Novel Analytical Model for Resource Allocation Over Cognitive Radio in 5G Networks

The framework of 5G with cognitive radio network faces a challenge of heterogeneity and non-synchronization. Existing approaches towards utilizing cognitive radio over 5G network for the purpose of resource allocation is strictly defined on smaller subsets of the nodes as well as non-consideration of practical parameters that is affected by the presence of artifacts like interference. Therefore, the proposed manuscript introduces a novel evaluation model that investigates the impact of mathematical optimization over resource allocation over 5G networks. The study uses an analytical research methodology where disciplined convex optimization is used as a part of improving the process of resource allocation along with novelty of consideration of practical parameters. The simulated outcome of study shows that proposed system offers better communication performance in contrast to existing resource allocation schemes.