Analysis of M-QAM Signals Using Adaptive Detection Approach for Maximum Spectrum Sensing

Ch. Jessy Beulah, M. Usha


It is shown that the detection problems can be solved as convex optimization problems if certain practical constraints are applied. Simulation results show that the framework under consideration achieves much better performance for M-QAM than for binary phase-shift keying or any real modulation scheme. The performance analysis of proposed framework is expressed in terms of probabilities of detection and false alarm, and selection of detection threshold and number of samples. The simulations have shown that Bayesian detector has a performance similar to the energy detector in low SNR regime, but has better performance in high SNR regime in terms of spectrum utilization and secondary users’ throughput.


Cognitive radio; Bayesian Detector; Signal to noise ratio; Throughput

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Copyright (c) 2015 Ch. Jessy Beulah, M. Usha

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