@inproceedings{b1292871f8614d528920016018331b7e,
title = "Adaptive radio resource allocation to optimize throughput in multi-cell energy harvesting wireless networks",
abstract = "Energy harvesting is necessary to make the wireless network self-sustaining and self-organizing regardless of the traditional power grid. How to allocate the limited radio resources in the energy harvesting wireless network is a challenging work. This paper focuses on optimizing the time and power related resources in the multi-cell scenario to maximize the throughput constraining of the changeable energy in the base station. The optimal off-line resource allocation strategy is proposed, based on analysis of structural properties of the optimal total power sequences. To decrease the complexity of the optimal solution, a low complexity suboptimal off-line algorithm is presented based on the nature of the concave function. Furthermore, inspired by the off-line algorithm, an on-line resource allocation algorithm is proposed as well. Simulation results show the suboptimal offline algorithm closely tracks the performance of the optimal solution. And the proposed on-line algorithm also has brilliant performance compared with several kinds of algorithms under different system settings.",
author = "Lei Li and Mugen Peng and Jiamo Jiang and Kecheng Zhang and Hao Jin and Zhiguo Ding",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE Wireless Communications and Networking Conference, WCNC 2014 ; Conference date: 06-04-2014 Through 09-04-2014",
year = "2016",
month = apr,
day = "3",
doi = "10.1109/WCNC.2014.6953004",
language = "British English",
series = "IEEE Wireless Communications and Networking Conference, WCNC",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3094--3099",
booktitle = "IEEE Wireless Communications and Networking Conference, WCNC",
address = "United States",
}