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International Journal of Electronics and Communication Engineering and Technology

(IJECET)

Volume 9, Issue 5, September-October 2018, pp. 1–16, Article ID: IJECET_09_05_001

Available online at http://www.iaeme.com/IJECET/issues.asp?JType=IJECET&VType=9&IType=5

ISSN Print: 0976-6464 and ISSN Online: 0976-6472

© IAEME Publication

ENERGY EFFICIENT SOLUTIONS FOR GREEN

CELLULAR NETWORKS – A SURVEY

Deepa Palani

Sethu Institute of technology, Tamilnadu, India

Merline Arulraj

Sethu Institute of technology, Tamilnadu, India

ABSTRACT

In recent years, Energy – Efficiency in Cellular Networks is an important concern

for network operators. The growing awareness of Energy – Efficiency as well as

economic concern of network operators provides the new technologies in designing

Green Cellular networks. The green cellular network has become the most popular

research topic for the future. The Energy – Efficiency solution can be achieved by

improving the design of certain hardware or by providing renewable energy sources

(RES) like solar or wind. According to the technical analyst, the Base Stations (BSs)

are the most energy intensive part of the Cellular Network. As the BSs consume more

power of the total energy used in cellular network, a survey on techniques to obtain

energy saving in BSs and powered by renewable energy sources in the area where

there is no public and stable power supply to obtain the Green Cellular Networking is

considered first. In this survey, the realities which gives the importance of green

mobile networking and review of the existing methods to obtain Energy – Efficiency is

presented.

Keywords: Energy – Efficiency, Base Station, Green Cellular Network, sleep mode,

Renewable Energy Sources (RES).

Cite this Article: Deepa Palani and Merline Arulraj, Energy Efficient Solutions for

Green Cellular Networks – A Survey. International Journal of Electronics and

Communication Engineering and Technology, 9(5), 2018, pp. 1–16.

http://www.iaeme.com/IJECET/issues.asp?JType=IJECET&VType=9&IType=5

1. INTRODUCTION

The rapid growth of mobile users and the network devices creates a severe consequence. The

growing awareness of global warming and environment consequences of Information and

Communication Technology (ICT), researchers have been finding ways to reduce energy

consumption [1], [2], [3]. In ICT, the cellular network become a significant component which

has considerable concentration of many researchers to reduce the energy in cellular networks,

since it increases the energy bills for telecommunication service providers and it increases the

emission of (CO2) carbon foot print [4]-[8]. The increase of energy bill depends on the usage

Energy Efficient Solutions for Green Cellular Networks – A Survey


of Android and iPhone devices, use of ebook readers such as iPad and Kindle and the success

of social networking giants. It increases the demand for cellular data traffic and motivates new

high – speed (more energy consuming) network standards like 4G LTE.

Figure 1 Number of Smart Phone users in India from 2015 to 2022

Such extraordinary growth in cellular industry has pushed the limits of energy

consumption in wireless networks. There are currently more than 4 million base stations

(BSs) serving mobile users, each consuming an average of 25MWh per year. The numbers of

BSs in developing regions are expected to almost double by 2022 as shown in Fig. 1.

Information and Communication Technology (ICT) already represents around 2% of total

carbon emissions (of which mobile networks represent about 0.2%), and this is expected to

increase every year. In addition to the environmental aspects, energy costs also represent a

significant portion of network operators’ overall expenditures (OPEX). While the BSs

connected to electrical grid may cost approximately 3000$ per year to operate, the off-grid

BSs in remote areas generally run on diesel power generators and may cost ten times more

[9]. Due to this tremendous growth, Energy efficiency is becoming increasingly important for

cellular mobile network operators due to environmental and economic concerns [10–12].

Reduction in energy consumption reduces pollution and greenhouse gas and brings cost-

saving benefits to the operators and consumers.

Figure 2 Power consumption of a Cellular Network

Figures 2 shows a power consumption of various components in a distinctive cellular

network and gives the understanding into the possible research avenues for reducing energy

consumption in wireless communications [9]. A typical cellular network consists of three

main elements; A core network that takes care of switching; base stations providing radio

Deepa Palani and Merline Arulraj


frequency interface; and the mobile terminals in order to make voice or data connections. The

power consumption is distributed across the different functionalities of the network like

mobile switching, core transmission, data centre etc. [13,14]. But the base stations are the

most energy intensive part of the cellular network. A typical 3G base station which uses

500W of input power to produce 40W of output RF power will consume more than 50GWh a

year in a network with 12,000 base stations. This causes a large amount of CO2 emission as

well as contributes to the network's operating costs [15]. In Cellular network, base station

power feeding is the major power issue concerning. Saving power in base stations is therefore

the primary focus in green cellular network development [16]. In this paper, a brief survey on

some of the work that has already been done to achieve power efficiency in cellular networks,

discuss some research issues and challenges and suggest some techniques to enable an energy

efficient or ―green‖ cellular network is provided.

2. METHODOLOGIES

There are various distinctive approaches to reduce energy consumptions in a mobile cellular

network. Approaches in previous research can be broadly classified into the following

categories.

Architecture Level.

Hardware Components

Base station Sleeping

Enhancing energy efficiency of the radio broadcast process.

Deployment of heterogeneous cells.

Implementing renewable energy resources.

2.1. Hardware Components

Approaches of the first category aim to improve hardware components (such as power

amplifier) with more energy efficient design (e.g. [17]–[21]). The performance of most

components used in current cellular network architecture is unsatisfactory from the energy

efficiency perspective. Considering, for example, the power amplifier, the component

consuming the largest amount of energy in a typical cellular base station (BS), more than 80%

of the input energy is dissipated as heat. Generally, the useful output power is only around 5%

to 20% of the input power [22]. Studies showed that the potentially optimized ratio of output

power to input power for power amplifiers (power efficiency) could be as high as 70% [22].

Accordingly, substantial amount of energy savings can be achieved if more energy efficient

components are adopted in the network. However, the implementation cost for these

approaches is high. For example, a power amplifier module with 35% power efficiency for

small cell WCDMA or LTE BSs (cover at most an area of a radius of 2 km) costs around $75

[23]. The cost will be even higher for larger coverage or higher power efficiency. Therefore,

careful consideration in both operational and economical aspects by network operators is

required before decisions on hardware replacement are made.

The Flexi base station (BTS) - An industry-leading, cost and energy-efficient multi-radio

base station for Single Radio Access Network (RAN) advanced mobile broadband networks is

an example of efficient site design and management by Nokia Siemens Networks [24]. The

Flexi base station acts as a software-defined base station for technologies like Global System

for Mobile Communications (GSM)/ Enhanced Data rates for GSM Evolution(EDGE),

Wideband Code Division Multiple Access(WCDMA)/ Evolved High-Speed Packet

Access(HSPA+), and 3rd Generation Partnership Project(3GPP) - Long Term Evolution(LTE)

(i.e Frequency division duplex(FDD)/ Time-division duplex(TDD) systems). The benefits of a



Flexi base station are as follows: reduced installation time and materials costs, compact size

and reduced weight - only 20% of a conventional cabinet base station, up to 70% reduction in

site power consumption, flexible location either indoor or outdoor without the need for air

conditioning, shorten antenna feeders. The Flexi base station carbon footprint is further

diminished by its software-based capacity to remotely manage tuning the running capacity,

upgrade, cancelling the need for site visiting. Its upgrading capability enables flexibility for

sites to upgrade and adapt to future radio technologies with maximum re-use of legacy site

infrastructure.

The Ericsson’s Tower Tube- Tower Tube is an award-winning solution by Ericsson with

latest technology and innovative design to reduce construction cost, decrease carbon emission,

energy optimization and for pleasant look [25]. In tower tube the radio base station is

positioned at height for improved network’s coverage, capacity and low feeder loss. It is

space efficient with all slim designed equipment encapsulated in the tower. It does not require

cooling. Thus, with cutting edge design and building materials like concrete with post-tension

reinforcement technology, the Tower tube lowers the amount of carbon dioxide in the

manufacturing process also.

2.2. Switching off Components

The second category covers approaches that selectively turn off some resources in the existing

network architecture during non-peak traffic hours (e.g.,1[26]–[32]). Approaches in this

category generally try to save energy by monitoring the traffic load in the network and then

decide whether to turn off (or switch to sleep mode, also referred as low-power mode or deep

idle mode in some literature), or turn on (or switch to active mode, ready mode or awake

mode) certain elements of the network. Unnecessary energy consumptions, for example, air

conditioning under-loaded BSs, can be avoided by adopting such sleep mode mechanisms.

These approaches generally involve switching certain elements including but not limited to

power amplifiers, signal processing unit, cooling equipment, the entire BS, or the whole

network back and forth between the sleep mode and the active mode [32]. Most often, sleep

mode techniques aim to save energy by selectively turning off BSs during ―off-peak‖ hours.

As shown in Fig. 2, BSs consume the highest proportion of energy in cellular networks. On

the other hand, dense BSs deployments today lead to small coverage area and more random

traffic patterns for individual BS, which make sleep mode operations more desirable. The

sleep mode techniques are based on current architecture, they have the advantage of being

easier to test and implement as no replacement of hardware is required and the performance

can be evaluated by computer simulation. One more practically implementable switching on –

off based energy saving algorithm (SWES) that can be operated in a distributed manner with

low computational complexity. [34].

2.3. Optimizing energy efficiency

In the current cellular network architecture based on WCDMA/HSPA, BSs and mobile

terminals are required to continuously transmit pilot signals. Newer standards such as LTE,

LTE-Advanced and WiMAX have evolved to cater ever-growing highspeed data traffic

requirements. With such high data requirements, although BSs and mobile units (MU)

employing newer hardware (such as multiple-input and multiple-output (MIMO) antennas)

increase spectral efficiency allowing to transmit more data with the same power, power

consumption is still a significant issue for future highspeed data networks and they require

energy conservation both in the hardware circuitry and protocols. A fairly intuitive way to

save power is to switch off the transceivers whenever there is no need to transmit or receive.

The LTE standard utilizes this concept by introducing power saving protocols such as

discontinuous reception (DRX) and discontinuous transmission (DTX) modes for the mobile



handset. DRX and DTX are methods to momentarily power down the devices to save power

while remaining connected to the network with reduced throughput. Continuous transmission

and reception in WCDMA/HSPA consumes significant amount of power even if the transmit

powers are far below the maximum levels, and therefore power savings due to DRX and DTX

is an attractive addition. IEEE 802.16e or Mobile WiMAX also has similar provisions for

sleep mode mechanisms for mobile stations [35]. The device negotiates with the BS and the

BS will not schedule the user for transmission or reception when the radio is off. There are

three power-saving classes with different on/off cycles for the WiMAX standard.

Unfortunately, such powers saving protocols for BSs have not been considered in the current

wireless standards. The traffic per hour in a cell varies considerably over the time and BS scan

regularly be under low load conditions, especially during the night time. In wireless standards,

energy saving potential of BSs needs to be oppressed by designing protocols to enable sleep

modes in BSs in the future. The authors in [36] suggest making use of downlink DTX

schemes for BSs by enabling micro-sleep modes (in the order of milliseconds) and deep-sleep

modes (extended periods of time). Switching off inactive hardware of BSs during these sleep

modes can potentially save a lot of power, especially under low load conditions [6].

2.4. Deploying heterogeneous cells

The next category tackles the problem by deploying small cells, including micro, pico and

femto cells, in the cellular network [37]. These smaller cells serve small areas with dense

traffic with low power-consuming cellular BSs (e.g., [26], [38]–[45]), which are affordable for

user-deployment and usually support plug-and-play feature. The area covered by base station

signals is called cell [3]. Based on the amount of area covered the base stations can be

classified as Macro cell base station, Micro cell base station, Pico cell station and Femto cell

base station. Femto cells cover the smallest area and they are deployed in a room. Pico cells

are deployed in offices or shopping malls and they cover more area than femto cells. Micro

cells can cover blocks of buildings in an urban locality and cover area more than pico cells.

Macro cells cover the largest area among all the cells and generally they are deployed in rural

areas or on high ways. [46] In contrast to conventional homogeneous macro cell deployment,

such heterogeneous deployment reduces energy consumption in the network by shortening the

propagation distance between nodes in the network and utilizing higher frequency bands to

support higher data rates. The major constraint of these approaches is the extra small cells

bring additional radio interferences as compared to conventional homogeneous macro cell

networks, which might negatively affect user experience.

2.5. Renewable Energy Sources

The last category includes approaches that adopt renewable energy resources. Compared to

current widely used energy resources such as hydrocarbon which produces greenhouse gases,

renewable resources such as hydro, wind and solar power stand out for their sustainability and

environmental friendliness [47], [48]. Telecom manufacturers have planned the supply of

solar power operated cellular BSs in under developed areas such as Bangladesh and Nigeria,

where roads are in poor condition and unsafe, so delivering traditional energy resources for

off grid BSs (e.g., diesel) cannot be guaranteed [49], [50]. Energy harvesting techniques,

namely exploiting available energy from such renewable resources to complement existing

electrical infrastructure will be the long term environmental solution for the mobile cellular

network industry.



Table 2 Comparison of Various Techniques for Energy Reduction

S.No Methods References Advantages

1.

Hardware

Compone

nts

Z. Hasan, H.

Boostanimehr,

and V. K.

Bhargava Ref

[6]

Upto 70%

reduced using

switch mode

power

amplifiers

2.

Flexi

Base

station

Chethana R

Murthy Ref

[13]

Up to 70%

reduction in

site power

Consumption

3. Tower

Tube

Chethana R

Murthy Ref

[13]

Reduction in

feeder loss,

Incrase the

network

Capacity.

4.

Base

station

Sleeping

E. Oh, K. Son,

and B.

Krishnamacha

ri Ref [34}

Upto 80%

energy saving

5.

Cell

Deployme

nt

Z. Hasan, H.

Boostanimehr,

and V. K.

Bhargava Ref

[6]

up to 60%

savings

compared to a

network with

macro-cells

6.

Renewabl

e Energy

Sources

Mohammed

H. Alsharif

and Jeong Kim

Ref [64]

up to 0.35%

of global

diesel

consumption

In general, green cellular network is a relatively new area of research. Most of existing

publications are based on ideal models. The fundamental aim, as its name implies, is to make

cellular networks ―greener‖ by reducing total power consumption through various approaches

described above.

3. THE GREEN METRICS MEASUREMENT

The notation of ―green‖ technology in wireless systems can be made evocative with a

comprehensive evaluation of energy savings and performance in a practical system. This is

where energy efficiency metrics play an important role. These metrics provide information in

order to directly compare and evaluate the energy consumption of various components and the

overall network. In addition, they also help us to set long term research goals of dropping

energy consumption. With the upsurge in research activities relating to green communications

and hence in number of diverse energy efficiency metrics, standards organizations such as

European Technical Standards Institute (ETSI) and Alliance for Telecommunications Industry

Solutions (ATIS) are currently making efforts to define energy efficiency metrics for wireless

networks [51], [52]. In general, energy efficiency metrics of telecommunication systems can

be classified into three main categories: facility-level, equipment-level and network-level

metrics [53], [54]. Facility-level metrics relates to high-level systems where equipment is

deployed (such as data centres, ISP networks etc.), equipment level metrics are defined to

evaluate performance of an individual equipment, and network level metrics assess the

performance of equipment while also bearing in mind features and properties related to

capacity and coverage of the network. The Green Grid (TGG) association of IT professional’s



first proposed facility-level efficiency metrics called PUE (Power Usage Efficiency) and its

reciprocal DCE (Data Centre Efficiency) in [55] to evaluate the performance of power

hogging data centres. PUE which is defined as the ratio of total facility power consumption to

total equipment power consumption is although a good metric to quickly assess the

performance of data centres at a macro level, it fails to account for energy efficiency of

individual equipment. Therefore, in order to quantify efficiency at the equipment level, ratio

of energy consumption to some performance measure of a communication system would be

more appropriate. However, grading the performance of a communication system is more

challenging than it actually first appears, because the performance comes in a variety of

different forms (spectral efficiency, number of calls supported in block of time, etc.) and each

such performance measure affects this efficiency metric very differently. Some suggested

metrics including power per user (ratio of total facility power to number of users) measured in

[Watt/user], and energy consumption rating (ECR) which is the ratio of normalized energy

consumption to effective full-duplex throughput and is measured in [Watt/Gbps] [56]. While

power per user can be a useful metric for a network provider to evaluate economic trade-offs,

network planning etc., metrics such as ECR provide the manufacturers a better insight into

performance of hardware components. However, even the busiest networks do not always

operate on full load conditions, therefore it would be useful to complement metrics such as

ECR to incorporate the dynamic network conditions such as energy consumption under full-

load, half-load and idle cases. In this regard, other metrics such as ECRW (ECR-weighted),

ECR-VL (energy efficiency metric over a variable-load cycle), ECR-EX (energy efficiency

metric over extended-idle load cycle), telecommunications energy efficiency ratio (TEER) by

ATIS, Telecommunication Equipment Energy Efficiency Rating (TEEER) by Verizons

Networks and Building Systems consider total energy consumption as weighted sum of

energy consumption of the equipment at different load conditions [56], [57], [58], [59]. As an

example, for TEEER, the total power consumption Ptotal is calculated by the following

formula

Ptotal = 0.35Pmax + 0.4P50 + 0.25Psleep, (1)

where Pmax, P50 and Psleep, are power consumption at full rate, half-rate and sleep

mode, respectively, and the weights are obtained statistically. However, these metrics such as

ECR, TEER, TEEER etc. are unable to capture all the properties of a system and research

work is still active to suggest different types of metrics. [9]

Table 2 Units of Energy Efficiency Metrics at Various Levels

Metric Units Type

PUE (Power Usage efficiency) Ratio Facility – level

DCE (Data Centre efficiency) Percentage Facility – level

Telecommunication Energy

Efficiency Ratio (TEER) Gbps/Watt Equipment – level

Energy Consumption

Rating(ECR) Watt/Gbps Equipment – level

ECR – Weighted (ECRW) Watt/Gbps Equipment – level

ECR – Variable load (ECR-

VL) Watt/Gbps Equipment – level

Performance Indicator in rural

areas (PIrural) Km2/watt Network-Level

Performance Indicator in urban

areas (PIurban) Users/watt Network-Level



4. ENERGY EFFICIENCY METRICS FOR BASE STATION SITES

Energy efficiency has become an important issue for base station sites, where specific

performance metrics, requirements and technologies to improve energy efficiency must be

taken into consideration. For site infrastructure, a simple metric used to verify the efficiency

of base station site facilities is considered sufficient and has the advantage of being relatively

simple to calculate as well as allowing remote measurements to be carried out. Renewable

energy usage is considered an important factor to reduce the effect of climate change.

Consumption of more energy from renewable sources including local or dedicated grid power

and the use of fuels with lower carbon contents are ways to reduce carbon emissions.

Electricity from renewable energy sources shall be included in the total energy consumption

on site. The site energy efficiency (SEE) metric described in ITU-T Recommendations helps

mobile network operators (MNOs) to assess important sustainability aspects on cell sites as

well as helping them to compare results and determine opportunities to increase energy

efficiency or reduce power consumption.

The total energy consumption of the base station site will include the grid electricity as

well as local energy sources such as diesel generators or solar systems.

4.1. Base station site energy efficiency assessment

Figure 4 shows a base station site diagram illustrating the energy measurement points

considered in ITU-T Recommendations.

Figure 3 An example of a radio base station site with energy flow and measurement points

Figure 4 does not take into account the fact that the power system is always a separate

entity with respect to the telecom equipment, nor does it take into account the following

configurations:

The AC/DC conversion may be integrated into the telecom part and the air cooling

unit may be not present, e.g., for a pole mounted base station site.

The battery may be present if power backup is required.

Multiple functions (telecom AC/DC conversion, battery and cooling) may be

integrated in a single box as is typical for outdoor equipment.

Functions may be realized as separate physical units.

Site energy efficiency metric definition Site energy efficiency (SEE) represents the site

efficiency of the measured site. Site energy efficiency (SEE) is the ratio between the total

energy consumption of telecommunication equipment and the total energy consumption on

site.



SEE = ECT/ ETS ×100% (2)

The definition proposed here is selected employing the same philosophy as the power

usage effectiveness (PUE) indicator used in data centre technologies. The total energy

consumption of telecommunication equipment is indicated as ECT in Figure 3. ECT is the

energy consumption of telecommunications equipment present in the base station site under

consideration during the measurement time period. ETS is the sum of different input energy

sources such as from a public grid, a diesel generator present on the site or from a different

type of local generator or a renewable energy source, etc.

ETS = EGE +EFE (3)

where ECT is the energy consumption of telecommunications equipment present in the

base station site under consideration during the measurement time period.

EGE is the input electric energy (in kWh) from the public grid during the measurement

time period

EFE is locally produced electrical energy (in kWh) generated by a genset or other type of

local generator with a renewable energy source on the site during the measurement time

period. [63]

5. OPTIMAL POWER SYSTEM FOR MOBILE BASE STATION

Currently, there has been an observed extraordinary growth in the number of mobile

subscribers in rural areas, which has prompted mobile network operators to expand their

cellular networks to provide mobile service to subscribers in rural areas, increasing the

profitability of the operators [65]. However, operational expenditures and greenhouse gas

emissions are a major concern of the mobile network operators because diesel generators are

typically used to power the off-grid cellular base stations in remote areas [66], which

challenge mobile network operators to find an economically feasible alternative power source

that is also environmentally friendly. With the current progress in renewable energy, the key

features of a power source, such as the cost effectiveness, sustainability, and reliability, as

well as reduction of the greenhouse gas emissions, can be met [64].

In recent years, society’s energy demands are fulfilled using conventional energy sources

such as water, coal, oil, natural gases or uranium. The production of energy using these

conventional sources is a cause of concern of many environmentalists. The major problems

can be quoted as follows:

It causes atmospheric pollution, climate changes or nuclear waste and thus can

endanger our living condition on the earth.

The extensive use of these limited conventional energy sources may result in

complete depletion of energy sources and hence, there is no guarantee of energy

supply for future.

The above-mentioned problems can be solved by using renewable energy sources such as

Sun and Wind. The renewable energy sources use natural resources and do not cause any

pollution. Hence, they are termed as Green Energy sources. Moreover, these renewable

energy sources only use a small part of the flow that is why they cannot damage natural

surrounding and also do have the risk of being depleted.[46]

Traditional Global System for Mobile communications (GSM) equipment is targeted to

the urban environments only. Vendors and operators of the GSM equipment have been facing

difficulty to meet certain challenges in remote rural areas such as it costs much, expensive to

run, uses much power and is difficult in deploying in rural areas with limited electricity



supply, lack of skilled engineers and poor roads. Hence it is very important to take into

consideration all these problems before deploying solar powered base stations.

It is very essential to get an estimate of not only the number of the photovoltaic (PV) cells,

inverters, batteries and generators required but also the cost of production of energy per unit

before the actual deployment of the solar powered base stations. In order to do so it is always

suggested to design and simulate the deployable solar powered base stations using software.

The average daily solar radiation in Chennai, which is located at latitude between 130 N

latitude and 800 E longitude, is estimated to be 5.32 kWh m−2 and varies from 4.09 kWh m

−2

in December to 6.51kWh m−2

in April. [67]

Figure 4 Monthly Average Global irradiance at 130 N latitude and 80

0 E longitude

According to figure (5), this study attempts to determine the criteria for the solar energy

systems for different values of solar radiation to cover all possible areas of Chennai: 5.4 – 5.6

kWh m−2. The monthly average solar radiation values used in this study are obtained from

the NASA Surface Solar Energy using the longitude and latitude of Chennai.

5.1. SYSTEM MODEL

A typical model of a solar energy system integrated with an LTE-macro base station is shown

in Figure 6. The solar panels feed the required energy to the LTE-macro base station.

However, in case of the malfunction of the solar panels, resulting in an inability to provide the

energy required to the LTE-macro base station, the battery bank compensates for the shortage

of energy. If the battery bank reaches its maximum depth of discharge (DOD) and loses the

ability to supply the LTE-macro base station the required energy, backup diesel generator

supplies energy to the LTE-macro base station. Hence, the diesel generator is suggested as a

backup power source to secure the power supply during maintenance or in case of a

malfunction in the system. The static switch monitors the power of the solar power system. If

the output power is less than required to meet the AC loads, the AC loads switch to draw

energy from the backup diesel generator.



Figure 5 A model of a solar energy system integrated with an LTE-macro base station

The elements of the solar power system are listed below; these elements are designed for

easy installation and disassembly. Moreover, due to the significant development in solar

technology, these components are designed with high efficiency and low losses to contribute

to energy saving.

a. Solar panels: absorb shortwave irradiance and convert it into direct current (DC)

electricity.

b. Solar regulator charger: control unit responsible for the regulation of the

unregulated DC output voltage of the solar array to regular DC voltage that is

compatible with the load and the battery. In this study, the DC load (LTE-macro

base station) voltage is 48 Vdc.

c. Batteries: store excess energy from the solar arrays to be used at night or when the

power output of the solar panels is not sufficient to cover the LTE-macro base

station load. A charge control unit is added to protect the batteries by regulating

the charging and discharging process and maintaining the battery lifecycle.

d. Inverter: converts the 48 DC voltage of the DC bus-bar into 220 alternating current

(AC) voltage that is used to feed the AC load in the base station.

e. Control unit: key element in the solar power system that manages and controls the

power flow of the different elements in the solar power system to meet the

demands of the LTE-macro base station load.



Figure 6 Grid – connected solar power system CO2

The implementation of a Grid – connected solar power system within the PVSYST

simulation software and the configurations for the various elements in the system are shown

in Figure 7. The system design for standalone system is more complicated compare to grid

connected as the standalone system contains batteries and generators apart from inverters and

PV modules. This adds extra constraint to the design.

Grid connected systems are suitable if the supply of solar energy is reliable. In other

words, it is suggested to use grid connected system in summer in India. If the supply of solar

energy is not reliable like during monsoon season in India then it is suggested to use

standalone system though it is costly compare to grid connected system. Hence there is

always trade-off between reliability and cost efficiency while deploying solar powered

cellular base stations.

6. CONCLUSION

In this paper, the inclusive survey of current green techniques for mobile networks with their

merits and demerits. Also, this paper has surveyed recent progression in the research of BS

sleep mode methods in cellular networks, which is one of the major methods to reduce total

energy consumption, have presented. Growing energy consumption has been a major concern

and many revisions on energy saving approaches in networking and telecommunication

sectors have been published after the first work concerning the energy issue in the main

stream networking area published in 2003, which refers to the greening of the Internet [68].

The fact that cellular networks were designed with the main goal of maximum throughput and

coverage indicates significant advances are possible by effective power managing schemes. It

is now widely accepted that the energy consumption reduction in cellular networks will bring

both operating profit for mobile operators and environmental benefit for the planet. In



summary, the sleep mode technologies as well as the whole green cellular network are

auspicious areas of research. It will undoubtedly remain a popular research topic for the

coming years, since there is bright potential as well as issues waiting to be solved.

REFERENCES

[1] Energy-Efficient Base-Stations Sleep-Mode Techniques in Green Cellular Networks: A

Survey Jingjin Wu, Yujing Zhang, Moshe Zukerman, Fellow, IEEE, and Edward Kai-

Ning Yung, Fellow, IEEE. IEEE communication surveys & Tutorials, Vol.17 N0.2,

second quarter 2015.

[2] GreenTouch. [Online]. Available: http://www.greentouch.org/

[3] Int. Telecommun. Union, ―ITU Green Standards Week,‖ Geneva, Switzerland, Sep. 2011.

[Online]. Available: http://www.itu.int/ITU-T/ climatechange/gsw/201102/index.html

[4] G. Fettweis and E. Zimmermann, ―ICT energy consumption—Trends and challenges,‖ in

Proc. 11th Int. Symp. Wireless Pers. Multimedia Commun., Lapland, Finland, Sep. 2008,

pp. 1–4.

[5] O. Blume, H. Eckhardt, S. Klein, E. Kuehn, and W. M. Wajda, ―Energy savings in mobile

networks based on adaptation to traffic statistics,‖ Bell Labs Tech. J., vol. 15, no. 2, pp.

77–94, Sep. 2010.

[6] Z. Hasan, H. Boostanimehr, and V. K. Bhargava, ―Green cellular networks: A survey,

some research issues and challenges,‖ IEEE Commun. Surveys Tuts., vol. 13, no. 4, pp.

524–540, 2011.

[7] Y. Zhang, P. Chowdhury, M. Tornatore, and B. Mukherjee, ―Energy efficiency in telecom

optical networks,‖ IEEE Commun. Surveys Tuts., vol. 12, no. 4, pp. 441–458, 2010.

[8] A. P. Bianzino, C. Chaudet, D. Rossi, and J. Rougier, ―A survey of

greennetworkingresearch,‖IEEECommun.SurveysTuts.,vol.14,no.1, pp. 3–20, 2012.

[9] Green Cellular Networks: A Survey, Some Research Issues and Challenges Ziaul Hasan,

Student Member, IEEE, Hamidreza Boostanimehr, Student Member, IEEE, and Vijay K.

Bhargava, Fellow, IEEE

[10] Performance analysis of green cellular networks with selective base-station sleeping,

Jingjin Wu, Eric W.M. Wong, Jun Guo, Moshe Zukerman. Performance Evaluation

(2017), http://dx.doi.org/10.1016/j.peva.2017.03.002

[11] M. Ismail, W. Zhuang, E. Serpedin, K. Qaraqe, A survey on green mobile networking:

From the perspectives of network operators and mobile users, IEEE Communications

Surveys and Tutorials 17 (3) (2015) 1535– 1556. doi:10.1109/COMST.2014.2367592.

[12] S. Tombaz, K. W. Sung, S. wook Han, J. Zander, An economic viability analysis on

energy-saving solutions for wireless access networks, Computer Communications 75

(2016) 50 – 61. doi:http://dx.doi.org/10.1016/j.comcom.2015.10.005.

[13] A Survey of Green Base Stations in Cellular Networks Chethana R Murthy, Dr. C

Kavitha IRACST – International Journal of Computer Networks and Wireless

Communications (IJCNWC), ISSN: 2250-3501 Vol.2, No.2, April 2012

[14] M. Deruyck, et. Al., ―Power consumption in wireless access networks‖, in Proceedings-

European Wireless Conference, April 2010 [

[15] White paper – Green Radio ―NEC’s Approach towards Energy-efficient Radio Access

Networks‖ February 2010, NEC Corporation

[16] http://www.nokiasiemensnetwroks.com/portfolio/products/mobile broadband/ single-ran-

advanced/flexi-muli radio-base station

[17] D. Kimball et al., ―High-efficiency WCDMA envelope tracking base station amplifier

implemented with GaAs HVHBTs,‖IEEE J.Solid-State Circuits, vol. 44, no. 10, pp. 2629–

2639, Oct. 2009.

http://dx.doi.org/10.1016/j.peva.2017.03.002

http://www.nokiasiemensnetwroks.com/portfolio/products/mobile%20broadband/



[18] K. Cho, J. Kim, and S. Stapleton, ―A highly efficient Doherty feedforward linear power

amplifier for W-CDMA base station applications,‖ IEEE Trans. Microw. Theory Techn.,

vol. 53, no. 1, pp. 292–300, Jan. 2005.

[19] O. Arnold, F. Richter, G. Fettweis, and O. Blume, ―Power consumption modelling of

different base station types in heterogeneous cellular networks,‖ in Proc. Future Netw.

Mobile Summit, Dresden, Germany, Jun. 2010, pp. 1–8.

[20] Y. Wei, J. Staudinger, and M. Miller, ―High efficiency linear GaAs MMIC amplifier for

wireless base station and femto cell applications,‖ in Proc. IEEE Topical Conf. PAWR,

Tempe, AZ, USA, Jan. 2012, pp. 49–52.

[21] C. Han et al., ―Green radio: Radio techniques to enable energy-efficient wireless

networks,‖ IEEE Commun. Mag., vol. 49, no. 6, pp. 46–54, Jun. 2011.

[22] H. Claussen, L. Ho, and F. Pivit, ―Effects of joint macrocell and residential picocell

deployment on the network energy efficiency,‖ in Proc. IEEE 19th Int. Symp. PIMRC,

Sep. 2008, pp. 1–6.

[23] TriQuint, ―RF Power Amplifier Module: TGA2450-SM.‖ [Online]. Available: http://store.triquint.com/ProductDetail/TGA2450-SMTriQuint-Semiconductor-Inc/472292/

[24] ―Multiradio Base Station makes network evolution easier and greener than ever‖, Press

Release Feb 5 2009, Nokia Siemens Networks. Available at: http://www.nokiasiemensnetworks.com/sites/defaul t/files/document/NokiaSiemensNetworks 2009

02 05 enFlexiMultiradioBTS.pdf

[25] http://www.ericsson.com/ourportfolio/products/eric sson-tower-tube

[26] O. Arnold, F. Richter, G. Fettweis, and O. Blume, ―Power consumption modelling of

different base station types in heterogeneous cellular networks,‖ in Proc. Future Netw.

Mobile Summit, Dresden, Germany, Jun. 2010, pp. 1–8.

[27] J. Wu, S. Zhou, and Z. Niu, ―Traffic-aware base station sleeping control and power

matching for energy–delay tradeoffs in green cellular networks,‖ IEEE Trans. Wireless

Commun., vol. 12, no. 8, pp. 4196–4209, Aug. 2013.

[28] J. Louhi, ―Energy efficiency of modern cellular base stations,‖ in Proc. 29th INTELEC,

Sep./Oct. 2007, pp. 475–476.

[29] P. Frenger, P. Moberg, J. Malmodin, Y. Jading, and I. Godor, ―Reducing energy

consumption in LTE with cell DTX,‖ in Proc. IEEE 73rd VTC Spring, Linkoping,

Sweden, May 2011, pp. 1–5.

[30] I. Ashraf, F. Boccardi, and L. Ho, ―Sleep mode techniques for small cell deployments,‖

IEEE Commun. Mag., vol. 49, no. 8, pp. 72–79, Aug. 2011.

[31] Micallef, P. Mogensen, and H. Sch, ―Cell size breathing and possibilities to introduce cell

sleep mode,‖ in Proc. EW Conf., Lucca, Italy, Apr. 2010, pp. 111–115.

[32] R. Li, Z. Zhao, X. Chen, J. Palicot, and H. Zhang, ―TACT: A Transfer Actor-Critic

learning framework for energy saving in cellular radio access networks, ‖IEEE Trans.

Wireless Commun.,vol.13,no.4,pp.2000– 2011, Apr. 2014.

[33] M. A. Marsan, L. Chiaraviglio, D. Ciullo, and M. Meo, ―On the effectiveness of single

and multiple base station sleep modes in cellular networks,‖ Comput. Netw., vol. 57, no.

17, pp. 3276–3290, Dec. 2013.

[34] Dynamic base station switching on /off strategies for green cellular networks E. Oh, K.

Son, and B. Krishnamachari, IEEE Trans. Wireless Commun., vol. 12, no. 5, pp. 2126–

2136, May 2013.

[35] M. J. Chang, Z. Abichar, and Chau-Yun Hsu, ―WiMAX or LTE: Who will Lead the

Broadband Mobile Internet?,‖ IT Professional , vol.12, no.3, pp.26-32, May-June 2010.

[36] L. M Correia, et. al, ―Challenges and enabling technologies for energy aware mobile radio

networks,‖ IEEE Communications Magazine, vol.48, no.11, pp.66-72, November 2010.

http://store.triquint.com/ProductDetail/TGA2450-SMTriQuint-Semiconductor-Inc/472292/

http://www.nokiasiemensnetworks.com/sites/defaul%20t/files/document/NokiaSiemensNetworks%202009%2002%2005%20enFlexiMultiradioBTS.pdf

http://www.nokiasiemensnetworks.com/sites/defaul%20t/files/document/NokiaSiemensNetworks%202009%2002%2005%20enFlexiMultiradioBTS.pdf



[37] V. Chandrasekhar, J. Andrews, and A. Gatherer, ―Femtocell networks: A survey,‖IEEE

Commun. Mag., vol. 46, no. 9, pp. 59–67, Sep. 2008.

[38] H. ElSawy, E. Hossain, and M. Haenggi, ―Stochastic geometry for modeling, analysis,

design of multi-tier and cognitive cellular wireless networks: A survey,‖ IEEE Commun.

Surveys Tuts., vol. 15, no. 3, pp. 996– 1019, 2013.

[39] A. R. Ekti, M. Z. Shakir, E. Serpedin, and K. A. Qaraqe, ―Downlink power consumption

of HetNets based on the probabilistic traffic model of mobile users,‖ in Proc. IEEE 24th

Int. Symp. PIMRC, Sep. 2013, pp. 2797–2802.

[40] F.Richter,A.Tehske,andG.Fettweis,―Energyefficiencyaspectsofbase station deployment

strategies for cellular networks,‖ in Proc. IEEE 70th VTC Fall, Sep. 2009, pp. 1–5.

[41] W. Guo and T. O’Farrell, ―Green cellular network: Deployment solutions,sensitivity and

tradeoffs,‖inProc.WiAd,London,U.K.,Jun.2011, pp. 42–47.

[42] H. Claussen, I. Ashraf, and L. Ho, ―Dynamic idle mode procedures for femtocells,‖ Bell

Labs Tech. J., vol. 15, no. 2, pp. 95–116, Sep. 2010.

[43] S. Bhaumik, G. Narlikar, S. Chattopadhyay, and S. Kanugovi, ―Breathe tostay cool: cell

sizes to reduce energy consumption,‖in Proc. 1st ACMSIGCOMM Workshop Green

Netw. ,Aug./Sep.2010,pp.41–46.

[44] C. Li, J. Zhang, and K. Letaief, ―Energy efficiency analysis of small cell networks,‖ in

Proc. IEEE ICC, 2013, pp. 4404–4408.

[45] A. Mukherjee, S. Bhattacherjee, S. Pal, and D. De, ―Femtocell based green power

consumption methods for mobile network,‖ Comput. Netw., vol. 57, no. 1, pp. 162–178,

Jan. 2013. [Online]. Available: http://www. Science direct .com /science /article /pii /

S1389 1286 12003295

[46] A Case Study of Solar Powered Cellular Base Stations, Geetha Pande.

[47] I.H.Rowlands, P. Parker, and D. Scott,―Consumer perceptions of ―green power‖,‖ J.

Consum. Marketing, vol. 19, no. 2, pp. 112–129, 2002.

[48] Y.-K. Chia, S. Sun, and R. Zhang, ―Energy cooperation in cellular networks with

renewable powered base stations,‖ in Proc. IEEE WCNC, Apr. 2013, pp. 2542–2547.

[49] Y.Chan ―China’s Huawei to supply solar powered base - stations to Bangladesh,‖

Business Green, London, U.K., Aug. 2009. [Online]. Available:

http://www.businessgreen.com/bg/news/1802444/ chinas-huawei-supply-solar-powered-

base-stations-bangladesh

[50] C. Okoye, ―Airtel base stations to be solar powered,‖ Daily Times Nigeria, Lagos,

Nigeria, Dec. 2011. [Online]. Available: http://dailytimes. com.ng/article/airtel-base-

stations-be-solar-powered.

[51] Alliance for Telecommunications Industry Solutions, ―ATIS Report on Wireless Network

Energy Efficiency‖, ATIS Exploratory Group on Green (EGG), Jan. 2010.

[52] European Telecommunications Standards Institute, Environmental Engineering (EE)

Energy Efficiency of Wireless Access Network Equipment, ETSI TS 102 706, v1.1.1,

Aug. 2009.

[53] A. P. Bianzino, A. K. Raju, and D. Rossi, ―Apple-to-Apple: A framework analysis for

energy-efficiency in networks,‖ Proc. of SIGMETRICS, 2nd GreenMetrics workshop,

2010. [54] T. Chen, H. Kim, and Y. Yang, ―Energy efficiency metrics for green wireless

communications,‖ 2010 International Conference on Wireless Communications and

Signal Processing (WCSP), pp.1-6, 21-23 Oct. 2010.

[54] C. Belady, et al., ―Green Grid Data Center Power Efficiency Metrics: PUE and DCIE,‖

The Green Grid, 2008.

[55] The Energy Consumption Rating Initiative, ―Energy Efficiency for Network Equipment:

Two Steps Beyond Greenwashing‖, White Paper, August 10 2008. Available:

http://www.ecrinitiative.org/pdfs/ECR TSBG 1 0.pdf



[56] The Energy Consumption Rating Initiative, ―Network and Telecom Equipment-Energy

and Performance Assessment‖, Draft 3.0.1, December 14, 2010. Available:

http://www.ecrinitiative.org

[57] Transmittal of ATIS Energy Efficiencies Specifications. Available:

http://www.itu.int/md/dologin md.asp?lang=en&id=T09-FG.ICT-IL0003!!MSW-E.

[58] Verizon NEBS Compliance: Energy Efficiency Requirements for Telecommunications

Equipment, Issue 4, August 2009. Available: http://www.verizonnebs.com/TPRs/VZ-TPR-

9205.pdf.

[59] EARTH, ―EARTH Deliverable D2.4 Aware Radio Netw. Technol., Most suitable

efficiency metrics and utility functions,‖ Jan. 2012. [Online]. Available: https://bscw.ict-

earth.eu/pub/bscw.cgi/d70454/ EARTH_WP2_D2.4.pdf

[60] European Telecommunications Standards Institute, Environmental Engineering (EE)

Energy Efficiency of Wireless Access Network Equipment, ETSI TS 102 706, v1.1.1,

Aug. 2009

[61] S. Morosi, P. Piunti, and E. Del Re, ―Improving cellular network energy efficiency by

joint management of sleep mode and transmission power,‖ in Proc. 24th TIWDC—Green

ICT, Sep. 2013, pp. 1–6.

[62] Energy efficiency metrics of a base station site, Recommendation ITU-T L.1350

[63] Optimal Solar Power System for Remote Telecommunication Base Stations: A Case

Study Based on the Characteristics of South Korea’s Solar Radiation Exposure

Mohammed H. Alsharif * and Jeong Kim

[64] Alsharif, M.H.; Nordin, R.; Ismail, M. Classification, recent advances and research

challenges in energy efficient cellular networks. Wirel. Pers. Commun. 2014, 77, 1249–

1269.

[65] Kusakana, K.; Vermaak, H.J. Hybrid Renewable Power Systems for Mobile Telephony

Base Stations in Developing Countries. Renew. Energy 2013, 51, 419–425.

[66] http://www.google.com/search?hl=en&source=hp&q=pvsyst+v4.33&rlz=1R2ADRA_enS

E336&aq= 7&oq=PVSYS&aqi=g3g-s1g6

[67] M. Gupta and S. Singh, ―Greening of the Internet,‖ in Proc. ACM SIGCOMM, Karlsruhe,

Germany, Aug. 2003, pp. 19–26.

http://www.verizonnebs.com/TPRs/VZ-TPR-9205.pdf

http://www.verizonnebs.com/TPRs/VZ-TPR-9205.pdf

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