An Artificial Intelligence Approach in 5G New Radio Beam Enhancement
Deepak Upadhyay, Saksham Mittal, Ayushi Jain, Ravi Sharma, Piyush Bagla, Neha Tripathi, Pallavi Tiwari
Abstract
The paper presents a novel application of artificial neural networks in the context of 5G new radio beamforming. The research leverages the intricate mechanism of ANNs to demonstrate the efficacy of this approach in optimizing the beamforming process and improving the overall performance of the 5G new radio system. The utilization of ANNs allows for real-time adaptation and decision-making, thereby mitigating the limitations of conventional beamforming techniques. The results of the study are quite promising, indicating a substantial enhancement in the accuracy and efficiency of beamforming in 5G new radio. The proposed method is expected to have a significant impact on the development of advanced wireless communication systems.