Abstract
Due to the continuous increase in data demanded by end-users, an energy-efficient base station (BS) is a vital topic of interest that would not only result in a substantial economic impact on service providers, but would also reduce the carbon footprint of operating a network. In this regard, we propose the structure and systematic operation of a BS with a large-scale (LS) antenna system that can increase the energy efficiency (EE) of cellular systems. The proposed BS structure includes various power-related units, such as a central management apparatus, power controller, EE calculator, radio site-dependent parameter space (RSD-PS) and determiner. With the information provided from each unit, the decision unit determines how to adjust each component of the BS in order to maximize the EE. Extensive simulations show that the proposed BS improves the EE performance by about 83.05% relative to the reference BS.
Highlights
Communication technologies that can increase channel capacity, as well as energy efficiency (EE)would be a key factor for future wireless systems
It is well known that base stations (BS) consume around 60%–80% of power consumption in cellular networks [1,2,3]
Rather than presenting a BS on/off mechanism or solving the theoretical optimization problem, we focus on more practical implementation aspects to improve the EE of cellular systems
Summary
Communication technologies that can increase channel capacity, as well as energy efficiency (EE)would be a key factor for future wireless systems. Reducing the power consumption of a BS is quite important to reduce the operational costs, as well as the carbon footprint. For this reason, researchers have actively investigated this problem [1,2,4,5,6,7,8,9,10,11,12,13,14,15]. Most work has concentrated on implementing the BS on/off technique, which means that the BS is turned off when there is no nearby traffic [1,2,9,10,12,14], as well as on conducting theoretical high-level analyses and optimizations to reduce the BS power consumption [7,8,11,13]. There could be many real implementation obstacles for theoretical, high-level optimization techniques
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