Dynamic Multiobjective Approach for Power and Spectrum Allocation in Cognitive Radio Networks

Cognitive radio (CR) is a promising technology for addressing resource scarcity in wireless networks. However, the current CR-based framework, when availability changes, existing allocation algorithms restart optimization process without using historical information. In addition, most previous studies have focused on one or two objectives and some only addressed pure power control spectrum allocation, limiting potential of CR. Thus, this article proposes dynamic multiobjective approach environment which available channels vary over time multiple are involved. This presents problem (MOP) with energy efficiency, fairness, utilization an Pareto optimality. A algorithm comprising hybrid initialization method feasible point generation mechanisms proposed to solve MOP. To dynamically adjust approximate optimal solutions, represented by center manifold, used predict new optima. The can yield better convergence level rate than those attained comparable algorithms. Compared conventional single-objective approaches, it achieves excellent balance between objectives.