Seybold Report ISSN: 1533-9211
P.Rajalingam
Assistant Professor, Department of Electronics and Communication Engineering,
Sridevi Women’s Engineering College, Hyderabad, India, rajalingam.raj@gmail.com
Prakhya P
U.G Student, Department of Electronics and Communication Engineering, Sridevi Women’s Engineering College, Hyderabad, India
R.Sreenija Reddy
U.G Student, Department of Electronics and Communication Engineering, Sridevi Women’s Engineering College, Hyderabad, India
M.Bhanu Priya
U.G Student, Department of Electronics and Communication Engineering, Sridevi Women’s Engineering College, Hyderabad, India
Vol 17, No 07 ( 2022 ) | DOI: 10.5281/zenodo.6877814 | Licensing: CC 4.0 | Pg no: 187-200 | Published on: 25-07-2022
Abstract
Increasing use of mobile networks requires research into new features in order to provide better and better services leading to the development of 2G, 3G, 4G and 5G now and developing and deploying these services requires more complex and costly infrastructure and to overcome this problem the author of this paper. build a new 3GPP-based template (machine learning artificial Intelligence (AI) algorithms) that can mimic 5G and other mobile services. The 3rd Generation Partnership Project (3GPP) brings together seven communication development organizations (ARIB, ATIS, CCSA, ETSI, TSDSI, TTA, TTC), known as "Partner Partnerships" "and provides its members with a stable environment for the production of Reports and Data which explains 3GPP technology.
Therefore, the rapid emergence of mobile system design in 5G and above raises the need for research into new features, design proposals and solutions in the practical settings of various deployments and operating cases.
Keywords:
Cellular networks, 3GPP, Machine learning Artificial Intelligence algorithms, Organizational Partners, 5G