Green Telecommunica.on: From Theory to Reality Rosdiadee Nordin Faculty of Engineering and Built Environment Universi9 Kebangsaan Malaysia : adee@ukm.edu.my : hBps://sites.google.com/site/rosdiadee/ : hBp://my.linkedin.com/pub/rosdiadee-­‐nordin Outline q  Introduc.on and Problem Background q  Fundamental trade-­‐offs on the design of green radio networks q  Classifica.ons of Energy-­‐Saving Techniques q  Case Study: Feasibility Study of Green Cellular in an Equatorial Climate q  Future Direc.ons & Challenges Related to Green Wireless Int*oduction and Problem Backg*ound Why Energy Efficiency in Cellular Communication?
Where is Energy Spent?
Int*oduction Big Success of Mobile Communications
2013
2012
2011
2010
2009
2008
2007
2006
2005
-
1,000
2,000
3,000
4,000
5,000
Mobile-cellular subscriptions in (Million)
Mobile
Subscribers
9.5 Billion
IOT
50 Billion
Video demand
69%
6,000
7,000
Cont’d Growth in Mobile Base Stations
Number of
subscribers
increased
Mobile data traffic
increased
Base stations
will be
increased
With 5G, the number of BSs globally will grows to reach approximately 8 million by 2020.
Z. J. Wu, Y. Zhang, M. Zukerman, and E. Yung (2015). Energy-Efficient Base Stations Sleep Mode Techniques in Green Cellular Networks: A Survey. IEEE
Communications Surveys & Tutorials .
In Malaysia, mobile cellular subscrip9ons reached more than 42.9 million in 2014 Cont’d 2%
15%
20%
6%
57%
Ø BSs are densely deployed and overlapping
Base station
Mobile switching
Core network
Data center
Retail
Reducing the power
consumption
of BSs is the key!
Ø  80% of the BSs are quite lightly loaded for
80% of the time, but still waste energy
E. Oh, B. Krishnamachari, X. Liu, and Z. Niu (2011). Towards Dynamic Energy-Efficient Operation of Cellular Network Infrastructure. IEEE Commun.
Mag.
Cont’d Why so many BSs under‐utilized?
Ø All BSs are ON (active) all the time (to keep coverage), although traffic is almost zero in many areas.
Ø Each BS almost transmits in peak power, although peak traffic only lasts for a very short time in most cells
Existing cellular is neither smart nor green
Migrate to Green Communications
Ø  From World-Wide-Web to World-WideWireless
Ø But definitely should not World-WideWait and World-Wide-Waste!
Cont’d Traffic dynamics can provide opportunities for energy saving
Ø  The traffic loads during the daytime differs from those
during the night for both of the business and residential
areas.
Why lightly‐loaded BSs can’t be switched off (sleep)?
Ø Key challenge: How to guarantee
the coverage and radio service?
Fundamental t*ade-­‐offs on the desig= of g*een radio net?orks Y. Chen, S. Zhang, S. Xu, & G.Y. Li (2011). Fundamental Trade-offs on Green Wireless Networks. IEEE Communications Magazine.
Y. Nijsure, G. Kaddoum, N. UL Hassan, & C. Yuen (2015). Energy Efficiency Trade off Mechanism Towards Wireless Green Communication: A Survey.
IEEE Communications Surveys & Tutorials.
Fundamental trade-offs
Energy efficiency (EE)
Deployment efficiency (DE)
Spectrum efficiency (SE)
Bandwidth (BW)
Power (PW)
Delay (DL)
Spectrum efficiency (SE) – energy efficiency (EE) trade-off:
Given bandwidth available, to balance the achievable rate and energy consumption of the system.
Shannon’s capacity formula (revisit)
(1)
⎛ R Eb ⎞
R
⎟⎟
= log 2 ⎜⎜1 +
W
⎝ W N o ⎠
Where,
η SE =
R
,
W
η EE =
(2)
1
Eb
(3)
EE (bits/Joule)
The following equation is equivalent transformations of the above formula
By substitution Eq. (3) in the Eq. (2)
SE (bps/Hz)
Lower transmission rate leads to a lower transmitted power, for the same system bandwidth.
Bandwidth (BW)–power (PW) trade-off:
Given a target transmission rate, to balance the bandwidth utilized and the power needed for
transmission
PW (W)
The following equation is equivalent transformations of the above formula
BW (Hz)
Ø  For a given data transmission rate, expansion of the signal bandwidth is preferred to reduce the
transmit power, thus achieves better energy efficiency.
Ø  Evolution of wireless systems exhibits the same trend for bandwidth demand.
Ø  GSM = 200 kHz
Ø  UMTS = 5 MHz
Ø  LTE/LTE-Advanced = min 1.4 MHz, to 20 MHz, may reach 100 MHz with CA
Delay (DL) – Power (PW) trade-off:
To balance the average end-to-end service delay and average power consumed in transmission.
Types of wireless services become diverse; http, multimedia message and video services (QoS).
To build a green radio, it is important to know when and how to trade tolerable DL for low power.
Focus on PHY & MAC
PW (W)
The following equation is equivalent transformations of the above formula
⎛
1
P ⎞
⎜
⎟⎟
= log 2 ⎜1 +
Tb
⎝ WN o ⎠
P = (2
1
WTb
− 1)WN 0
DL (ηSec.)
The above expression shows a monotonically decreasing relation between per bit PW and DL,
as in Figure
Deployment efficiency (DE)–energy efficiency (EE) trade-off:
To balance deployment cost, throughput, and energy consumption in the network as a whole.
EE (bits/Joule)
Ø  The deployment cost consists of both capital expenditure
(CapEx) and operational expenditure (OpEx).
Ø  CapEx: infrastructure costs, such as base station equipment,
backhaul transmission equipment, site installation, and radio
network controller equipment.
Ø  OpEx: electric bill, site and backhaul lease, and operation and
maintenance cost.
DE (Mbits/$)
However, trade-off between DE and EE depends on specific deployment scenarios.
Ø  For suburban, path loss exponent is small (about 3.5); network EE increases with its DE.
Ø  For dense urban, path loss exponent is large (about 4.5), two different EE values result in
same DE value, corresponding to very small and very large cell radii, respectively
Overview of the fundamental framework guides specific green system designs
Classifications of EnergB-­‐Saving Techniques Previous works on energy-savings
Advantages and Shortcomings
Classifica;ons of Energy-­‐Saving Techniques Green Wireless Cellular Techniques Coopera.on Management BSs switching On/Off Coopera9ve base sta9ons Coopera9ve mobile operators Cell zooming Operator switching On/Off HetNet Hardware Solu.ons Improvements PA Renewable energy sources M. H. Alsharif, R. Nordin, and M. Ismail (2014). Classifica.on, Recent Advances and Research Challenges in Energy Efficient Cellular Networks. Wireless Personal Communica0ons, 77 (2), 1249-­‐1269. Cont’d Part I: Cooperation Management Techniques
The philosophy behind all the proposed methods is the same: reduce energy consumption based on the
traffic load.
Ø  BSs Switch Off/On
The first research discussed this technique:
L. Chiaraviglio, D. Ciullo, M. Meo, M. A. Marsan (2008). Energy-Aware UMTS Access Networks. Proc. in the11th International Symposium
on Wireless Personal Multimedia Communications (WPMC’08),
Idea
Switching off a specific number of base stations BSs during low-traffic, while
still guaranteeing coverage and services by the active remaining BSs.
Savings
Advantages
Shortcomings
25-50%
Easier and less costly for testing & implementation
Coverage issue and UE battery life.
BSs Switch Off/On Cont’d
Summary of Switch-Off Previous Studies that have Investigated the Possibility of Energy Savings 50.0%
40.7%
37.5%
40.0%
35.0%
30.0%
30.0%
29.0%
17.0%
Chiaraviglio et Chiaraviglio et Chiaraviglio et Chiaraviglio et Chiaraviglio et Marsan et al.,
2009
al., 2008,
al., 2008,
al., 2008,
al., 2009,
al., 2009,
(Residential)
(Office)
(Hierarchical)
(Uniform)
(Hierarchical)
Xiang et al.,
2011
Lorincz et al.,
2012
Bousia et al.,
2012
More details are given in:
M. H. Alsharif, R. Nordin, and M. Ismail (2014). Classification, Recent Advances and Research Challenges in Energy Efficient Cellular Networks. Wireless
Personal Communications, 77 (2), 1249-1269.
Cont’d Ø  Cell Zooming
The first research discussed this technique: Z. Niu, Y. Wu, J. Gong, and Z. Yang (2010). Cell Zooming for Cost-Efficient Green
Cellular Networks. IEEE Communications Magazine.
Idea
When congestion occurs in a cell, the congested cell could “zoom-in,” while neighboring cells
with a smaller amount of traffic could “zoom-out” to provide coverage for the UEs.
Savings
Up to 40%.
Advantages
Improve throughput and UE’s battery life. Largest reported savings.
Shortcomings
Coverage issue, Interference (when all cells zoom out), and Compatibility.
Cell zooming operations in cellular networks:
(a) Original size;
(b) Central cell zooms in when load increases;
(c) Central cell zooms out when load decreases Cont’d H. Claussen, L. T. W. HO, F. Pivit (2008). Effects of joint macrocell and residential
Ø  HetNet
picocell deployment. Proc. in the 19th Annual IEEE International Symposium on Personal,
The first research discussed this technique: Indoor and Mobile Radio Communications (PIMRC'08)
Idea
Macrocells are deployed to provide overall coverage, while small cells (e.g., micro, pico, femto)
are activated if the demand increases.
Savings
Up to 70%
Advantages
Smaller cell size improve coverage & capacity
Shortcomings
Interference, Interface Management, Complexity and deadzone problem.
Ø  Two E-UTRAN cells (Cell A, Cell B) with separate
frequency bands cover the same geographical area.
Ø  Cell B has a smaller size (Pico Cell or Micro Cell)
than Cell A (Macro Cell) and is covered totally by
Cell A
Ø  Cell A is deployed to provide continuous coverage of
the area, while Cell B increases the capacity of the
special sub-areas, such as hot spots.
Ø  Cell B deactivation in case of light traffic. Cell B
activation when the traffic resumes to a high level.
E-UTRAN
Macro
Cell A E-UTRAN
Pico/Micro
Cell B Cont’d Ø  HetNet
vary in size, output power, and data rate Cont’d Ø  Cooperative Mobile Operators
M. A. Marsan, M. Meo (2010). Energy efficient wireless Internet access with
The first research discussed this technique: cooperative cellular networks. Computer Networks.
Idea
Switch off one or more BSs when the traffic load is low, managing coverage with a
subset of remaining active BSs through either the same operator network or another
operator, with both networks covering the same geographical area.
Savings
Depends on the number of operators (n=4; 90%).
Advantages
A good exploitation of the network.
Shortcomings
Complexity & compatibility, resource management, policy and QoS.
OpenCellID.com Cont’d Ø  Relay
C. Bae and W. E. Stark, “Energy-bandwidth tradeoff with spatial reuse in wireless
The first research discussed this technique: multi-hop networks,” in Proceedings of the IEEE Military Communications Conference
(MILCOM ’08), pp. 1–7, November 2008.
Idea
Reduce transmission distance, provides independence path among different fading
channels (fundamental aspect of the diversity gain concept)
Savings
???
Advantages
Enhance capacity, range, QoS & load balancing
Shortcomings
Deployment efficiency
Cont’d Renewable Energy System
• Prev studies focused on feasibility of renewable energy for off-­‐grid sites, do not consider ci9es • Majority BSs located within ci9es due to coverage needs of high popula9on densi9es • By 2018, no. of LTE BSs is expected to reach 2.43 million to achieve the popula9on coverage target, which is expected to reach 1.3 billion LTE subscribers M. H. Alsharif, R. Nordin, and M. Ismail (2016). Green wireless network optimisation strategies within smart grid environments for Long Term Evolution
(LTE) cellular networks in Malaysia. Renewable Energy, 85, 157-170.
Mo.va.ons Towards Renewable Energy The concept of using diesel generator (DG) to power rural BS has become much less viable for the mobile operators for the following reasons: •
•
•
Fuel, opera9ng, and maintenance costs. Environmental impacts: air pollu9on, emidng harmful components such as CO2, SO2. Technical issues: The efficiency of the system is low (30%) Forecast Carbon Footprint Contribu9on by Telecom for 2020. 14% 15% 51% 51% of the ICT industry! 20% Net costs of opera9ng a diesel generator Total= 179 MtCO2 Mobile Sector Fixed Narrowband Telecom Devices Fixed Broadband M. H. Alsharif, R. Nordin, and M. Ismail (2015). Energy Op.miza.on of Hybrid Off-­‐Grid System for Remote Telecommunica.on Base Sta.on Deployment in Malaysia. EURASIP Journal on Wireless Communica0ons and Networking, 2015:64. Comparison of renewable energy & diesel generator
Case StGdy Intelligent Cooperation Management Among Solar Powered LTE-­‐
BSs for urban areas M. H. Alsharif, R. Nordin, and M. Ismail (2015). Intelligent Cooperation Management among Solar Powered Base Stations towards
a Green Cellular Network in a Country with an Equatorial Climate. Telecommunication Systems, 62(1): 179-198
Cont’d Potential of Solar in Malaysia
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Sabah Perlis Kedah 6 1 5 0.8 Clearness Index Daily Radia.on (kWh\m2\d) 7 6 5 4 3 2 1 0 Daily Radia.on (kWh\m2\d) Note: [Mj/m2/d] to [kWh/
m2/d] = divided by 3.6 4 0.6 3 0.4 2 1 0.2 0 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Daily Radia9on Clearness Index M. H. Alsharif, R. Nordin, and M. Ismail (2016). Green wireless network optimisation strategies within smart grid environments for Long Term Evolution
(LTE) cellular networks in Malaysia/. Renewable Energy, 85, 157-170.
Intelligent Cooperation Management Among BSs
1. LTE Network Topology
Key challenge: coverage
2. Problem Formulation
Op9mal solu9on for best global fitness (max coverage) and best global posi9on (constraints parameters) Results Fitness function - coverage
Constraint parameters
Results (Cont’d) Cell radii versus receiver sensitivity power
for different MCSs
Data rate
BS Subsystem
Power consumption of the LTE-BS hardware elements
Item
Notation
Unit
Macro
PA
Max transmit (rms) power, Pmax
W
39.8
Max transmit (rms) power
PA efficiency, µ
dBm
%
46.0
38.8
W
102.6
W
W
W
W
W
W
W
%
%
%
W
5.7
5.2
10.9
5.4
4.4
5.0
14.8
6.0
9.0
7.0
160.8
Number of sectors
#
Number of antennas
#
Total number of NTRX chains, Pin= NTRX × Total per W
TRX
3
2
964.9
Total PA (PPA)=
TRX
BB
Pmax
µ
PTX
PRX
Total RF (PRF)
Radio (inner Rx/Tx)
Turbo code (outer Rx/Tx)
Processor
Total BB (PBB)
DC-DC loss, σDC
Cooling loss, σcool
AC-DC (main supply) loss, σMS
PPA + PRF + PBB
Total per TRX =
(1 − σ DC )(1 − σ cool )(1 − σ MS )
G Auer, O Blume, V Giannini, I Godor, M A Imran, Y Jading, E Katranaras, M
Olsson, D Sabella, P Skillermark, W Wajda, Energy efficiency analysis of the
reference systems, areas of improvements and target breakdown. EARTH project
report, Deliverable D2.3 (2010).
HOMER for hybrid power system modelling
•  NPC represents the system’s life cycle cost •  Assesses costs within the project life9me; ini9al set-­‐
up, component replacements and maintenance •  Assump9ons: •
•
•
•
•
•
•
•
•
•
Project life9me: 20 years Annual interest: 6% 10% reserve (backup) Inverter efficiency: 90% BaBery efficiency: 85% SPV cost: $4/W SPV size = 1, 1.5, 2, 2.5 kW Converter = 0.5, 1, 1.5, 2 kW BaBery units = 5, 10, 11, 12, 13, 14 Output power = 965 W Results 1. Optimisation Criteria
Optimal design of the hybrid PV/electric grid system for master cell (operates 24 hours)
Optimal design of the hybrid PV/electric grid system for cell operates at high traffic only (13 hours)
Results (Cont’d) Cell operates at high traffic only (13 hours)
4,524 5,112 4,500 4,400 4,300 5,140 2,900 5,120 2,800 5,100 5,074 4,407 4,290 4,200 5,059 5,040 5,080 5,060 5,040 4,997 4,281 5,020 5,000 4,177 4,980 4,960 4,100 4,940 4,000 4,920 5.1 5.2 5.3 5.4 5.5 Globel Solar (kWh/m2/day) SPV contribu9on for master cell PV Produc.on (kWh/yr) 4,600 2,700 2,600 2,500 2,800 2,715 2,691 2,784 2,781 2,644 Grid Purchases (kWh/yr) Master cell
Grid Purchases (kWh/yr) PV Produc.on (kWh/yr) 2. Energy Yield
2,750 2,700 2,574 2,650 2,663 2,378 2,635 2,400 2,600 2,607 2,300 2,550 2,200 2,100 2,500 5.1 5.2 5.3 5.4 5.5 Globel Solar (kWh/m2/day SPV contribu9on for cell operates 13 hrs Results (Cont’d) Capital cost: SPV (65.6%), baBery (27%), inverter (7.4%) 3. Cash Flow
Nominal Cash Flow ($) 4,000 2,000 0 -­‐2,000 Replacement
Batteries
-­‐4,000 -­‐6,000 Replacement
Inverter
-­‐8,000 -­‐10,000 -­‐12,000 -­‐14,000 1 2 3 Salvage ($ 3,719) 4 5 6 7 8 Replacement Cost ($) 9 10 11 12 13 14 15 16 17 18 19 20 Year Number O&M Cost ($ 800) Capital Cost ($ 12,200) Cash flow summary of the hybrid power system within the project lifetime at 5.1 kWh/m2/day for master cell
Prac;cal Solar Powered Base Sta;on Implementa;on
Italy Burkina Faso Kenya Angola Brazil Arab gulf region Lebanon Nepal India Bangladesh Turkey Sri Lanka … and … Malaysia! Solar power system in remote areas of Burkina Faso provided by ZTE Location: The latitude of this site is 11°59′, north; the maximum
continuous rainy/cloudy days in the local area is 5 days.
Requirements: power system is required to provide power for BTS and
microwave equipment; the total power consumption is 550W.
In this project, 22 solar-powered BTSs are deployed. They have a
relatively small capacity, which is in the range of 400-900W.Solar power
system makes diesel re-fuelling and maintenance work unnecessary,
which can save about US$150,000 for operator every year.
It is worth mentioning, ZTE has helped over 40 operators in more
than 20 countries build solar-powered BTS system.
Reference: http://wwwen.zte.com.cn/endata/magazine/ztetechnologies/2009year/no7/articles/200907/t20090710_173704.html
Italia
Location: Solar powered base station at the
Italian city of L'Aquila implemented by Ericsson
and Telecom Italia.
System Design: The Eco Smart solution features
an elliptical support structure coated with flexible
solar panels wrapping up the antenna.
Reference: http://www.cellular-news.com/story/Operators/38446.php
Solar base stations by Alfa mobile operator in Lebanon
Location: five remotes sites, namely in Hourata, Challita,
Aakoura, Ouyoun Laqlouq, and Mehmarch, which are
implemented by ECOsys company that specialist in solar
energy solution.
Reference: http://www.itgholding.com/news/1899
Arab gulf region
Location: 300 solar-powered base stations has deployed in Arab
gulf region implemented by Eltek. In addition, 200 sites will be
deployed in 2015 and 2016.
The solution design is based on full reliability on solar and
backup batteries, knowing that on few sites, unstable utility and
generators are available for additional backup. The battery
autonomy is very high and the solution can provide continuous
energy for 5 days.
It is worth mentioning, Eltek has provided solar powered telecom installations across the African continent, in
countries such as Angola, Chad, Kenya, Lesotho, Mauritania, Morocco, Mozambique, Somalia, Somaliland, South
Africa, Zambia and Zimbabwe.
Reference: http://www.eltek.com/detail.epl?cat=28971&id=2183193
Prac.cal case in Malaysia Solar BS project implementa9on by: Solar Energy Research Ins9tute(SERI) Universi9 Kebangsaan Malaysia (UKM) Digi is first in Malaysia to test hybrid hydrogen-­‐
powered base sta;ons (25th Jan, 2016)
•  Pilot base sta9on near Rompin, Pahang •  Hydrogen fuel cell system extracts water from the atmosphere. •  Breaks the water down to produce hydrogen to power the fuel cells and generate electricity •  The by-­‐product of this form of energy is oxygen and water. •  Zero GHGs are released into the atmosphere! hBp://www.telenor.com/media/ar9cles/2016/digi-­‐is-­‐first-­‐in-­‐malaysia-­‐to-­‐test-­‐hydrogen-­‐powered-­‐base-­‐sta9ons/ Burkina Faso http://wwwen.zte.com.cn/endata/magazine/ztetechnologies/2009year/no7/articles/200907/t20090710_173704.html
Angola hBp://www.amerescosolar.com/solar-­‐power-­‐solu9ons-­‐communica9ons Nepal
http://www.ztebrasil.com.br/pub/en/press_center/news/201101/t20110105_199217.html
http://wwwen.zte.com.cn/endata/magazine/ztetechnologies/2004year/no8/articles/200406/t20040611_161343.html
Arab gulf region
http://www.eltek.com/detail.epl?cat=28971&id=2183193
Lebanon hBp://www.itgholding.com/news/1899 Turkey hBp://www.cellular-­‐news.com/story/Operators/37123.php Italia hBp://www.cellular-­‐news.com/story/Operators/38446.php Sri Lanka hBp://www.cellular-­‐news.com/story/Operators/36151.php FutGre directions & challenges related to g*een cellular Peak Data Rate (Gbps) Visions of 5G Cellular Wireless Networks
Ø  Key challenge is to meet several
goals, at a similar cost and energy
consumption as today’s networks.
Latency (mSec) Ø 5G networks will adopt a set
of new technologies to support Simultaneous
Connection the increase in the volume of
(104/km2) traffic in future wireless
communications
Cell Edge Data
Rate(Mbps) Cell Spectral
Efficiency (bps/Hz) The 5G roadmap: revolution, evolution, and complementary new technologies
A. Osseiran, F. Boccardi, V. Braun, K. Kusume, P. Marsch, M. Maternia, O. Queseth, M. Schellmann, H. Schotten, H. Taoka, H. Tullberg, M. A. Uusitalo, B. Timus,
and M. Fallgren (2014). Scenarios for 5G Mobile and Wireless Communications: The Vision of the METIS Project. IEEE Communications Surveys & Tutorials .
Both massive MIMO systems and small cell networks are expected to
achieve high energy efficiency (EE) for high throughput cellular
networks.
1.  Massive MIMO improves EE by exploiting a large array gain, and
using the narrow beams between the transmitter and receiver.
2.  Small cells improve EE by deploying numerous low-power BSs to
reduce the propagation losses and increase the opportunity of BS
sleep.
Antenna
SINR
BW
B. Panzner, W. Zirwas, S. Dierks, M. Lauridsen, P. Mogensen, K. Pajukoski, and D. Miao (2014). Deployment and Implementation Strategies for Massive
MIMO in 5G. Proc. in Globecom 2014 Workshop - Massive MIMO: From Theory to Practice
Ø  Adjustments in massive MIMO (antenna switching off/on) at high traffic load conditions, with
the BSs switching off/on technique
Ø  Investigation of the proposed solar energy-harvesting system in other environments, such as
IoT and Smart City; aim to improve long term reliability and stability
Ø  Investigation of cooperation between mobile network providers (switching off/on) in the same
geographical.
Ø  Energy harvesting, e.g.: RF, mechanical, renewables, etc.
OpenCellID.com Thank you for your aSen;on! •  Project supported by Universi9 Kebangsaan Malaysia (UKM), under the Grant Ref: ETP-­‐2013-­‐072. •  Special thanks to Dr. Mohammed Al-­‐Sharif, Sejong University, Seoul, Korea