Intelligent battery management for cellular networks with hybrid energy supplies
Document Type
Conference Proceeding
Publication Date
9-12-2016
Abstract
Green communications has received much attention in recent years. In cellular networks, base stations (BSs) account for more than 50 percent of the energy consumption. Reducing energy consumption of BSs is essential to realize green cellular networks. Utilizing green energy to power BSs is a promising way to reduce the on-grid energy consumption. Owing to the dynamics of both mobile traffic loads and green energy, the mismatch between the energy demands and green energy generation in a BS results in inefficient green energy utilization. Managing the battery in BSs can control the green energy usage in individual time slots, thus alleviating the inefficiency caused by the mismatch. In this paper, we propose an intelligent battery management mechanism to optimize the green energy utilization in BSs based on the Markov Decision Process (MDP). A large number of states in the Markov chain are required to model the dynamics of solar radiation and BS workload demands. Thus, the original MDP optimal policy iteration method incurs a high computational complexity. Therefore, we propose some heuristics to approximate the optimal energy dispatching strategy with low computational complexity, and validate the performance of the proposed algorithm through extensive simulations.
Identifier
84989956054 (Scopus)
ISBN
[9781467398145]
Publication Title
IEEE Wireless Communications and Networking Conference Wcnc
External Full Text Location
https://doi.org/10.1109/WCNC.2016.7564759
ISSN
15253511
Volume
2016-September
Grant
1320468
Fund Ref
National Science Foundation
Recommended Citation
Liu, Xilong; Han, Tao; and Ansari, Nirwan, "Intelligent battery management for cellular networks with hybrid energy supplies" (2016). Faculty Publications. 10279.
https://digitalcommons.njit.edu/fac_pubs/10279
