-correlation between two OFDM symbols. This paper mainly focusses on improving the detection probability at low SNR values without considering cross-correlation, which requires more computations.
Index Terms: Cognitive Radio (CR), False Alarm Probability (PFA), Orthogonal Frequency Division Multiplexing (OFDM), Receiver Operating Characteristics (RoC).
Scope of the Article: Cognitive Radio Networks