Open AccessPerformance of Massive MIMO systems in cognitive spectrum sensing
Author(s) -
B. Shamla,
T R Amrutha
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1817/1/012001
Subject(s) - cognitive radio , false alarm , computer science , spectrum management , fading , additive white gaussian noise , interference (communication) , channel (broadcasting) , mimo , detector , white spaces , energy (signal processing) , electronic engineering , statistical power , telecommunications , algorithm , real time computing , wireless , artificial intelligence , engineering , statistics , mathematics
Cognitive radio is a revolutionary technology that guarantees a viable solution to the spectrum scarcity problem. This prominent new technology has the power to change future technological developments forever if intelligently applied. In Cognitive Radio Networks, secondary (unlicensed) user uses the licensed spectrum band opportunistically, without creating any interference with primary user (licensed) transmission. Spectrum sensing is a vital challenge for spectrum usage and to prevent harmful interference with licensed users. Energy detection has been for a long, constituting the most widely known sensing technique in cognitive radio systems. In this paper, Neyman - Pearson criterion-based detection rules are used to incorporate the local probabilities of detection and false alarm to analyse an energy detector sensing behaviour over additive white Gaussian (AWGN) channel, fading channel and massive multiple input multiple output(MIMO) cases. Closed-form solutions for the probabilities of false alarm and detection were derived. The analytical results were verified by numerical computations using the Monte Carlo method with MATLAB.