Dense network energy consumption and energy efficiency joint optimization method by considering cell difference

Abstract

The invention relates to a dense network energy consumption and energy efficiency joint optimization method by considering cell difference, which is characterized by comprising the following steps that: S1, each small base station counts the load and neighbor base station information of the small base station and reports the information to a local gateway, and the local gateway calculates the energy efficiency preference function of the small base station; S2, energy consumption and energy efficiency of the dense network are calculated, an energy efficiency preference function is calculated, and an energy consumption and energy efficiency joint optimization problem is modeled into a multi-objective optimization problem; S3, sub-frame configuration A * of each small base station is optimized by adopting a sub-frame configuration algorithm based on a cooperative dormancy set to reduce network energy consumption; and S4, the optimal power P* is solved by adopting a power distribution algorithm based on a concave-convex process, and the network energy efficiency is optimized. According to the method, the energy consumption and energy efficiency joint optimization problem of the dense network is described as a multi-objective optimization problem, a base station cooperation subframe dormancy strategy and a power distribution scheme are formulated, and the network energy efficiency is optimized to the maximum extent while the user rate demand is ensured.

Description

technical field [0001] The invention relates to a network optimization method, in particular, a joint optimization method for dense network energy consumption and energy efficiency considering cell differences. Background technique [0002] In a dense network, network energy consumption increases dramatically due to the increased density of small base stations. As an important indicator of 5G systems, energy efficiency has attracted widespread attention from all walks of life. In a dense network, how to consume the least energy while improving network energy efficiency is an urgent problem to be solved. [0003] The two main goals of green communication are to save energy consumption and improve network energy efficiency. The main methods used are resource allocation, network planning and deployment, energy collection and transfer, and hardware optimization. In network planning and deployment schemes, energy consumption is reduced or network energy efficiency is improved m...

AI Technical Summary

Problems solved by technology

Therefore, the differences between small base stations should be taken into account when optimizing the energy efficiency of dense networks, and the differences between small base stations have been ignored in the existing energy efficiency optimization.

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