Premium
RAT selection for a low battery mobile device for future 5G networks
Author(s) -
Adiwal Manisha,
Singh Niraj Pratap
Publication year - 2019
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.4055
Subject(s) - computer science , heterogeneous network , computer network , selection (genetic algorithm) , access network , radio access technology , quality of service , wireless network , umts frequency bands , cellular network , radio access network , task (project management) , wireless , user equipment , telecommunications , base station , artificial intelligence , mobile station , management , economics
Summary The growth of wireless communication toward fifth generation will lead to the existence of number of access technologies to provide seamless connectivity and form heterogeneous network environment. Earlier, there was single access technology to run applications, but 5G will have heterogeneous network environment and provide separate network for each application. As compared with 4G, 5G will provide increase in data rate, decrease in delay, increase in quality of service, and so on because of its various enabling technologies. Therefore, for each application, selection of best access network via its enabling technology is an important task. This selection is done either at user terminal side or at network operator side by combining preferences for network attributes and network parameters. In this paper, to enjoy 5G, selection is done in a heterogeneous networks environment for enabling technologies like device‐to‐device communication, spectrum sharing, enhancing quality of experience, energy efficiency, and so on. This selection is done via optimization techniques for a fixed duration video clip that is to be transmitted from a device running low in battery. The selection environment composed of UMTS, WLAN1, and WLAN2 as available networks. The simulation results show that the network selected for each enabling technology supports various features of 5G. Also, error analysis of selection results is done using confidence interval estimate at 90%, 92%, and 95% confidence level. From results obtained, it is seen that different optimization techniques used to access network for different enabling technologies (providing 5G features) prove to be useful for future 5G network.