Throughput Maximization in Cognitive Radio Network Under Constant Fading using Hierarchical Neural System

Cognitive radios (CRs) predominantly reuse the spectrum holes to proficiently utilize the scarcely available radio spectrum. In the CRs, the throughput limitation is a major difficulty among the key limitations such as energy consumption, processing resources, cost, and quality of service limitations, that affects a wide range of telecommunication applications nowadays. Moreover, attaining high throughput will overcome the bottleneck of CRs applications. To overcome this emerging throughput limitation issue in the CRs, this paper proposes the best channel prediction algorithm using Multilayer Feed forward Neural Network (MFNN) which tackles the throughput limitations.