Abstract

Conventional methods for spectrum sensing do not consider historical traffic data. Equal amount of time is allocated to each channel of interest for sensing. In this research paper, we formulate the time optimization problem for spectrum sensing keeping historical traffic data into account. We have solved the problem for interesting constraints. For the solution of these constraints stochastic programming formulation has been done. The problem is also formulated as a quadratic/hybrid programming problem where the variance of discrete random variable constitutes a quadratic form associated with a laplacian like matrix. Using this result, time optimal spectrum sensing is formulated as a multi-linear objective function optimization problem.

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