Performance Optimization in Energy Harvesting Cognitive Radio Networks a Shift Towards Metaheuristics

Optimization in energy-harvesting cognitive radio networks is accomplished by the amalgamation of metaheuristics with wireless networks. The design of an optimized energy-harvesting cognitive radio network (EHCRN) is challenging in the realm of wireless networks. This paper proposes a modified optimization technique rank-based multiobjective antlion optimization (RMOALO) based on antlions that finds an approximate solution to the optimization problem of sensing duration and energy consumption with throughput maximization. The search behavior of antlions is improved thus reaching an optimal solution while considering the constraints on collision and energy. The simulated results obtained in this paper show that the average throughput of the secondary wireless network gets maximized for an optimized sensing duration. The results also demonstrate the effect of spectrum sensing duration on the average harvested energy and average throughput for the energy-sufficient and energy-deficit regions.