Intelligent cooperation management among solar powered base stations towards a green cellular network in a country with an equatorial climate

Abstract

Energy efficiency in cellular networks is a growing concern for cellular operators with regard to maintaining profitability and reducing their overall environmental impact. Because evolved node Bs (eNBs) for long-term evolution wireless cellular networks are deployed to accommodate peak traffic, they are underutilized most of the time, especially under low-traffic conditions. Hence, switching eNBs on and off in accordance with traffic pattern variations is considered to be an effective method of improving energy efficiency in cellular networks. However, two main concerns of network operators when applying this technique are coverage issues and securing radio service for an entire area in response to the increased size of some cells to provide coverage for cell areas that are switched off. This study focuses on the parameters that affect coverage in order to find a balance between cellular network energy consumption and the area of cell coverage. To achieve this goal, particle swarm optimization, a bio-inspired computational method, has been adopted in this study to maximize the cell coverage area under the constraints of the transmission power of the eNB $$(P_{tx})$$(Ptx), the total antenna gain (G), the bandwidth (BW), the signal-to-interference-plus-noise ratio (SINR), and shadow fading $$(\sigma )$$(�). In addition, the study investigated potential for gains in operational expenditures by operating eNB on solar energy. The optimum criteria, including economic, technical and environmental feasibility parameters, were analyzed using the HOMER.