scholarly journals Energy-Aware Base Stations: The Effect of Planning, Management, and Femto Layers

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
G. Koutitas ◽  
L. Chiaraviglio ◽  
Delia Ciullo ◽  
M. Meo ◽  
L. Tassiulas
Keyword(s):  
Energy Savings ◽  
Mobile Network ◽  
Basic Element ◽  
Base Station ◽  
Base Stations ◽  
Energy Aware ◽  
Urban District ◽  
Mobile Operator ◽  
Deterministic Algorithms ◽  
Management Scheme

We compare the performance of three base station management schemes on three different network topologies. In addition, we explore the effect of offloading traffic to heterogeneous femtocell layer upon energy savings taking into account the increase of base station switch-off time intervals. Fairness between mobile operator and femtocell owners is maintained since current femtocell technologies present flat power consumption curves with respect to served traffic. We model two different user-to-femtocell association rules in order to capture realistic and maximum gains from the heterogeneous network. To provide accurate findings and a holistic overview of the techniques, we explore a real urban district where channel estimations and power control are modeled using deterministic algorithms. Finally, we explore energy efficiency metrics that capture savings in the mobile network operator, the required watts per user and watts per bitrate. It is found that the newly established pseudo distributed management scheme is the most preferable solution for practical implementations and together with the femotcell layer the network can handle dynamic load control that is regarded as the basic element of future demand response programs.

scholarly journals Online Supervisory Control and Resource Management for Energy Harvesting BS Sites Empowered with Computation Capabilities

2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Thembelihle Dlamini ◽  
Ángel Fernández Gambín ◽  
Daniele Munaretto ◽  
Michele Rossi
Keyword(s):  
Energy Harvesting ◽  
Energy Savings ◽  
Virtual Machines ◽  
Mobile Network ◽  
Base Stations ◽  
Traffic Load ◽  
Short Term ◽  
Energy Aware ◽  
Multi Access

The convergence of communication and computing has led to the emergence of multi-access edge computing (MEC), where computing resources (supported by virtual machines (VMs)) are distributed at the edge of the mobile network (MN), i.e., in base stations (BSs), with the aim of ensuring reliable and ultra-low latency services. Moreover, BSs equipped with energy harvesting (EH) systems can decrease the amount of energy drained from the power grid resulting into energetically self-sufficient MNs. The combination of these paradigms is considered here. Specifically, we propose an online optimization algorithm, called Energy Aware and Adaptive Management (ENAAM), based on foresighted control policies exploiting (short-term) traffic load and harvested energy forecasts, where BSs and VMs are dynamically switched on/off towards energy savings and Quality of Service (QoS) provisioning. Our numerical results reveal that ENAAM achieves energy savings with respect to the case where no energy management is applied, ranging from 57% to 69%. Moreover, the extension of ENAAM within a cluster of BSs provides a further gain ranging from 9% to 16% in energy savings with respect to the optimization performed in isolation for each BS.

Mobile network synthesis strategy

2019 ◽  
pp. 98-101
Author(s):  
V. Lyandres
Keyword(s):  
Average Distance ◽  
Mobile Network ◽  
Base Station ◽  
Service Area ◽  
Base Stations ◽  
Frequency Assignment ◽  
Network Synthesis ◽  
Universal Method ◽  
Synthesis Strategy ◽  
Adaptive Vector Quantization

Introduction:Effective synthesis of а mobile communication network includes joint optimisation of two processes: placement of base stations and frequency assignment. In real environments, the well-known cellular concept fails due to some reasons, such as not homogeneous traffic and non-isotropic wave propagation in the service area.Purpose:Looking for the universal method of finding a network structure close to the optimal.Results:The proposed approach is based on the idea of adaptive vector quantization of the network service area. As a result, it is reduced to a 2D discrete map split into zones with approximately equal number of service requests. In each zone, the algorithm finds such coordinates of its base station that provide the shortest average distance to all subscribers. This method takes into account the shortage of the a priory information about the current traffic, ensures maximum coverage of the service area, and what is not less important, significantly simplifies the process of frequency assignment.

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 Base Station Energy Efficiency Improvement for Next Generation Mobile Networks

2017 ◽  
Vol 63 (2) ◽  
pp. 187-194 ◽  
Author(s):  
Weston Mwashita ◽  
Marcel Ohanga Odhiambo
Keyword(s):  
Mobile Networks ◽  
Energy Efficient ◽  
Carbon Dioxide Emissions ◽  
Mobile Network ◽  
Base Station ◽  
Base Stations ◽  
Data Traffic ◽  
Energy Efficiency Improvement ◽  
Next Generation Mobile Networks ◽  
Operational Expenditure

Abstract As more and more Base Stations (BSs) are being deployed by mobile operators to meet the ever increasing data traffic, solutions have to be found to try and reduce BS energy consumption to make the BSs more energy efficient and to reduce the mobile networks’ operational expenditure (OPEX) and carbon dioxide emissions. In this paper, a BS sleeping technology deployable in heterogeneous networks (HetNets) is proposed. The proposed scheme is validated by using extensive OMNeT++/SimuLTE simulations. From the simulations, it is shown that some lightly loaded micro BSs can be put to sleep in a HetNet when the network traffic is very low without compromising the QoS of the mobile network.

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 Green Base Station using WSN

2019 ◽  
Vol 9 (2) ◽  
pp. 3660-3665
Keyword(s):  
Large Scale ◽  
Power Saving ◽  
Mobile Network ◽  
Base Station ◽  
Base Stations ◽  
Diesel Generator ◽  
Successful Operation ◽  
Night Time ◽  
Communication Services ◽  
Reduction Of Co2

Since the number of mobile users has been increased, there comes a number of new mobile operators. This accounts for the increased installation of towers. A critical mobile network consume 40-50MW (approx.) and a diesel generator consume 1MG (approx.) of diesel per day. Also a base station requires greater amount of power employed for its working in which some of its internal applications like light, coolant systems say air conditioning, fans etc., uses the major part of the power utilized. This intensifies the burning of coal which emits carbon dioxide into the atmosphere. At times the number of users for a base station may be very less especially during night time, consuming the power unnecessarily. Our approach is to reduce the intake of power by the base stations during unwanted time. This can be done by establishing communication between the adjacent towers to intimate the unused tower to remain idle or active based on the requirement. Also this approach conveys the measures taken to reduce the power consumed by the internal applications of the base station. The entire setup is under the surveillance of personal computer thereby creating an energy efficient mobile infrastructure with power saving, reduction of CO2 emission which in turn reduces global warming and successful operation of large scale mobile communication services.

scholarly journals USE OF ADAPTIVE ANTENNA ARRAYS FOR INCREASE THE THROUGHPUT IN LTE-A

2021 ◽  
pp. 17-25
Author(s):  
D. O. Makoveenko ◽  
S. V. Siden ◽  
V. V. Pyliavskyi
Keyword(s):  
Antenna Array ◽  
Antenna Arrays ◽  
Noise Analysis ◽  
Mobile Network ◽  
Base Station ◽  
Base Stations ◽  
Adaptive Antenna ◽  
Adaptive Antenna Arrays ◽  
Useful Signal ◽  
Antenna Systems

Context. The aim of the article is to analyze the throughput of the LTE-A mobile network on the uplink using an adaptive linear equidistant antenna array. Objective. Suggestions have been made for the possibility of using adaptive antenna arrays to increase bandwidth in LTE-A mobile networks and analyze the benefits of its use compared to the standard type of base station antenna Method. To achieve this result, a computer model of noise analysis of the mobile network in the form of a flat regular hexagonal antenna array consisting of 7 three-sector cells was developed. To estimate the benefit from the use of adaptive antenna arrays, two options were analyzed: when using a standard antenna array of the LTE-A network, and an adaptive linear equidistant antenna array. During the simulation, 100 random placements of subscribers of useful and interference signals were performed and the minimum, maximum and average gain from the use of adaptive antenna arrays was calculated. The average value of the gain for the adaptive antenna array in the direction of the subscriber station, which generates a useful signal of 5.69 dB more than the standard antenna array of the LTE-A network. At the same time, there is a significant reduction in the gain of the adaptive antenna in the direction of the interference subscriber stations, namely, for those with the highest interference level, the gain is 32.84 dB and 28.33 dB, respectively. To clearly show the gain in the qualitative characteristics of the network, a bandwidth analysis was performed for different types of antennas. The bandwidth distribution (transport block size) for 50 resource blocks using an adaptive equidistant linear antenna array compared to a standard antenna array is presented. Results. It is shown that due to the use of adaptive antenna systems, the average bandwidth increases from 11 Mbit/s to 35 Mbit / s for all types of distribution considered channels. Conclusions. The article proposes the use of adaptive antenna arrays to increase the bandwidth of the LTE-A network. The simulation of bandwidth for 50 resource blocks showed that in the presence of internal system interference when using standard antennas of base stations, the average bandwidth is from 11.2 Mbps to 12.3 Mbps. At the same time, due to the use of adaptive antenna systems, the average bandwidth increases from 11 Mbit/s to 35 Mbit/s for all types of multipath channels considered.

Management Scheme for Data Collection within Wireless Sensor Networks

2012 ◽  
Vol 3 (2) ◽  
pp. 59-76
Author(s):  
Sami J. Habib ◽  
Paulvanna N. Marimuthu
Keyword(s):  
Data Collection ◽  
Energy Level ◽  
Data Management ◽  
Dominating Set ◽  
Residual Energy ◽  
Base Station ◽  
Base Stations ◽  
Intermediate Node ◽  
Management Scheme ◽  
Simulation Results

This paper proposes a data management scheme which employs an energy constrained algorithm selecting between direct and multi-hop transmissions autonomously based on the residual energy level of the individual sensors. The proposed data management scheme rules out the selection of hotspot sensors, the sensors located closer to the base stations, as the intermediate sensors to avoid the dying of these sensors. In each data transmission, the scheme selects one of the neighborhood sensors having minimal Euclidean distance and maximum energy-level as the intermediate node from the neighboring set, without repeating the selection. The proposed data management scheme manages the data collection by utilizing two scheduling algorithms; as soon as possible (ASAP) and as late as possible (ALAP). As a measure of performance, the simulation results of the data management scheme have been compared with that of minimum connected dominating set algorithm (MCDS). The simulation results demonstrate that the data management scheme outperforms with respect to consume less energy; moreover, it can be observed that the scheme finishes an overall short waiting time of the selected sensors compared to the direct transmission in transmitting the data to the base station. The robustness of the proposed scheme is tested by varying the network sizes and varying the sensing radii.

MEASUREMENT OF EMF EXPOSURE AROUND SMALL CELL BASE STATION SITES

2018 ◽  
Vol 184 (2) ◽  
pp. 211-215
Author(s):  
Marthinus Jacobus van Wyk ◽  
Jacobus Christiaan Visser ◽  
Christiaan Wynand le Roux
Keyword(s):  
Geographical Area ◽  
Mobile Network ◽  
Base Station ◽  
Small Cell ◽  
Base Stations ◽  
Small Cells ◽  
Service Areas ◽  
Exposure Levels ◽  
Network Technologies ◽  
Cell Base

Abstract As mobile network technologies and usage change, mobile network cells have become smaller to meet the increased demand for data throughput. Small cell base stations are frequently used as a mobile network deployment method and are predominantly installed to service areas with a high density of people and to cover a small geographical area. Various measurement programs of the electromagnetic field (EMF) exposure have been conducted around base stations in general and these results have been published. There is, however, little data available on the EMF exposure levels around small cells. A measurement program was conducted to perform EMF exposure measurements around small cell base station sites. Results are compared to the relevant safety guidelines and to available data for EMF exposure around base stations in general.

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. 

Sign in / Sign up

Export Citation Format

Share Document