An Artificial Intelligence Approach in 5G New Radio Beam Enhancement
- Resource Type
- Conference
- Authors
- Upadhyay, Deepak; Mittal, Saksham; Jain, Ayushi; Sharma, Ravi; Bagla, Piyush; Tripathi, Neha; Tiwari, Pallavi
- Source
- 2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC) Secure Cyber Computing and Communication (ICSCCC), 2023 Third International Conference on. :641-646 May, 2023
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Engineering Profession
Wireless communication
Performance evaluation
Array signal processing
Precoding
Decision making
Scattering
Artificial neural networks
ANN
Beamforming
ML
CNN
IoT
- Language
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.