Fair Spectrum Allocation with Reducing Spectrum Handoff in Cognitive Radio Sensor Networks

This paper considers the problem of centralized spectrum allocations in wireless cognitive radio sensor networks towards the following goals: (1) maximizing fairness reflecting the priority among sensor data, and (2) avoiding unnecessary spectrum handoff. We cast this problem into a multiobjective mixed integer non-convex nonlinear programming. To tackle the intractability, we first convexify the original problem using arithmetic-geometric mean approximation, and then deploy weighted Chebyshev norm-based scalarization method in order to collapse the multiobjective problem into a single objective one. Finally, we apply simple rounding method in order to obtain approximate integer solutions. A noticeable advantage of the proposed approach is that it enables to find fairly good approximated integer solutions within reasonable computation time.