Hierarchical cellular network base station sleep method based on low-power base station

Abstract

The invention discloses a hierarchical cellular network base station sleep method based on a low-power base station. The hierarchical cellular network base station sleep method comprises the following steps of: S1, executing a sleep judgment of a macro base station according to the distribution density of the low-power base stations in a macro cell of the macro base station; and S2, after the sleep judgment of the macro base station is completed, executing a sleep judgment of the lower-power base stations in the macro cell. According to the invention, the problem that the traditional base station sleep policy is not applicable to a hierarchical network with co-existence of base stations of different types is solved; according to the characteristics of the hierarchical network, the advantages of the low-power base stations are fully utilized to make the sleep of the macro base station more flexible; and due to a dynamic bias value set in the sleep judgment, the blocking rate of a system is effectively reduced particularly in a user amount increase period, and the QoS (Quality of Service) requirements of users are met; and the judgment is made always by taking minimal energy consumption as a target, so that the energy consumption of the system is minimized on the basis of guaranteeing the QoS of the users.

Description

technical field [0001] The invention relates to the technical field of wireless communication, in particular to a dormancy method for hierarchical cellular network base stations based on distribution density of low-power base stations. Background technique [0002] In the past 10 years, the cellular network market has expanded rapidly, and the number of users and traffic demands have grown exponentially, which has brought enormous energy consumption demands to wireless networks. Today, more than four million base stations have been put into use around the world, consuming an average of 25MWh of electricity per year, and the number of base stations is expected to double in two years. In the access network, the energy consumption of the base station accounts for 80%. Taking the macro base station as an example, the fixed energy consumption of its internal components is huge. Therefore, when the number of users is low, there is a huge waste. In addition, although studies have ...

AI Technical Summary

Problems solved by technology

Secondly, in a macro cell, the distribution density of low-power base stations has a great impact on the distribution of macro base station users.

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