Motion Sensor-Based Small Cell Sleep Scheduling for 5G Networks

Abstract

The fifth generation of mobile systems will rely on a dense deployment of small cells in order to meet its ambitious Key Performance Indicator targets. However, this dense deployment will result in a significant increase in the energy consumption of 5G networks, and thus, OPEX costs. Several small cell sleeping algorithms have been proposed in the literature but they require complex algorithms to decide when to switch on/off the small cells. On the basis of a distributed self-organizing approach, in this paper, we propose a low-cost, low-complexity small cell sleep scheduling algorithm to minimize the energy consumption of small cells in 5G and beyond networks. Our control utilizes a motion detection circuit to toggle the small cell between sleep and active modes based on the presence of a user. We evaluate the performance the algorithm on an experimental testbed and the results show that our algorithm achieves up to 20% reduction in energy consumption when compared to 'always on' approach.

Multi-Objective UAV Positioning Mechanism for Sustainable Wireless Connectivity in Environments with Forbidden Flying Zones

“…Consequently, energy saving is a fundamental design requirement for 5G networks. Although, in the case of ground base stations, solutions as low-cost, low-complexity cell sleep scheduling algorithms may help to minimize the energy consumption while guaranteeing the service requirements [28,29], for UAV-assisted networks it is still an open-issue. For the coexistence of UAVs and underlaid device-to-device (D2D) communication networks, a tractable analytical framework is proposed in [22].…”