A novel approach for energy detector sensing time and periodic sensing interval optimization in cognitive radios

In this paper a new approach of optimizing the sensing time and periodic sensing interval for energy detectors has been explored. This new approach is built upon maximizing the probability of right detection, captured opportunities and transmission efficiency. The probability of right detection is defined as the probability of having no false alarm and correct detection. Optimization of the sensing time relies on maximizing the summation of the probability of right detection and the transmission efficiency while optimization of periodic sensing interval subjects to maximizing the summation of transmission efficiency and the captured opportunities. The optimum sensing time and periodic sensing interval are dependent on each other, hence, iterative approach to optimize them is applied and convergence criterion is defined. The simulations show that both converged sensing time and periodic sensing interval increase with the increase of the channel utilization factor, moreover, the probability of right detection, the transmission efficiency and the captured opportunities have been taken as the detector performance metrics and evaluated for different values of channel utilization factor and signal-to-noise ratio.

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