Network energy-saving method based on base stations to be closed preferably

Abstract

The invention discloses a network energy-saving method based on base stations to be closed preferably. Firstly, an access function of a user and load functions and energy consumption functions of the base stations are defined, cost brought by closing of a certain base station to increase of loads of a whole network is estimated by means of the defined functions, a base station sequencing method is designed on the basis of network cost, and ultimately, accordingly to sequencing of the base stations, the base stations which are good in energy-saving effect are closed preferably, and switching is finished by the user according to the rule that the network loads are increased in the minimized mode. According to the method for closing the base stations preferably, overall consumption of network energy can be reduced, performance is close to the optimal value of exhaustive solving, and meanwhile calculation complexity is greatly reduced.

Description

technical field [0001] The invention relates to a network energy-saving method based on preferably shutting down base stations, which is used to solve the problem of energy-saving of LTE (Long Term Evolution) networks, and belongs to the network technical field in wireless communication networks. Background technique [0002] The LTE network has been widely recognized by the industry for its higher spectrum utilization and faster data rate, but the subsequent large amount of energy consumption and the environmental problems it has become the focus of attention of the communication industry and the whole society. LTE wireless network varies with time and location, and the tidal effect in the network is significant, while the LTE wireless network is designed according to the maximum capacity required by users. When the traffic in the network is low, many devices are idle, resulting in a large amount of energy. waste. Therefore, in order to reduce the energy consumption of the...

AI Technical Summary

Problems solved by technology

The advantage of the first method is that the amount of calculation is small, but due to the large difference in business volume in different regions and time periods, defining a reasonable threshold requires long-term analysis and statistics, and it is difficult to achieve the optimal energy-saving effect

The second method has the advantage of good energy-saving effect, but the amount of calculation required to complete the decision-making is as high as the user's power of the cell. It takes a long time to complete the dynamic decision-making under the existing server computing capacity, and it is difficult to apply on the scale of the existing network.

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