EVOLUTION OF WIRELESS (CELLULAR) COMMUNICATION NETWORKS

• Published in: Radio physics and radio astronomy (Print) Vol. 30; no. 2; pp. 89 - 100
• Main Authors: Chernogor, L., Shevelev, M.
• Format: Journal Article
• Language: English
• Published: National Academy of Sciences of Ukraine, Institute of Radio Astronomy 01.06.2025
• Subjects: data rate; delay time; fundamental constraint; information transfer duration; network evolution; regression; saturation effect; wireless network
• ISSN: 1027-9636; 2415-7007
• DOI: 10.15407/rpra30.02.089

Subject and Purpose. One of today’s challenges in contemporary radio physics is exploring the terahertz frequency range which holds immense promise for revolutionary new applications in part at the level of wireless communication systems. A substantial frequency capacity of the range theoretically permits a usable frequency band expansion to a hundred terahertz. The data transfer rate can increase by many orders of magnitude, surpassing the capabilities of current networks. An urgent research priority involves assessing the potential growth rates of wireless communication network resources. The immediate purpose of this paper is to suggest simple mathematical models developed to predict the growth rates of wireless (cellular) communication network resources over the next 20 to 25 years. Methods and Methodology. The research problem receives analytical consideration, systems analysis, and mathematical modeling of the evolutionary pace of wireless communication in new generations. Results. Using average data on the parameters of 1G to 5G communication networks and 6G in development, we have built regression models representative of the evolution of information transfer rates and data transmission durations until the year 2050. Equations have been derived describing the evolution of the main parameters of wireless communications. The information rate increase since 1979 is shown to obey the instability equation, wherein the main parameter of the communication system exhibits exponential growth. Models featuring accelerated evolution have been proposed along with more realistic, slowed evolution models considering the saturation effect and a substantial slowdown in the information transfer rates. The saturation effect is associated with the exponential growth of the characteristic evolution time and determined by the data rate growth slowdown, with fundamental, conditionally fundamental, and scientific-technical constraints considered. It has been substantiated that 8G is not expected sooner than 2040—2045 and will likely terminate the wireless communication evolution, with a maximum information transfer rate of 300 to 1000 Tbit/s in the terahertz range. Conclusions. The mathematical models developed by the authors are simple and capable of predicting the growth dynamics of wireless communication network resources.