Optimal spectrum assignment for cognitive radio sensor networks under coverage constraint

Cognitive radios emerged as a solution to spectrum scarcity problem. The integration of cognitive radios and Wireless Sensor Networks (WSN) enables a new paradigm of communication in which, sensor nodes can avoid heavily crowded transmission bands by tuning their transmission parameters to less crowded bands. In this paper we consider the problem of Spectrum Assignment (SA) for Cognitive Radio Sensor Network (CRSN) under coverage, interference, minimum data rate, and power budget constraints. A Mixed Integer Non-Linear Programming (MINLP) problem formulation that addresses optimal power allocation, channel selection, and node scheduling is presented. Following a practical assumption, that any CRSN node can only access one channel for its transmission with the CRSN base station, the problem is transformed to a Binary Linear Programming (BLP) problem. Using Relaxation techniques, the problem is transformed to a Linear Programming (LP) problem that is solvable in polynomial time, and has the same optimal solution of the BLP problem. We propose the minimum power algorithm that achieves the optimal solution of our problem. To further reduce the complexity of the solution, we propose three heuristic lower-complexity algorithms to solve the problem: random, greedy, and two-stage (decoupled) algorithms.