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

A dense network and joint optimization technology, applied in the field of network optimization, can solve problems such as ignoring the differences of small base stations, and achieve the effect of reducing network energy consumption and optimizing network energy efficiency

Active Publication Date: 2020-04-24
YANTAI UNIV
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Problems solved by technology

Therefore, the differences between small base stations should be taken into account when optimizing the energy efficiency of de

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

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Embodiment Construction

[0085] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with the accompanying drawings.

[0086] This embodiment is applicable to a scenario where a macro cell and a dense network are deployed at different frequencies. In this scenario, macro cells are deployed on frequency F1, and a dense network composed of a large number of small cells is deployed on frequency F2. Each small base station is deployed in a frequency reuse manner with a reuse factor of 1. The small base station is connected to the core network through a local gateway. Users in the network select the serving base station through the maximum reference signal received power (RSRP). The scenario of this embodiment is as figure 1 shown.

[0087] In such a network, the number of small base stations is huge, resulting in huge energy consumption of the network, and co-frequency deployment w...

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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...

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Application Information

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IPC IPC(8): H04W24/02H04W24/06H04W28/02
CPCH04W24/02H04W24/06H04W28/0221Y02D30/70
Inventor 吴世娥郑石军鞠雅林
Owner YANTAI UNIV
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