Time-Efficient Sub-Optimal Solutions for Dynamic Spectrum Allocation in CRN With User Fairness

Abstract

The incredibly increasing demand for higher rates in the last decade as well as the introduction of many new applications that require wireless connectivity necessitate proper and efficient utilization of the frequency spectrum. During the last decade, the concept of cognitive radio has been introduced and extensively researched as a possible solution for telecommunication operators to increase the use of the spectrum, which is usually under-utilized. In this paper, the problem of dynamic spectrum allocation is discussed. A new mathematical formulation is proposed for the dynamic spectrum allocation problem. The new formulation defines a bi-objective function that considers the maximization of both the total system throughput and the number of active users. The proposed formulation is solved optimally using the branch and bound algorithm with a linear programming solver at its core. In addition, two novel heuristic algorithms are proposed for use instead to alleviate the time complexity of the branch and bound algorithm. Simulations show that although sub-optimal, the solutions obtained by the proposed algorithms are at least 80% of the optimum solution obtained by the branch and bound algorithm, with the advantage of significantly shorter time.

Keywords

• Cognitive radio
• binary linear program
• optimization
• spectrum allocation
• throughput
• user fairness