scholarly journals Analysis of Energy Consumption Using Sequential to Better Signal (SBS) Scheme for Green Celluler Network

2020 ◽  
Vol 8 (1) ◽  
pp. 221-239
Author(s):  
Haniah Mahmudah ◽  
Okkie Puspitorini ◽  
Ari Wijayanti ◽  
Nur Adi Siswandari ◽  
Yetik Dwi Kusumaningrum
Keyword(s):  
Energy Consumption ◽  
Power Consumption ◽  
Cellular Network ◽  
Energy Savings ◽  
Base Station ◽  
Base Stations ◽  
Sleep Mode ◽  
Total Energy Consumption ◽  
Energy Consuming ◽  
Save Energy

Over time, cellular communication technology developed significantly from year to year. This is due to increasing the number of users and the higher needed. To overcome this problem, many providers increase the number of new base station installations to fill up the customer's needed. The increase number of base stations does not take into account the amount of power consumption produced, where in the cellular network Base Stations (BS) are the most dominant energy consuming equipment estimated at 60% - 80% of the total energy consumption in the cellular industry. In addition, energy waste often occurs in the BS where the emission power will always remain even if the number of users is small. Power consumption and energy savings are important issues at this time because they will affect CO2 emissions in the air. This paper proposes to save energy consumption from BS by turning off BS (sleep mode) if the number of users is small and distributed to other BS (neighboring BS) which is called cell zooming technique. The cell size can zoom out when the load traffic is high and zoom in when the load traffic is low. To determine the central BS and neighboring BS, a sequential to better signal (SBS) scheme is used where this scheme sorts neighboring BS based on the SINR value received (user). The results of this research, base station can be able to save energy 29.12% and reduce CO2 emission around 3580 kg/year.  It means saving energy consumption which is also reducing air pollution occurs and this term can be named as green cellular network. 

Energy Efficient Schemes for Base Station Management in 4G Broadband Systems

2014 ◽  
pp. 100-120 ◽  
Author(s):  
Alexandra Bousia ◽  
Elli Kartsakli ◽  
Angelos Antonopoulos ◽  
Luis Alonso ◽  
Christos Verikoukis
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Energy Savings ◽  
Base Station ◽  
Base Stations ◽  
Traffic Load ◽  
Network Resources ◽  
Load Variations ◽  
Mobile Cellular ◽  
Main Component

Reducing the energy consumption in wireless networks has become a significant challenge, not only because of its great impact on the global energy crisis, but also because it represents a noteworthy cost for telecommunication operators. The Base Stations (BSs), constituting the main component of wireless infrastructure and the major contributor to the energy consumption of mobile cellular networks, are usually designed and planned to serve their customers during peak times. Therefore, they are more than sufficient when the traffic load is low. In this chapter, the authors propose a number of BSs switching off algorithms as an energy efficient solution to the problem of redundancy of network resources. They demonstrate via analysis and by means of simulations that one can achieve reduction in energy consumption when one switches off the unnecessary BSs. In particular, the authors evaluate the energy that can be saved by progressively turning off BSs during the periods when traffic decreases depending on the traffic load variations and the distance between the BS and their associated User Equipments (UEs). In addition, the authors show how to optimize the energy savings of the network by calculating the most energy-efficient combination of switched off and active BSs.

scholarly journals Power Consumption: Base Stations of Telecommunication in Sahel Zone of Cameroon: Typology Based on the Power Consumption—Model and Energy Savings

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Albert Ayang ◽  
Paul-Salomon Ngohe-Ekam ◽  
Bossou Videme ◽  
Jean Temga
Keyword(s):  
Power Consumption ◽  
Air Conditioning ◽  
Energy Savings ◽  
Base Station ◽  
Energy Model ◽  
Base Stations ◽  
Consumption Model ◽  
Lighting Systems ◽  
Energy Audits ◽  
Air Conditioning Systems

In this paper, the work consists of categorizing telecommunication base stations (BTS) for the Sahel area of Cameroon according to their power consumption per month. It consists also of proposing a model of a power consumption and finally proceeding to energy audits in each type of base station in order to outline the possibilities of realizing energy savings. Three types of telecommunication base stations (BTS) are found in the Sahel area of Cameroon. The energy model takes into account power consumption of all equipment located in base stations (BTS). The energy audits showed that mismanagement of lighting systems, and of air-conditioning systems, and the type of buildings increased the power consumption of the base station. By applying energy savings techniques proposed for base stations (BTS) in the Sahel zone, up to 17% of energy savings are realized in CRTV base stations, approximately 24.4% of energy are realized in the base station of Missinguileo, and approximately 14.5% of energy savings are realized in the base station of Maroua market.

scholarly journals Transfer restless multi-armed bandit policy for energy-efficient heterogeneous cellular network

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Navikkumar Modi ◽  
Philippe Mary ◽  
Christophe Moy
Keyword(s):  
Cellular Network ◽  
Energy Savings ◽  
Learning Algorithm ◽  
Base Stations ◽  
Traffic Load ◽  
Total Energy Consumption ◽  
Load Variation ◽  
Markov Decision ◽  
Bs Switching ◽  
Upper Confidence Bound

Abstract This paper proposes a learning policy to improve the energy efficiency (EE) of heterogeneous cellular networks. The combination of active and inactive base stations (BS) that allows for maximizing EE is identified as a combinatorial learning problem and requires high computational complexity as well as a large signaling overhead. This paper aims at presenting a learning policy that dynamically switches a BS to ON or OFF status in order to follow the traffic load variation during the day. The network traffic load is represented as a Markov decision process, and we propose a modified upper confidence bound algorithm based on restless Markov multi-armed bandit framework for the BS switching operation. Moreover, to cope with initial reward loss and to speed up the convergence of the learning algorithm, the transfer learning concept is adapted to our algorithm in order to benefit from the transferred knowledge observed in historical periods from the same region. Based on our previous work, a convergence theorem is provided for the proposed policy. Extensive simulations demonstrate that the proposed algorithms follow the traffic load variation during the day and contribute to a performance jump-start in EE improvement under various practical traffic load profiles. It also demonstrates that proposed schemes can significantly reduce the total energy consumption of cellular network, e.g., up to 70% potential energy savings based on a real traffic profile.

scholarly journals Performance Analysis of Cell Zooming Based Centralized Algorithm for Energy Efficient in Surabaya

2016 ◽  
Vol 4 (2) ◽  
Author(s):  
Hani’ah Mahmudah ◽  
Okkie Puspitorini ◽  
Ari Wijayanti ◽  
Nur Adi Siswandari ◽  
Rosabella Ika Yuanita
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Cellular Network ◽  
Mobile User ◽  
Base Station ◽  
Base Stations ◽  
Traffic Load ◽  
Traffic Condition ◽  
Centralized Algorithm ◽  
Cell Zooming

The cellular subscribers’s growth over the years increases the traffic volume at Base Stations (BSs) significantly. Typically, in central business district (CBD) area, the traffic load in cellular network in the daytime is relatively heavy, and light in the daynight. But, Base Station still consumes energy normally. It can cause the energy consumption is wasted. On the other hand, energy consumption being an important issue in the world. Because, higher energy consumption contributes on increasing of emission. Thus, it requires for efficiency energy methods by switching BS dynamically. The methods are Lower-to-Higher (LH) and Higher-to-Lower (HL) scheme on centralized algorithm. In this paper propose cell zooming technique  which can adjusts the cell size dynamic based on traffic condition. The simulation result by using Lower-to-Higher (LH) scheme can save the network energy consumption up to 70.7917% when the number of mobile user is 37 users and 0% when the number of mobile user is more than or equal to 291 users. While, Higher-to-Lower (HL) scheme can save the network energy consumption up to 32.3303% when the number of mobile user is 37 users and 0% when the number of mobile user is more than or equal to 292 users. From both of these schemes, we can analyze that by using Lower-to-Higher (LH) scheme reduces energy consumption greater than using Higher-to-Lower (HL) scheme. Nevertheless, both of them can be implemented for energy-efficient method in CBD area. Eventually, the cell zooming technique by using two schemes on centralized algorithm which leads to green cellular network in Surabaya is investigated.

scholarly journals Investigation and Evaluation of Energy Consumption Performance for Hospital Buildings in China

2019 ◽  
Vol 11 (6) ◽  
pp. 1724 ◽  
Author(s):  
Ru Ji ◽  
Shilin Qu
Keyword(s):  
Energy Consumption ◽  
Evaluation System ◽  
Energy Use ◽  
Energy Savings ◽  
Building Energy ◽  
Total Energy Consumption ◽  
Electricity Use ◽  
Hospital Building ◽  
Save Energy ◽  
Air Conditioning Systems

Energy use in hospitals is higher than other public buildings, so it is essential to investigate and evaluate its energy consumption performance to save energy. In this paper, a comprehensive investigation was conducted to study energy consumption of hospitals in China. The investigation results show that electricity use accounts for the maximum share in total energy consumption of hospitals, especially in south China. Improving air conditioning systems is the most direct and effective way for realizing hospital building energy savings. What’s more, a new evaluation system of energy-saving performance for hospital buildings was developed. This evaluation system could evaluate performance of energy use in hospital, find out the weakness of energy use, and provide improving suggestions. Furthermore, a kind of visual software was given by our paper, which can be used intuitively by practitioners to evaluate building energy consumption performance of a hospital.

DEVELOPMENT OF VALUATION METHOD OF THE STATUS OF BASE STATIONS FOR DETERMINING THE NEED OF THEIR UPGRADING

2017 ◽  
pp. 60-70
Author(s):  
Natalya Ivanovna Shaposhnikova ◽  
Alexander Aleksandrovich Sorokin
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Cellular Network ◽  
New Technologies ◽  
Base Station ◽  
Base Stations ◽  
Valuation Method ◽  
The Status ◽  
Telecommunications Services ◽  
Theory Of Fuzzy Sets

The article consideres the problems of determining the need to modernize the base stations of the cellular network based on the mathematical apparatus of the theory of fuzzy sets. To improve the quality of telecommunications services the operators should send significant funding for upgrading the equipment of base stations. Modernization can improve and extend the functions of base stations to provide cellular communication, increase the reliability of the base station in operation and the functionality of its individual elements, and reduce the cost of maintenance and repair when working on a cellular network. The complexity in collecting information about the equipment condition is determined by a large number of factors that affect its operation, as well as the imperfection of obtaining and processing the information received. For a comprehensive assessment of the need for modernization, it is necessary to take into account a number of indicators. In the structure of indicators of the need for modernization, there were introduced the parameters reflecting both the degree of aging and obsolescence(the technical gap and the backlog in connection with the emergence of new technologies and standards). In the process of a problem solving, the basic stages of decision-making on modernization have been allocated. Decision-making on the need for modernization is based not only on measuring information that takes into account the decision-makers, but also on linguistic and verbal information. Therefore, to determine the need for upgrading the base stations, the theory of fuzzy sets is used, with the help of which experts can be attracted to this issue. They will be able to formulate additional fuzzy judgments that help to take into account not only measuring characteristics, but also poorly formalized fuzzy information. To do this, the main indicators of the modernization need have been defined, and fuzzy estimates of the need for modernization for all indicators and a set of indicators reflecting the need for upgrading the base stations have been formulated.

Energy savings potential of new aeration system: Full scale trials

2012 ◽  
Vol 7 (4) ◽  
Author(s):  
A. Lazić ◽  
V. Larsson ◽  
Å. Nordenborg
Keyword(s):  
Control System ◽  
Energy Consumption ◽  
Total Energy ◽  
Energy Savings ◽  
Treatment Plant ◽  
Full Scale ◽  
Total Energy Consumption ◽  
Aeration System ◽  
Fine Bubble ◽  
Aeration Control

The objective of this work is to decrease energy consumption of the aeration system at a mid-size conventional wastewater treatment plant in the south of Sweden where aeration consumes 44% of the total energy consumption of the plant. By designing an energy optimised aeration system (with aeration grids, blowers, controlling valves) and then operating it with a new aeration control system (dissolved oxygen cascade control and most open valve logic) one can save energy. The concept has been tested in full scale by comparing two treatment lines: a reference line (consisting of old fine bubble tube diffusers, old lobe blowers, simple DO control) with a test line (consisting of new Sanitaire Silver Series Low Pressure fine bubble diffusers, a new screw blower and the Flygt aeration control system). Energy savings with the new aeration system measured as Aeration Efficiency was 65%. Furthermore, 13% of the total energy consumption of the whole plant, or 21 000 €/year, could be saved when the tested line was operated with the new aeration system.

scholarly journals Practical Model for Energy Consumption Analysis of Omnidirectional Mobile Robot

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1800
Author(s):  
Linfei Hou ◽  
Fengyu Zhou ◽  
Kiwan Kim ◽  
Liang Zhang
Keyword(s):  
Energy Consumption ◽  
Power Consumption ◽  
Mobile Robot ◽  
Load Capacity ◽  
Working Environment ◽  
Energy Consumption Analysis ◽  
Mecanum Wheel ◽  
Save Energy ◽  
Energy Consumption Modeling ◽  
Robot Platform

The four-wheeled Mecanum robot is widely used in various industries due to its maneuverability and strong load capacity, which is suitable for performing precise transportation tasks in a narrow environment. While the Mecanum wheel robot has mobility, it also consumes more energy than ordinary robots. The power consumed by the Mecanum wheel mobile robot varies enormously depending on their operating regimes and environments. Therefore, only knowing the working environment of the robot and the accurate power consumption model can we accurately predict the power consumption of the robot. In order to increase the applicable scenarios of energy consumption modeling for Mecanum wheel robots and improve the accuracy of energy consumption modeling, this paper focuses on various factors that affect the energy consumption of the Mecanum wheel robot, such as motor temperature, terrain, the center of gravity position, etc. The model is derived from the kinematic and kinetic model combined with electrical engineering and energy flow principles. The model has been simulated in MATLAB and experimentally validated with the four-wheeled Mecanum robot platform in our lab. Experimental results show that the accuracy of the model reached 95%. The results of energy consumption modeling can help robots save energy by helping them to perform rational path planning and task planning.

scholarly journals Adaptive offloading in mobile-edge computing for ultra-dense cellular networks based on genetic algorithm

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Zhuofan Liao ◽  
Jingsheng Peng ◽  
Bing Xiong ◽  
Jiawei Huang
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Cellular Networks ◽  
Physical Distance ◽  
Edge Computing ◽  
Base Stations ◽  
Mobile Edge Computing ◽  
Total Energy Consumption ◽  
Average Delay ◽  
Server Selection

AbstractWith the combination of Mobile Edge Computing (MEC) and the next generation cellular networks, computation requests from end devices can be offloaded promptly and accurately by edge servers equipped on Base Stations (BSs). However, due to the densified heterogeneous deployment of BSs, the end device may be covered by more than one BS, which brings new challenges for offloading decision, that is whether and where to offload computing tasks for low latency and energy cost. This paper formulates a multi-user-to-multi-servers (MUMS) edge computing problem in ultra-dense cellular networks. The MUMS problem is divided and conquered by two phases, which are server selection and offloading decision. For the server selection phases, mobile users are grouped to one BS considering both physical distance and workload. After the grouping, the original problem is divided into parallel multi-user-to-one-server offloading decision subproblems. To get fast and near-optimal solutions for these subproblems, a distributed offloading strategy based on a binary-coded genetic algorithm is designed to get an adaptive offloading decision. Convergence analysis of the genetic algorithm is given and extensive simulations show that the proposed strategy significantly reduces the average latency and energy consumption of mobile devices. Compared with the state-of-the-art offloading researches, our strategy reduces the average delay by 56% and total energy consumption by 14% in the ultra-dense cellular networks.

Analysis of China’s Provincial Energy Efficiency Based on the Generalized DEA Method

2014 ◽  
Vol 953-954 ◽  
pp. 890-895
Author(s):  
Hui Min Li ◽  
Cun Bin Li ◽  
Zhan Xin Ma
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Utilization ◽  
Utilization Efficiency ◽  
Total Energy Consumption ◽  
Rapid Economic Growth ◽  
Technology Changes ◽  
Dea Method ◽  
Save Energy ◽  
The Impact

In recent years, with the rapid economic growth, the demand on the amount of energy in China is increasing. So the problem of how to improve the energy utilization efficiency and save energy consumption has to be tackled. The traditional CCR model and BCC model used in the study of provincial energy efficiency do not take the impact of technological progress into consideration. Therefore, the paper uses the generalized DEA method to research the energy utilization efficiency of China’s 29 provinces, that is, to evaluate and analyze the energy utilization efficiency by selecting the capital stock, employment and total energy consumption of China’s provinces as input factors and GDP, per capital GDP as output factors, and then draw tables showing each province’s change of average annual overall efficiency and the pure technology changes, and finally analyze the regularities underlying these changes.

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