Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICC.2013.6655484
Title: Optimal power and range adaptation for green broadcasting
Authors: Luo, S.
Zhang, R. 
Lim, T.J. 
Issue Date: 2013
Source: Luo, S.,Zhang, R.,Lim, T.J. (2013). Optimal power and range adaptation for green broadcasting. IEEE International Conference on Communications : 5595-5600. ScholarBank@NUS Repository. https://doi.org/10.1109/ICC.2013.6655484
Abstract: Improving energy efficiency is key to network providers maintaining profit levels and an acceptable carbon footprint in the face of rapidly increasing data traffic in cellular networks in the coming years. The energy-saving concept studied in this paper is the adaptation of a base station's (BS's) transmit power levels and coverage area according to channel conditions and traffic load. Cell coverage is usually pre-designed based on the estimated peak traffic load. However, traffic load in cellular networks exhibits significant fluctuations in both space and time. We design short- and long-term power control (STPC and LTPC respectively) policies for the OFDMA-based downlink of a single-cell system, where bandwidth is dynamically and equally shared among a random number of mobile users (MUs). STPC is a function of all MUs' channel gains that maintains the required user-level quality of service (QoS), while LTPC is a function of traffic density that minimizes the long-term energy consumption at the BS under a minimum throughput constraint. We first develop a power scaling law that relates the (short-term) average transmit power at BS with the given cell range and MU density. Based on this result, we derive the optimal (long-term) transmit adaptation policy by considering a joint range adaptation and LTPC problem. Finally, we compare our proposed adaptation scheme with suboptimal schemes of lower complexity to demonstrate the potential energy saving in broadcast channels. © 2013 IEEE.
Source Title: IEEE International Conference on Communications
URI: http://scholarbank.nus.edu.sg/handle/10635/71292
ISBN: 9781467331227
ISSN: 15503607
DOI: 10.1109/ICC.2013.6655484
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