Optimal Hybrid Channel Allocation:Based On Machine Learning Algorithms
K Viswanadh, Dr.G Rama Murthy

TL;DR
This paper proposes an intelligent hybrid channel allocation scheme using machine learning to improve spectrum utilization in wireless communications, enhancing traditional fixed allocation methods.
Contribution
It introduces the Optimal Hybrid Channel Allocation (OHCA) scheme that employs multilayer perceptron to optimize channel distribution over fixed methods.
Findings
Improved spectrum efficiency with OHCA.
Enhanced channel allocation accuracy.
Better resource utilization in cellular systems.
Abstract
Recent advances in cellular communication systems resulted in a huge increase in spectrum demand. To meet the requirements of the ever-growing need for spectrum, efficient utilization of the existing resources is of utmost importance. Channel Allocation, has thus become an inevitable research topic in wireless communications. In this paper, we propose an optimal channel allocation scheme, Optimal Hybrid Channel Allocation (OHCA) for an effective allocation of channels. We improvise upon the existing Fixed Channel Allocation (FCA) technique by imparting intelligence to the existing system by employing the multilayer perceptron technique.
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Taxonomy
TopicsWireless Communication Networks Research · Advanced Wireless Communication Techniques · Advanced MIMO Systems Optimization
