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Iterative Optimization of Energy Detector Sensing Time and Periodic Sensing Interval in Cognitive Radio Networks
Abstract
In this chapter the authors propose a new approach for optimizing the sensing time and periodic sensing interval for energy detectors in cognitive radio networks. The optimization of the sensing time depends on maximizing the summation of the probability of right detection and transmission efficiency, while the optimization of periodic sensing interval is subject to maximizing the summation of transmission efficiency and captured opportunities. Since the optimum sensing time and periodic sensing interval are dependent on each other, an iterative approach to optimize them simultaneously is proposed and a convergence criterion is devised. In addition, the probability of detection, probability of false alarm, probability of right detection, transmission efficiency, and captured opportunities are taken as performance metrics for the detector and evaluated for various values of channel utilization factors and signal-to-noise ratios.
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