Green Wireless Networks

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Transcription:

Green Wireless Networks Dr. Gee Rittenhouse Chairman of the Board, GreenTouch

OUTLINE 1. GreenTouch Introduction 2. Research Directions for Green Wireless Networks 3. Initial Research Results and Ongoing Activities 2

A NEW WIRELESS WORLD / INTERNET 3

MASSIVE DATA TRAFFIC GROWTH MORE DATA MEANS MORE POWER 5 000 000 towers = 17.5 GigaWatts ~ 9 Hoover Dams ~ 15 nuclear power plants 4 Today 78 Mtons of CO 2 ~ 15M car emissions a year ~ 150,000 Paris to New York round-trip flights Future 5 000 000 000 people without broadband

2020 ICT CARBON FOOTPRINT 820m tons CO 2 360m tons CO 2 2007 Worldwide ICT carbon footprint: 2% = 830 m tons CO 2 Comparable to the global aviation industry Expected to grow to 4% by 2020 The Climate Group, GeSI report Smart 2020, 2008 260m tons CO 2 5

ICT: A PROBLEM AND THE SOLUTION ICT today: 2% of global emissions with an opportunity to make tremendous impact on the remaining 98% Gtons CO 2 1.4 0.8 0.5 2002 2007 2020-0.9 Lower ICT Emissions Zero Growth Line Greening of ICT How do I reduce or keep in check the carbon footprint of ICT itself? Greening with ICT How do I use ICT to reduce carbon footprint and achieve sustainable living? Prediction that ICT will save more energy than it will consume -7.8 Lower emissions from other Industries Indirect benefit is 10x ICT target footprint Source: GeSI SMART 2020: Enabling the Low Carbon Economy in the Information Age 6

Traffic (Tb/s) CONTINUED EXPONENTIAL TOTAL TRAFFIC GROWTH IN THE INTERNET North America 10 3 10 2 10 1 10 0 10-1 10-2 P2P 2010 2015 2020 Year Wireless Voice Data from: RHK, McKinsey-JPMorgan, AT&T, MINTS, Arbor, ALU, and Bell Labs Analysis: Linear regression on log(traffic growth rate) versus log(time) with Bayesian learning to compute uncertainty Traffic doubling every 2 years 40% per year 30x in 10 years 1000x in 20 years 7 7

SLOW-DOWN IN TECHNOLOGY Network energy efficiency only increasing at 10-15% per year 8 8

Growth THE NETWORK ENERGY GAP 50 40 Mobile Data Traffic Internet Backbone 30 20 10 Growing Gap! Mobile Efficiency Wireline Efficiency 2005 2010 2015 2020 Year 9 9

Power/User (W) BEST CASE EFFICIENCY IMPROVEMENTS 100 Fixed Access WDM Mobile Routing & Sw Mobile Access: Ultra-efficient power amplifiers (70%) Active antennas Self organizing networks 10 Fixed Access: Cost-reduced FTTH/N Green PON (from ~16W/user to ~5W/user) 1 Metro/Core: Mesh protection / fast restoration Dynamic Optical Bypass 0.1 Other: Passive cooling everywhere Dynamic energy usage (proportional to load) Network Virtualization 2010 2015 2020 Year Apply uniformly up to 2017 Degree of Difficulty: Lower Higher 10 10

Efficiency (Mb/s/W) GREENTOUCH MISSION (www.greentouch.org) By 2015, our goal is to deliver the architecture, specifications and roadmap and demonstrate key components and technologies needed to increase network energy efficiency by a factor of 1000 from current levels. 100 10 1 0.1 0.01 1E-3 1E-4 1000x Target Total Network: BAU 2010 2015 2020 Year Global research consortium representing industry, government and academic organizations Launched in May 2010 52 member organizations 300 individual participants from 19 countries 25+ projects across wireless, wireline, routing, networking and optical transmission = ~ 3 Years 11

EFFICIENCY AND RENEWABLE ENERGY SOURCES Directions and requirements Greenpeace, G. Cook, J.V. Horn, How dirty is your data 2011 Greenpeace, EREC Energy (R)evolution 2010 New technologies and capabilities 12 12 GreenTouch Introduction 2012 2012 GreenTouch Consortium

SOME RESEARCH PROJECTS Beyond Cellular Green Mobile Networks Virtual Home Gateway Optimal End-to-End Resource Allocation Service Energy Aware Optical Networks Green Transmission Technologies Minimum Energy Access Architectures Single-Chip Linecards Large-Scale Antenna Systems Highly-Adaptive Layer Mesh Networks Massive MIMO 25+ Projects 13

Research Directions for Green Wireless Networks 14

Energy Use POWER CONSUMPTION OF MOBILE COMMUNICATIONS Total Energy = 2 TWh/yr 0.1W per user for 3 billion Subscriptions Total Energy = 60 TWh/yr 1kW per user for 4 million Base Stations Total Energy = <1 TWh/yr 1kW per user for 10,000 Controllers Total Energy = 14 TWh/yr 10kW per user for other elements The greatest opportunity to reduce energy consumption is to improve base stations Based on: ETSI RRS05_024, NSN Users Base Station Network Control Core & Servers 15

GREEN NETWORK OPPORTUNITIES (I) Deployment: Relays Nodes Multi RAT Heterogeneous Networks Network Management: BS cooperation, Adaptive NW configuration H i g h Traffic Freq. L o w (a) (b) (c) (d) (e) Freq. Multi-Antenna Techniques: Reconfigurable antennas, Beam forming, Spatial multiplexing 16

Power Consumption per Cell [W] GREEN NETWORK OPPORTUNITIES (II) Radio Resource Management: Energy efficient scheduling, Sleep modes, Bandwidth Adaptation 160 140 120 100 00.00hrs Saved energy 12.00hrs Telecom traffic 24.00hrs 80 60 40 20 0 SOTA BW Adaptation Capacity Adaptation Micro DTX 0 4 8 12 16 20 24 Time [h] Power consumption model per cell Power [W] Resource block with data Resource block with pilots only Empty resource block Variable power Constant power DTX power 0% 100% PA utilization High load: Most resources used Low load: Capacity adaptation BW adaptation: Pilots suppressed 17

Recent Results and Ongoing Projects 18

SOME SPECIFIC RESEARCH ACTIVITIES 1. Large Scale Antenna Systems Massive MIMO Distributed Antenna Systems 2. EARTH (Energy Aware Radio and network technologies) Small cells and heterogeneous network deployment Network management 3. BCG 2 (Beyond Cellular Green Generation) Green network management / intelligent power management Independent network configuration for data and signaling 19

LARGE SCALE ANTENNA SYSTEM Measured transmit power is inversely proportional to the number of antennas: Beam-forming for energy efficiency, not capacity First GreenTouch technology demonstration 20 GreenTouch : Building the Roadmap 2011 20 2011 GreenTouch Consortium

Processing Unit APPLICATION SCENARIOS Massive Co-located Antennas Spatially Distributed Antennas Short-range RF link (e.g., 16-20GHz, E-Band, ) Centralized Processing Unit Cable/fiber link Marzetta, T. L., IEEE Trans Wireless Communications, Nov 2010 100 s or 1000 s of antenna elements Power amplifiers operating at micro-watt levels 21

TOTAL ENERGY VS. COMPUTATIONAL ENERGY EFFICIENCY & SPECTRAL EFFICIENCY M: number of service antenna 22

EU FP 7 PROJECT EARTH (Energy Aware Radio and network technologies) PST Internet Mobile Core Network Network Server Gateway (SGSN, HLR) (PDG, GGSN) Media Server (IMS) Access Network Base Station 70-80% of overall energy consumption GOAL: SAVE 50% POWER IN LTE-BASED ACCESS NETWORKS Deployment Network Management Components Zzz DC supply DC supply small cells off Small cell RF in PA Small Cells with Overlay Macro Cell Dynamic operation; Sleep modes, Bandwidth Adaptation, Power Amplifier & Transceiver, Load-adaptive Hardware https://www.ict-earth.eu 23

Energy Savings of Base Station Site [%] Energy Savings per Base Station Site [%] GREEN MANAGEMENT SOLUTIONS Energy saving potential for Green LTE calculated over daily traffic cycle Saved energy Telecom traffic Highest gains by combination of BW adaptation and micro DTX 00.00 12.00 hrs hrs High energy savings for combination of CAP adaptation and micro DTX Complemented by improvements in baseband hardware and other components Overall a 50% saving is reached 70 30 61.8 27.4 60 57.9 25 23.1 49.8 50 47.5 19.7 20 17.3 40 24.00 hrs 15 30 10 Dense Urban Rural 20 Dense Urban Rural 5 10 24 0 BW Adaptation and Micro DTX CAP Adaptation and Micro DTX 20% improvements by new PA and management 0 BW Adaptation and Micro DTX CAP Adaptation and Micro DTX Complemented by EE baseband components

Area power consumption [W/km²] Gain [%] HETEROGENEOUS DEPLOYMENT with adapted Macro Cells and Micro Cells at Cell Edges Micro cell Macro cell Approach: System Level study on best cell size and optimum deployment strategy depending on traffic demand Indoor user with uniform distribution Hexagonal macro network, Tx power density adapted to cell size One or more micro cells at cell edge Area Power [W/m²] Relative gain in Area Power consumption [%] Reference: only macro cells Gain Scenario 1: 1 micro per sector Scenario 4: 5 micros per sector only micros Loss Inter site distance [m] Target area throughput [Mbps/km²] see O. Blume, F. Richter in section 2.1 of EARTH D3.1 Most Promising Tracks of Green Network Technologies. https://bscw.ict-earth.eu/pub/bscw.cgi/d31509/earth_wp3_d3.1.pdf Results: There is an optimum urban macro InterSiteDistance (ISD), depending on traffic density. Small cells help to reduce the system power consumption only in case when the offered extra capacity is required. 25

Traffic Load Power Consumption BEYOND CELLULAR GREEN GENERATION (BCG 2 ) Network capacity Minimum energy consumption in active mode Sleep mode Day 1 Day 2 Day 3 Traffic Load Wireless access networks are dimensioned for estimated peak demand using dense layers of cell coverage Traffic varies during the day Energy consumption is almost constant Due to the power consumed by signaling 26

TRADITIONAL CELLULAR ARCHITECTURE Signaling Data Full cellular coverage for data access Limitation of traditional cellular architecture: Continuous and full coverage for data access Limited flexibility for energy management High energy consumption also at low traffic load 27

BCG 2 ARCHITECTURE sleep sleep sleep sleep Data Separate Opportunities for sustainability: System designed for energy efficiency Separate capacity from coverage Optimise signalling transmission Lean access to system Cope with massive amount of low data rate services Signaling sleep Beyond cellular coverage with data capacity on demand Challenges: New system architecture Re-invent mobility management Agile management, context aware, network with memory Hardware for fast reconfiguration 28 28

THEORETICAL UPPER BOUNDS ON POTENTIAL GAINS 2010 Reference scenario: Macro BSs only (SCENARIO 1) Always-on Low traffic level 2015 Mixed scenario with BCG 60% micro, 40 macro BSs (SCENARIO 2) BCG energy management Medium traffic level 2020 Micro/pico cellular scenario 10% macro, 60% micro, 30% pico BSs (SCENARIO 3) BCG energy management High traffic level 2010 2015 2020 Urban: 3887 Dense U: 1296 [10-3 J/kbit] Urban: 38X Dense U: 16X Urban: 76X Dense U: 36X Long term scenario Atto cellular scenario 100% atto BSs BCG energy management Any traffic level 20xx Urban: 1555X Dense U: 518X 29

CONCLUSIONS ICT networks are growing rapidly Scaling networks is becoming more difficult Bringing focus to energy efficiency ICT and research communities are organizing to address challenges Dramatic, holistic change, but over long term evolution Cooperative organizations such as GreenTouch guiding evolution Several promising research directions and initial results have been obtained More work remains! 30

Thank you! 31

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