A Base Station Dormancy Method Based on Traffic Prediction and Base Station Status

Abstract

The invention discloses a base station dormancy method based on traffic prediction and base station state. The method predicts the future traffic load of each base station in the cellular network by introducing a fuzzy prediction model, which has better robustness and may obtain more accurate predicting result. By introducing traffic prediction in the sleep mode of the base station, the proportionof reserved resources of each base station may be reasonably set to improve the utilization of network resources, so that more base stations may switch to the sleep state so as to reduce the networkenergy consumption. Adding state factors of the base station to the value function may reduce the number of times of switching the working state of the base station and improve the stability of the base station state. By introducing a fuzzy prediction model, the invention predicts the future traffic of the base station, dynamically sets the reserved resources of the base station according to the prediction result, performs pre-sorting of the dormancy test on each base station by using the value function, and finally determines the dormant base station in the cellular network, thereby reducingthe network energy consumption.

Description

technical field [0001] The invention belongs to the technical field of communications, and relates to a base station dormancy method based on flow prediction and base station status. Background technique [0002] With the rapid development of the mobile communication industry, the number of cellular network users is also increasing year by year. In order to meet the growing demand of users for cellular networks, network operators need to deploy cellular network infrastructure on a large scale, which brings to our daily life However, with the large-scale deployment of base stations, the problem of energy consumption in cellular networks is becoming more and more serious. According to statistics, the current energy consumption of the information and communication industry accounts for about 2% of the global energy consumption, and the information and communication industry’s Energy consumption is growing rapidly, at an annual rate of 15% to 20%, almost doubling every five year...

AI Technical Summary

Problems solved by technology

The existing technology only considers more dormant base stations, but does not consider reducing the number of base station state switching. The proportion of reserved resources for base stations is only statically set, and no dynamic decision is made according to the future load of the base station, so it is difficult to implement. Maximize energy saving

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