Autonomous energy management method in small cell network based on energy harvesting

Abstract

The invention discloses an autonomous energy management method in a small cell network based on energy harvesting, belonging to the technical field of wireless communication. The autonomous energy management method in the small cell network based on energy harvesting comprises the following steps: setting the small cell network to include a macro base station MBS; constructing a base station management model in the small cell network, a small base station SBS energy consumption model of the small cell network, a macro base station MBS energy consumption model of the small cell network, and a small cell network energy harvesting model; establishing a QoS-based utility function mechanism, and setting a SON as an intelligent body in the small cell network, so as to realize autonomous management in the wireless network; constructing a multi-arm gambling machine model; setting an optimization objective function of the multi-arm gambling machine model; introducing an overhead factor C, and maximizing an overall network utility value; and determining the optimal sleep mechanism strategy of the small base station. The invention can improve the network utility value, improve the energy efficiency and reduce the network overhead under the conditions of no priori knowledge of energy harvesting and no global information.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and in particular relates to an autonomous energy management method in an ultra-dense wireless network based on energy collection. Background technique [0002] At present, the existing technologies commonly used in the industry are as follows: In 5G networks, with the continuous increase in the number of mobile devices and the emergence of data-driven emerging services, mobile data has exploded. Therefore, providing higher network capacity and wider network coverage to ensure the user's service quality requirements (QoS, quality of service) is a major challenge for future 5G wireless networks. Super-dense wireless network (small cell network, SCN) is an emerging network technology, which can be used as an effective supplement to macro base stations to effectively improve network capacity and coverage. With the dense deployment of wireless networks, due to the spatio-temporal dyna...

AI Technical Summary

Problems solved by technology

This increases network operation and maintenance costs and network management complexity. However, due to the uncertainty of the wireless environment around the base station and the random arrival characteristics of energy harvesting, it is difficult to predict the amount of energy collected, and centralized energy efficiency management, especially for super Dense wireless networks will make network management more complex and costly, requiring more complex energy management algorithms

[0003] To sum up, the problems existing in the existing technology are: the existing energy efficiency management based on energy harvesting technology has centralized management based on the premise that the collected energy and global network information are known, which requires a lot of signaling overhead; Due to the uncertainty of the wireless environment around the base station and the random arrival characteristics of energy collection, it is difficult to predict the amount of energy collected, and centralized energy efficiency management makes network management more complicated and more expensive

[0005] With the continuous increase of users and business growth, the wireless environment has high dynamic characteristics, which makes the complexity of the algorithm high and requires a more dynamic energy strategy

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