Techniques for Minimizing Power Consumption of Base Transceiver ...

Techniques for Minimizing Power Consumption of Base Transceiver Station in Mobile Cellular Systems N. Faruk, A.A Ayeni, M. Y. Muhammad, L.A.Olawoyin, A. Abdulkarim, J. Agbakoba, M. O. Olufemi

Techniques for Minimizing Power Consumption of Base Transceiver Station in Mobile Cellular Systems 1

N. Faruk*, 2A.A Ayeni, 3M. Y. Muhammad, 4L.A.Olawoyin, 5A. Abdulkarim, 6 J. Agbakoba, 7M. O. Olufemi 1,2,3,4 Department of Telecommunication Science, University of Ilorin, Nigeria Email: {faruk.n, ayeni, olawoyin, mujahid}@unilorin.edu.ng 5 Department of Electrical and Electronics Engineering, University of Ilorin, Nigeria 5 abdulkarim.aunilorin.edu.ng 6 RF Department, MTN, Nigeria 6 [email protected] 7 RF planning and optimization, Huawei Technologies Co, Ltd, Nigeria 7 [email protected]

Abstract Physical limitations of the wired line communication systems in satisfying the ever increasing demands seem to be in favour of wireless systems. Wireless systems have been firmly established as a key and convenient means of communication that enables efficient and effective business operation. The power consumption of wireless access networks has therefore, remain a major economic and environmental issue. This paper investigates power consumption of base transceivers stations (BTS), schemes that could potentially decrease the power consumption and the potential of reusing the conserved power without compromising quality of service (QoS) of the network explored. Analysis of results shows that, when 5% of the total sites for operator with 4700 sites are optimized, using SISO (Single Input Single Output) technique, 578.1KW of power would be reserved for all transceivers (TRX). While, optimizing the sites with MIMO (Multiple Input Multiple Output) technique, 680.748KW of power would be reserved when sites with 1TRX are optimized, this increase to 1.1MW of power when sites with 6TRX per sector are optimized representing 43% increase in reserve power. It was found that, the reserved power could be used to power extra sites to reduce the cost of power production and it is also noted that the number of extra sites that the reserved power can power varies as a function of number of TRX the site has and this depends exclusively on the optimization techniques employed and the type of sites optimized. New performance metric representing power efficiency gain (PEG) was introduced in the work. Key words: Base Transceivers Station (BTS), energy conservation, power consumption, access network

1. Introduction Physical limitations of the wired line communication systems in satisfying the ever increasing demands seem to be in favour of wireless systems. The consequent phenomenal growth in demand has led to a world-wide number of mobile subscribers to be 6 billion as at July 2010 and the demand for wireless technologies and services is increasing every year [1]. Wireless communication system is one of the most versatile technologies for contributing to social and economic development around the world. Studies identify the development of mobile communications as a significant contribution to sustainable GDP growth. In Nigeria, the penetration of mobile communication in the market has created job opportunities which contribute to the economic development [2]. At microeconomic level, the sector contribution to GDP increased by 53% in 2003 making it the third highest contributor ahead of the financial sector which has been in operation for about 100 years. In respect of employment, over 135, 000 persons have been directly or indirectly employed by the operators [2].

International Journal of Sustainability Volume 2, Number 1, June 2013 doi : 10.4156/ijs.vol2.issue1.1

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Protecting the environment, combating global climate changes and the need to reduce energy consumption are major issues currently challenging mankind. Research outcome shows that, 3% of worldwide energy is consumed by information and communications technology (ICT) infrastructure which causes about 2% of world-wide CO2 emissions. In comparison, airplanes contributed one quarter of world-wide emission [3]. In [4], the annual CO2 footprint of the average mobile subscriber is around 25kg which is comparable to driving a car on the motorway for one hour, or running a 5W lamp for a year. Today’s typical wireless access networks consumes more than 50% of the total power consumption of mobile communications networks which excludes the power consumed by the mobile stations (user terminals) whose more than 50% of energy consumption is directly attributed to the base station (BTS) equipment. However, reduction in energy consumption of mobile networks is of great importance from economical (cost reduction), environmental (decreased CO2 emissions) and efficiency perspectives. Hence, both reduction in energy consumption and CO2 emission are key drivers for the future of the ICT industry. In a recent report by the International Telecommunications Union (ITU) and Alliance for Telecommunications Industry Solutions (ATIS), a number of energy efficient practices and methods for consideration by companies seeking to achieve greater efficiencies within their wireless networks have been outlined. There are active research works on energy consumption, reduction and efficiency in wireless access networks, but issue relating to the reusability of the reserved energy has not been explicitly addressed. This paper investigates power consumption of base transceivers stations (BTS), schemes that could potentially decrease the power consumption were described and the potential of reusing the conserved power without compromising quality of service (QoS) of the network explored. The research also investigates the significance of deploying optimization techniques on energy efficiency. The paper is organized as follows; Section 2 provides the theoretical power consumption of base transceiver station, Section 4 gives the techniques for minimizing power consumption, simulation results in section 5 and finally, Section 6 concludes the paper.

2. Theoretical Power Consumption of Base Transceiver Station (BTS) Base Transceiver Station (BTS) - is a transceiver and acts as interface between the mobile stations (MS) to the network. A BTS will have between 1 and 16 Transceivers (TRX) [5], depending on the geography and demand for service of an area. Each TRX represents one ARFCN (Absolute radio frequency channel number). However, depending on geography, service demand and operator’s network strategy and architecture, a BTS may be host up to two, three or six sectors, or a cell may be serviced by several BTSs with redundant sector coverage. Each sector is covered by sector antenna, which is a directional antenna. Figure 1 shows typical macro BTS we found today.

Figure 1. Typical Macro cell Base Station 2


In Figure 1, there are several power consuming components. Some components are used per sector such as the digital signal processing (DSP) which is responsible for system processing and coding, the power amplifier, the transceiver which is responsible for generating the signal and also receiving signals to the mobile station and the rectifier as shown in Figure 2.The power consumption of such components should be multiplied by the number of sectors when determining the power consumption of BTSs [6]. Within these components the transceiver and the power amplifier are one per transmitting antenna. Other components such as the air conditioning and the microwave link, when no fiber link is available for backhaul, are common to all sectors. It is assumed that the power consumption of each component is constant except for the power amplifier and the air conditional system. For amplifier, the power consumption solely depends on the efficiency of the amplifier. The efficiency h is defined as the ratio of output power (in watts) pout to the input power (in watts) pin i.e;

h= If

pout pin

(1)

pTX is the input power of the sector antenna which is equal to the output power from the amplifier, then the

power consumption of the power amplifier (

p Amp ) can be obtained from the equation (2) p Amp =

Where,

PTX

(2)

h

p Amp = Pin and pout = pTX . One per transmitting antenna (TX)

Transceiver

Digital Signal Processing

Power Amplifier To Power

PTX Antenna

Rectifier

One per sectors

Grid PBTS Air Conditioning

Microwave Link (if Present)

Common to all sectors Figure.2. Block Diagram of Base Station Equipment

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In the case of the air conditioning system (AC), the power consumption varies with the internal and ambient temperature of the BTS cabinet. [6] [7] consider the ambient temperature to be 250C this is not always the case in Nigeria. The internal and ambient temperature varies with locations. Therefore, in this paper, when estimating power consumption of air conditioning system, the worst case temperature scenario is considered. In theoretical based power consumption, analytic model is developed to estimates the power consumption of a base station. Though in some cases, the estimation never gives the realistic power consumption but somehow approximations. [6], developed a model to determine the power consumption of base station. The model indicates that once the power consumption of individual components of the base station is known, the total power consumption could be evaluated. As a validation of their model, the power consumption of one sector base station with one antenna was found to be 761W this could only be achieved when the power consumption of AC of 225W as specified in the paper is used. In a typical situation in Nigeria BTSs, most sites use two AC, Incandescent Bulbs and more than one microwave units. Therefore, there is need to modify the model proposed to suite the realistic situations in Nigeria. In our proposed model, we include a relation that would take care of the number of ACs, microwave units and the incandescent bulbs as shown in equation (3)

PBTS = nsec tor * ( PDSP + nTR * ( PAmp + PTran ) + PRe c

n

) + å PAC

i

i

l

m

+ å Pmicro + å PLB j k

j

(3)

nsec tor Is the number of sectors in the cell, nTR is the number of transmitting antennas per sector and PBTS , PDSP , n

PAmp , PTran PRe c ,

å PACi i

m

l

åP

å Pmicro and

LB j

are the total power consumption of the base transceiver

j

k

station, the digital signal processing unit, the power amplifier, the transceiver, the rectifier, the air conditions, the microwave and incandescent bulbs respectively. Where n, l and m represents the total number of AC’s, microwaves in the BTS and bulbs in the site. The total energy consumption (EBTS) for the BTS is given in equation (4); this is the energy consumption of one site. EBTS =PBTS*t Where, t is the total time of usage (i.e. duration of power supply). Then the total energy consumption

(4) ( ET ) for

the all sites would be evaluated from equation (5) as follows: k

ET = å E i BTS

(5)

i

For

i = 1 to k and k > 0 . k is the number of sites in the network.

Table 1 gives the summary of power consumption of different components of the BTS. Some parameters value such as the power amplifier for SISO and MIMO and microwave were obtained from [6].

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Table1- Power Consumption of Different Components of the BTS EQUIPMENTS Digital signal processing Power amplifier (SISO)

POWER PDSP

PAmp(Max)

VALUE 100 W 12.8% 156W 11.5% 10.4W

PTrans PRec PAC PLB Pmicro

100 W 100 W 1170 W 60W 80W

h

PAmp(Max)

h

Power amplifier (MIMO)

Transceiver Rectifier Air conditioner (AC) Incandescent Bulb Microwave Link

3. Realistic Energy Consumption of BTS in Nigeria There are several factors that could affect the BTS power consumption; these include the traffic load which is time dependent function of number of subscribers and subscribers’ (consumer behaviour)1. Other factors could affects the power consumption of individual components which would subsequently alter the overall power consumption, some of them mentioned in section 2. This indicates that, the power consumption of individual BTS may vary with location area. Considering realistic power consumption for a typical mobile operator in Nigeria BTS, this includes both the transceivers and the microwave radio unit for 2G network some sites are used for backbone only. In the event of network upgrade, 3G network is sometimes collocated with 2G BTS to minimize cost and reduce space consumption. This is shown in Table 2. In Table 2, the power consumption for the site with 6 PDH (Plesiochronous Digital Hierarchy) and 2 SDH (Synchronous Digital Hierarchy) is 5868W and this decrease to 4478W for 1 PDH and site. Generally, the power consumption increase with increase in either microwave units or the number of transceivers. Table 2- Realistic Power Consumption of BTS in Nigeria CONFIGURATION/EQUIPMENTS 6 PDH RADIOS, 2 SDH RADIOS, (6TRX 900BAND, 12TRX 1800BAND) 1PDH RADIO, (2G 6TRX BAND, 12TRX 1800BAND) 5 PDH RADIO, 5 SDH RADIO, MUX, (6TRX 900BAND, 22TRX 1800BAND), 3G 1PDH RADIO, 2 SDH RADIO, (8TRX 900BAND) 2PDH, 2 SDH RADIO, MUX,( 14TRX 900, 22TRX 1800BAND), 3G 2G 9TRX 900BAND, 36TRX 1800BAND 2G 6TRX 900BAND 36TRX 1800BAND + 3G

Power (watts) 5868 4478 8460 6108 8460 7240 8580

4. Minimizing Power Consumption of Base Transceiver Station (BTS) Power consumption has drawn considerable attention from researchers across the world. In an attempt to improve energy efficiency in access networks, [8], investigated the impact of deployment strategies on the power consumption of mobile radio networks. They considered layouts featuring varying numbers of micro-base stations

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Subscribers’ behaviours are determined by numerous exogenous factors such as markets forces (e.g price, promotions), social forces (e.g. emergencies, social meetings) e.t.c 5


per cell in addition to conventional macro-sites. [9], shows the impact of air conditioning and transmission equipment while plotting the best areas of intervention for saving energy and improving environmental impact. [10], discusses the implementation of some important techniques like sleep scheduling, power saving algorithms for dynamic base stations as a means of achieving energy optimization and sustainability in wireless mobile networks. Energy efficiency could be improved by base station hardware efficiency i.e. if the efficiency of the power amplifier is increased the overall power consumption would decrease this is true as shown by equation (2) [11].The paper also outlined that deployment of MIMO (Multiple Input Multiple Output) systems would help in creating transmit diversity which would subsequently reduce the energy consumption. One way energy efficiency can also be improved is through main remote solution also known as tower top-mounted radios [4]. This can reduce energy consumption by two-thirds. In the traditional network deployment, all the radio base stations (RBS) equipment are located in a shelter or in an outdoor on the ground as shown in Figure 3 Alt 1. The radio units are connected to the antennas using feeder cables, which can be several tens of meters long. Typically half of the emitted power from the radio transmitters is lost in the feeders [4]. To improve the energy efficiency in the BTS, the main unit could now, as an alternative, be housed in an outdoor casing adjacent to the remote radio unit(s) on the tower as shown in Figure 3 Alt 2 this means that, either the input power can be halved, or the output power can be doubled for the same input. In addition, both site planning and Installations are simplified, as the RBS has virtually no footprint. Cooling systems such as the air conditioner units used to secure the battery lifetime are also eliminated, as the main unit can be cooled through natural convection.

Figure 3. Main Remote configurations [4] In this paper, the optimization techniques reported in [9][2][4] has been used to investigate the impact of reducing some power consumption components such as the air conditioning systems and the bulbs when employing tower top-mounted radios [4]. The effects of improving the efficiency of power amplifiers for both SISO and MIMO systems were investigated and how this affects the overall power consumption of the BTS. Let

G be the energy efficiency gain (PEG) this indicates how much as percentage power consumption decrease PBTS

when the system is optimized as compared to the conventional system without optimization. Then, PEG can be evaluated from the relation in (6):

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PEG =

Where

P G BTS/MIMO - P G BTS / SISO x100% P G BTS/MIMO

(6)

G G PBTS / MIMO and PBTS / SISO are the energy efficiency gain obtained over non optimized systemfor MIMO and

SISO systems respectively. If

B A and E BTS are respective energy consumption of the BTS before and after optimization, then reserved E BTS R

energy ( E BTS ) can be obtained from (7); R A B = E BTS - E BTS E BTS

And the overall reserved energy ( E

T BTS

) which indicates the total energy reserved of the optimized sites is given by; j

T R = = å ( E BTS E BTS i

For j £

(7)

) j

(8)

k , j and k are respectively, total number of optimized sites and total number of sites in the network.

5. Simulation Results In this paper, macro cells are considered and though, a site could consist of 2, 3 4 or 6 sectors, an average of 3 sector sites are assumed as majority of the sites in Nigeria are 3 sectored sites. The power consumption is evaluated using equation (3) and the parameters values stated in Table 1. The service providers are categorised into four; A, B, C and D. It is estimated that each operator has the following configuration shown in Table 3. Table 3. Showing operators with number of three sector sites Operator

Number Of Three Sector Sites

Average Number Of Transceivers (TRX) Per Sector

A B C D

4700 4000 4500 4200

4 3 3 3

Using equation (3), the total instantaneous power requirement for the four operators was estimated to be 103.1832MWconsuming 2451.3MWh/day energy. The distribution of power requirement for each operator is shown in Figure 4. Figure 4 shows the power consumption for each operator. Operator A consumes about 29.5724MW and operator B consumes 22.096 MW this increases to 28.314 MW for operator C when the number of sites increases from 4000 to 4500 representing 11.1% increase in BTSs which corresponds to 22% increase in power consumption. Similarly, there is 6.67% increase in the number of BTSs from operator D with 4200 sites and operator C with 4500 sites, this corresponds to 18% increase in power consumption (i.e. about three order of magnitude). This is indicting that increasing in the number of sites, increases the power consumption by at least factor of 2.

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Further analysis on the energy consumption for each operator as a function of number of sites and the duration of power supply, each component is assume to consume power for 24hrs/day except for the incandescent bulbs which is expected to provide lightning for 12 hrs/day during the night periods. The energy consumption for operator A with 4700 three sector sites each having average of 4TRX per sector is 702.97MWh/day as shown in Figure 5. Same comparison applied for the energy, as the increase in energy of about 22% was recorded between operator B and operator C. The total energy consumption for the four operators was evaluated to be 2451.3MWh/day.

35 29.5724

Average Power Consumption (MW)

30

28.314 23.2008

25

22.096

20 15 10 5 0 Operator A with 4700 4 sector Sites

Operator B with 4000 3 sector Sites

Operator C with 4500 3 sector Sites

Operator D with 4200 3 sector Sites

Daily Energy Consumption MWh/day

Figure 4. Power consumption (MW) for Operator A, B, C and D

800

702.9696

673.056

700 600

550.7712

524.544

500 400 300 200 100 0 Operator A

Operator B

Operator C

Operator D

Figure 5. Energy consumption (MWh/day) for Operator A, B, C and D

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The power consumption for operator A with three sector site, before and after optimization has been evaluated. The result is shown in Figure 6.After optimization, no AC’s and bulbs used. It was found that the average power consumption for the site increase with increase in the number of transceivers per sector. It is note-worthy that an increase of 768W and 331W per transceiver was recorded for SISO and MIMO respectively. The power consumption for the site with 1TRX per sector is found to be 3.988KW this decreases to 1.528KW and 1.0912KW respectively for SISO and MIMO representing 61.68% and 72.63% decrease in power consumption. The percentage gain which indicates the decrease in power consumption for both SISO and MIMO over the non-optimized sites shows highest for 1TRX with 61.68% gain for SISO as compared to 22% gain when 10TRX was used. When critically observed, it was found that SISO shows fixed gradient of 2.46KW for all transceivers. (I.e. gain of 2.46 was observed despite increasing number of TRX per sector for the optimized sites), whereas, the gradient for MIMO varies from 2.396KW for 1TRX to 5.080KW for 6TRX.

Average Power Consumption (KW)

9 8 7 6 5 Before Optimization

4

After Optimization SISO

3

After Optimization MIMO

2 1 0 0

1

2

3

4

5

6

7

Number of Transcievers Per Sector Figure 6. Average power consumption (KW) with the number of transmitters per sector before and after optimization for both SISO and MIMO systems

The energy efficiency gain (PEG) was also evaluated using equation (6); it was found that, the gain obtained using MIMO over the SISO system increases with increase in the number of TRX. Using 1TRX, 15% gain was measured for MIMO over SISO and this increase to 63% with 10 TRX per sector. This indicates that despite the gain decreases with increase in number of TRX per sector as observed in above, the efficiency gain of MIMO over SISO increases with increase in number of TRX per sector.

5. Appropriating the Conserved Energy The energy conserved after optimization can be alternatively used. This can be translated to cost reduction by powering extra BTSs or it can be used for domestic purpose (i.e. to power houses) [11]. From the analysis in Fig 6, reserved energy can be obtained. Equation (8) is used calculate the total energy reserved of the optimized sites. It was found that when 5% of the total sites for operator A are optimized, using SISO technique 578.1KW of power 9


would be reserved for all transceivers. While, optimizing the sites with MIMO technique, 680.748KW of power would be reserved when sites with 1TRX are optimized, this increase to 1.1MW of power when sites with 6TRX per sector are optimized representing 43% increase in reserve power. In Figure 7, it can be seen that, 145 sites with 1 TRX per sector each with power requirement of 3.988KW per site could be powered with the reserved obtained using SISO this decrease to 74 sites with 6TRXper sector each site with power requirement of 7.828KW. Similarly, 177 sites could be powered each with 1TRX per sector using the reserved obtained from 1TRX MIMO, this increase to 197 and 299 sites for 2TRX MIMO and 6TRX MIMO respectively. Figure 7 also indicates that, for all the optimization techniques, the number of sites powered decrease exponentially with increase in number of TRX per sector. Conclusively, the number of extra sites the reserved power could power varies as a function of number of transceivers the site has and these depends exclusively on the optimization techniques employed and the type of sites optimized. 350

Number of Sites Powered

300 250

OPT SISO For All TRX Sites OPT 1TRX Sites MIMO

200

OPT 2TRX Sites MIMO 150

OPT 3TRX Sites MIMO OPT 4TRX Sites MIMO

100

OPT 5TRX Sites MIMO OPT 6TRX Sites MIMO

50 0 0

1

2

3

4

5

6

7

Number of Transceivers Per Sector Figure 7. Number of sites powered as a function of number of transceivers per sector

6. Conclusions In this paper, we have examined the power consumption in wireless access networks particularly base transceiver stations (BTS), other BTS peripherals such as the power amplifier which is one of the major power consuming components of the BTS are investigated. The impacts of increasing the efficiency of the power amplifier and reducing some power consuming component such as the air conditional system were also investigated. Analysis of results shows that, reserved energy could be obtained when optimization technique is deployed in the network and this reserved could be used to power extra sites to reduce the cost of power supply and it is also noted that the number of extra sites the reserved power can power varies as a function of number of TRX the site have and these depends exclusively on the optimization techniques employed and the type of sites optimized.

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7. References [1]

ATIS, “Report on Wireless Network Energy Efficiency”, January, 2010. Available on http://www.google.com.ng/url?sa=t&rct=j&q=&esrc=s&frm=1&source=web&cd=2&ved=0CEgQFjAB&url =http%3A%2F%2Fifre.re.kr%2Fboard%2Ffiledown.php%3Fseq%3D208&ei=aLpUJCdGebe0QHuhIHACg&usg=AFQjCNHEjM1eb_3gWhNw_5wKeuMvhlB8uQ&sig2=U9F7_l_crd7sE4 hFBeEUgQ&bvm=bv.1355534169,d.dmQ [Accessed on 10/12/2012]

[2]

Ashwin A., “Green Communication, Annotated Literature Review and Research Vision, Institutes for critical Technology and applied Science, Virginia Tech. pp 1-19, Available on http://filebox.vt.edu/users/aamanna/web%20page/Amanna%20%20Green%20Communications%20Literat ure%20Review%20and%20Research%20Proposal.pdf [Accessed on 07/11/2012] Vadgama Sunil, “Trends in Green Wireless Access”, Fujitsu Science. Tech. J., Vol.45, No.4, pp. 404-408, 2009. Ericsson, “White Paper on Sustainable energy use in mobile Communications”, August 2007, Available on http://www.google.com.ng/url?sa=t&rct=j&q=&esrc=s&frm=1&source=web&cd=1&ved=0CD4QFjAA&url= http%3A%2F%2Fwww.connectedurbandevelopment.org%2Fdownloads%2Fdownload%2Fsustainableenergy-use-in-mobile-communications-aug-2007&ei=2uHpULPUK6O0QHBjICQBg&usg=AFQjCNGmq7V0MZSrE8ZMw1Fv3c_X1ZbYcA&sig2=WLwr81kuMFUVqCrQXT G6gg&bvm=bv.1355534169,d.dmQ [Accessed on 10/11/2012]

[3] [4]

[5] Mishra. A. J, “Advanced Cellular Networks Planning and Optimization 2G/2.5G/3G …Evolution to 4G”, John Wiley and Sons Ltd ISBN 13 978-0-470-01471-4 , pp 1-12, 2007. [6] Margot. D., Emmeric, T., Wout, J., Luc, M.,“Modelling and optimization of power consumption in wireless access network”, Computer Communications, Elsevier, Vol. 34, Issue 17, Pages 2036–2046, 2011. [7] Arnold. O, Richter. F, Fettweis. G, Blume. O, “Power consumption modelling of diﬀerent base station types in heterogeneous cellular networks”. In Future Network and Mobile Summit (Florence, Italy, 2010), pp. 1–8 [8] Richter F, Albrecht J. Fehske, Gerhard Fettweis, “Energy Efficiency Aspects of Base Station Deployment Strategies for Cellular Networks”, In Proceedings of IEEE Vehicular Technology Fall (VTC 2009-Fall), 70th. pp.1-5, 2009. [9] Lubrittoa C, A. Petragliaa,, C. Vetromilea, S. Curcurutob, M. Logorellib, G. Marsicob, A. D'Onofrioa, “Energy and environmental aspects of mobile communication systems”, Energy, Volume 36, Issue 2, February, pp 1109-1114, 2011. [10] Kumar. S. S, K. Amit, L Yunfei. and S. Tanvir,” Sustainable Energy Optimization Techniques in Wireless Mobile Communication Networks”, The First International Conference on Interdisciplinary Research and Development, 31 May - 1 June 2011, Thailand [11] Faruk. N., Muhammed. M.Y., Olayiwola W. B., Abdulkarim A., Agbakoba J., and Mohammed I. G., “Energy Conservation through Site Optimization for Mobile Cellular Systems”, Epistemic in science Engineering and Technology, Vol.2, No. 1, pp 26-33, 2011.

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