Communication Micro Base Station Energy Method
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Power consumption modeling of different base station types in
In this paper we developed such power models for macro and micro base stations relying on data sheets of several GSM and UMTS base stations with focus on component
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Base station configuration # Antennas (per sector) # Sectors
In wireless communications micro cells are potentially more energy efficient than conventional macro cells due to the high path loss exponent. Also, heterogeneous deployments of both cell
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9
Various approaches have been proposed to reduce the energy consumption of an RBS, for instance, passive cooling techniques, energy-efficient backhaul solutions, and distributed base
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Energy-Efficient Base Station Deployment in Heterogeneous
In this paper we formalize the deployment of micro BSs in the coverage area of macro BSs as a mixed integer nonlinear programming problem, and then propose, based on Kuhn-Munkres
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Renewable microgeneration cooperation with base station
The energy consumption of the mobile network is becoming a growing concern for mobile network operators and it is expected to rise further with operational costs and carbon
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smart millimeter-wave base station for 6G application based on
For illustrating the potential of the proposed prototype in the application of a smart 6G base station, we take the proposed system to assist a millimeter-wave base station and
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EP2785097A1
To provide a radio communication method when a macro-base station and micro-base station are regarded as a plurality of transmission points and the plurality of transmission
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QoS-Aware Energy-Efficient MicroBase Station Deployment
We present a micro base station deployment strategy in 5G HetNets for obtaining high energy efficiency. It optimizes target values as are trade-offs at different user distribution
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Carbon emissions and mitigation potentials of 5G base station in
This study aims to understand the carbon emissions of 5G network by using LCA method to divide the boundary of a single 5G base station and discusses the carbon emission
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QoS-Aware Energy-Efficient MicroBase Station Deployment
An energy deployment algorithm based on high efficiency for micro base stations is considered as jointly optimizing micro base station''s number, deployment location, and
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Energy Consumption Optimization Technique for Micro Base
Abstract. In order to solve high energy consumption caused by massive micro base stations deployed in multi-cells, a joint beamforming and power allocation optimization algorithm is
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pimrc2010_final.dvi
In this paper we study various homogeneous and heterogeneous deployment strategies incorporating micro base stations with focus on energy efficiency represented by power
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Modelling the 5G Energy Consumption using Real-world Data: Energy
This paper proposes a novel 5G base stations energy consumption modelling method by learning from a real-world dataset used in the ITU 5G Base Station Energy Consumption Modelling
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Energy Efficiency Aspects of Base Station Deployment
In this paper we investigate on this issue in more detail and introduce concepts to assess and optimize the energy consumption of a cellular network model consisting of a mix of regular
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QoS-Aware Energy-Efficient MicroBase Station
There are several reasons for high energy consumption. Among them, we find that the increase in base station density of the 5G heterogeneous network (5G HetNets) is prominent. We present
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Energy-saving control strategy for ultra-dense network base
Aiming at the problem of mobile data traffic surge in 5G networks, this paper proposes an effective solution combining massive multiple-input multiple-output techniques
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Multi‐objective interval planning for 5G base station
Large-scale deployment of 5G base stations has brought severe challenges to the economic operation of the distribution network, furthermore,
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Green Deployment Method of Micro Base Station for Ultra-Dense
This paper proposes a green deployment method for micro base stations for ultra-dense heterogeneous cellular networks to balance network energy efficiency and electromagnetic
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Research on Capacity Allocation Method of Virtual Power Plant
Virtual power plant can aggregate distributed resources and obtain large-scale economic benefits. Communication base station energy storage is usually in an idle state, so it can provide a
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Optimization of 5G base station coverage based on self-adaptive
In communication network planning, a rational base station layout plays a crucial role in improving communication speed, ensuring service quality, and reducing investment
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Base Station Microgrid Energy Management in 5G Networks
The work begins with outlining the main components and energy consumptions of 5G BSs, introducing the configuration and components of base station microgrids (BSMGs),
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Modelling the Energy Efficiency of Microcell Base Stations
In this paper, an energy efficiency model for microcell base stations is proposed. Based on this model, the energy efficiency of microcell base stations is compared for various...
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US9374812B2
To provide a radio communication method when a macro-base station and micro-base station are regarded as a plurality of transmission points and the plurality of transmission points performs
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Energy-saving control strategy for ultra-dense network base stations
Aiming at the problem of mobile data traffic surge in 5G networks, this paper proposes an effective solution combining massive multiple-input multiple-output techniques
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Energy-Efficient Base Station Deployment in Heterogeneous Communication
In this paper we formalize the deployment of micro BSs in the coverage area of macro BSs as a mixed integer nonlinear programming problem, and then propose, based on Kuhn-Munkres
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Can power models be used for macro and micro base stations?
In this paper we developed such power models for macro and micro base stations relying on data sheets of several GSM and UMTS base stations with focus on component level, e.g., power amplifier and cooling equipment. In a first application of the model a traditional macro cell deployment and a heterogeneous deployment are compared.
What are the standardized energy-saving metrics for a base station?
(1) Energy-saving reward: after choosing a shallower sleep strategy for a base station, the system may save more energy if a deeper sleep mode can be chosen, and in this paper, the standardized energy-saving metrics are defined as (18) R i e = E S M = 0 − E S M = i E S M = 0 − E S M = 3
What is the power consumption of a base station?
The power consumption of each base station is considered about the number of mobile subscribers and random mobility to minimize the energy-saving cost of the cellular network.
Why does network sensitivity affect the energy consumption of base stations?
In addition, the high sensitivity of the existing policies to network conditions during the period when the network load is relatively smooth may lead to unnecessary and frequent switching of the sleep mode of the base stations, thus adding non-negligible additional energy consumption.
Why do base stations waste so much energy?
When there is little or no communication activity, base stations typically consume more than 80% of their peak power consumption, leading to significant energy waste . This energy waste not only increases operational costs, but also burdens the environment, which is contrary to global sustainability goals .
How does distributed execution affect base station control?
In the distributed execution phase, each actor network makes decisions independently based only on its own network and observations, and although each actor executes independently, the whole system is able to obtain a better base station control strategy because their strategies are based on the results of global optimization. Fig. 2.
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