Energy Efficient Beam-Forming and Power Distribution in Cognitive Radio Network

Potential solutions to meet the growing need for wireless applications can be found in the Cognitive Radio Network. There are many obstacles to overcome in the pursuit of higher-quality services with good spectrum efficiency. Multiple unlicensed users' capacity limitations are the main cause of this. In this model beam shaping technique combined with Distributed Dynamic Power Allocation (DDPA) with multiple constraints are put forth to address the underutilization and restricted spectrum availability in cognitive networks (CN). Channel allocation and spectrum hole classification with capacity constraints are effectively addressed by the suggested method. In this case, efficient methods are used for both spectrum prediction and forecast frequency allocation. By increasing spectral and energy efficiencies in CRN, the suggested system also increases the likelihood of using frequency spectrum. The proposed (DDPA) model with (Fractional Transmit Power Algorithm and Power Based Pricing Algorithm (PBPA)) shows the increased efficiencies of the suggested approach. The outcome shows a noteworthy efficacy in improving the CN's efficiencies with less computational complexity and higher throughput.