TY - GEN
T1 - Self-optimization of cell sizes in cellular networks
AU - Papaioannou, Charalampos
AU - Onireti, Oluwakayode
AU - Imran, Muhammad Ali
AU - Arshad, Kamran
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/10/2
Y1 - 2015/10/2
N2 - 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.
AB - 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.
KW - Heterogeneous networks
KW - Self-optimization
KW - Self-organizing networks
UR - https://www.scopus.com/pages/publications/84949498423
U2 - 10.1109/IWCMC.2015.7289288
DO - 10.1109/IWCMC.2015.7289288
M3 - Conference contribution
AN - SCOPUS:84949498423
T3 - IWCMC 2015 - 11th International Wireless Communications and Mobile Computing Conference
SP - 1406
EP - 1411
BT - IWCMC 2015 - 11th International Wireless Communications and Mobile Computing Conference
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th International Wireless Communications and Mobile Computing Conference, IWCMC 2015
Y2 - 24 August 2015 through 28 August 2015
ER -