0% Complete
Home
/
13th International Conference on Computer and Knowledge Engineering
Deep Learning-Driven Beamforming Optimization for High-Performance 5G Planar Antenna Arrays
Authors :
Rahman Mohammadi
1
Seyed Reza Razavi Pour
2
1- Department of Electrical Engineering, Faculty of Engineering Ferdowsi University of Mashhad
2- Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
Keywords :
5G،Beamforming،Deep Learning،mmWave،Planar Antenna Array
Abstract :
The ability of 5G wireless communication networks to effectively and simultaneously interact with incoming signals is made possible by antenna arrays, which play a vital role in assisting the functioning of 5G wireless communication networks. The utilization of beamforming enables the enhancement of signal strength, expansion of coverage area, and reduction of interference, thereby optimizing the performance of the communication networks. This paper introduces a deep learning approach that utilizes a deep neural network (DNN). This approach establishes an appropriate framework to implement beamforming for planar antenna arrays. The DNN utilizes the desired radiation pattern as an input to generate the complex excitation coefficients for each antenna element. For the purpose of enhancing the training procedure of the DNN being studied, a dataset including 300,000 varied radiation patterns was developed. These patterns were created by changing the amplitude and phase of each element within a uniform planar array by 208 elements. To showcase the efficacy of our proposed methodology, we conducted simulations in two different beamforming scenarios, namely single-beam and multi-beam modes. The simulations demonstrate that the utilization of beamforming techniques on the antennas within the novel approach has the potential to enhance the reliability and effectiveness of wireless communication networks in dynamic mode, as well as other antenna array systems.
Papers List
List of archived papers
An Ensemble CNN for Brain Age Estimation based on Hippocampal Region Applicable to Alzheimer's Diagnosis
Zahra Qodrati - Seyedeh Masoumeh Taji - Habibollah Danyali - Kamran Kazemi
AI-Driven Relocation Tracking in Dynamic Kitchen Environments
Arash Nasr Esfahani - Hamed Hosseini - Mehdi Tale Masouleh - Ahmad Kalhor - Hedieh Sajedi
Disturbance Rejection in Quadruple-Tank System by Proposing New Method in Reinforcement Learning
Alireza Nezamzadeh - Mohammadreza Esmaeilidehkordi
Evaluation of Efficient Electrocardiomatrix-based Identification Using Deep Learning Methods
Amirhossein Safari - Narges Mokhtari - Mohsen Hooshmand - Sadegh Sadeghi - Peyman Pahlevani
GAP: Fault tolerance Improvement of Convolutional Neural Networks through GAN-aided Pruning
Pouya Hosseinzadeh - Yasser Sedaghat - Ahad Harati
Deep Learning-Based Malaysian Sign Language (MSL) Recognition: Exploring the Impact of Color Spaces
Ervin Gubin Moung - Precilla Fiona Suwek - Maisarah Mohd Sufian - Valentino Liaw - Ali Farzamnia - Wei Leong Khong
Data Clustering using Chimp Optimization Algorithm
SAYED PEDRAM HAERI BOROUJENI - ELNAZ PASHAEI
The process of multi class fake news dataset generation
Sajjad Rezaei - Mohsen Kahani - Behshid Behkamal
BioBERT-based SNP-traits Associations Extraction from Biomedical Literature
Mohammad Dehghani - Behrouz Bokharaeian - Zahra Yazdanparast
Farsi Optical Character Recognition Using a Transformer-based Model
Fatemeh Asadi Zeydabadi - Elham Shabaninia - Hossein Nezamabadi-pour - Melika Shojaee
more
Samin Hamayesh - Version 41.5.3