Self-Optimization of Cell Sizes in Cellular Networks

Papaioannou, C., Onireti, O. , Imran, M. A. and Arshad, K. (2015) Self-Optimization of Cell Sizes in Cellular Networks. In: 2015 International Wireless Communications and Mobile Computing Conference (IWCMC), Dubronvnik, Croatia, 24-28 Aug 2015, pp. 1406-1411. ISBN 9781479953448 (doi: 10.1109/IWCMC.2015.7289288)

Abstract

The next generation networks seem to be too dense compared to the existing one, so a self-control mechanism, which determines the optimal cell size will be essential. In this paper, we present self organized cell size control algorithms, which maintain optimum system throughput and power consumption. Particularly, we investigate three different algorithms that control the cells size, while maintaining the optimum power consumption and block allocation in the network. These algorithms differ in terms of their decision area. The first one is based on a centralized control; the second one is a distributed approach; and the final one is based on a group distributed control. In order to evaluate their performance, these algorithms are tested upon two different simulation environment, which approach real scenarios. Our results indicate that the group distributed algorithm is the best approach for future network, since it has a good performance and about 10 times lower computational complexity when compared with the centralized approach.

• Item Type: Conference Proceedings
• Additional Information: This research leading to these results was partially derived from the University of Greenwich Research & Enterprisel Investment Programme grant under agreement number RAEES-01/14.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Imran, Professor Muhammad and Onireti, Oluwakayode
• Authors: Papaioannou, C., Onireti, O., Imran, M. A., and Arshad, K.
• College/School: College of Science and Engineering > School of Engineering; College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
• ISBN: 9781479953448