Published Paper Details:

The lack of available spectrum is a problem for everyone involved in the telecommunications sector. Recent research has demonstrated that inefficient use of the spectrum, rather than a lack of spectrum, is the primary cause of the availability problem. Inspiring from this line of thinking is the concept of New Radio(5G)that can make use of the spectrum as it becomes accessible in a manner similar to how natural frequencies are used. In this setting, we take on the dual challenges of power regulation and frequency allocation. Specifically, we develop a simple, near-optimal method with linear complexity to maximize the capacity of a new radio network by optimizing the distribution of channels among users. We also take into account a conservative design in which primary users must meet certain requirements.With the advent of 5G networks, it has become crucial to provide quality of service (QoS) for channel allocation for base station to macro-cell, to accommodate the enormous data rates and low latency of 5G's internet-connected devices, a new method for the delivery of quality of service has evolved. For over decades, there has been a rapid rise in the number of data users. In terms of bandwidth availability and reliability, data demand is at peak than standard voice services. Allocating a channel based on, the proposed method for decision-making algorithm trained using machine learning to detects when a channel becomes available for channel allocation, the proposed model will have lower average delay and a higher success rate.