from always‐on to always‐available to always‐optimized! · nb2. assumed device mix: 60%...

From Always‐on to Always‐available to Always‐optimized!

Presented By –Dr. Ylva Jading, Senior Specialist

Ericsson Researchylva.jading[at]ericsson.com

1st IEEE Energy Efficiency Tutorial:

Wednesday, September 19, 2018

ALL INFORMATION SHALL BE CONSIDERED SPEAKER PROPERTY UNLESS OTHERWISE SUPERSEDED BY ANOTHER DOCUMENT.

—An introduction and some background—Economy, Ecology and Engineering

—Putting energy performance on the agenda with EARTH—Metrics, Models, Mindset and some concepts

—From always‐on to always‐available with 4G/LTE—Cred, Trust and perhaps some Brilliant Mistakes…

—Operating closer to our highest potential with 5G/NR—Always‐optimized with ultra‐lean design and beamforming

2

Energy Performance – a story of change

ALL INFORMATION SHALL BE CONSIDERED SPEAKERS PROPERTY UNLESS OTHERWISE SUEPRSEEDED BY ANOTHER DOCUMENT


Introduction and Background



—Energy efficiency has continuously improved over the years!

—So why do we still care about network energy consumption?

4

Why network energy performance?



The big picture

4G

3G

2G1G~20% ~80%

RANCore / IP

The big picture

2G3G

4G5G

…Or can we do better?

BusinessAs Usual


Network energy performance

Minimizing total network energy consumption, despite increased traffic and service expansion

Economy Ecology Engineering


Perspectives and players

Energy performance – Same answer, different questions

Economy

Operators Vendors Governments

Ecology

Engineering

Reduce OPEXBranding

Capture Energy SpendPremium Brand

Reach CO2reduction targets

Technology for good“Walk the talk”

Drive energy and climate transition

“Less is more”

Size, weight, enable new deployments etc.

Subscriber growth in off‐grid areas

Enable new power solutions

Sustainable growth

Drive innovation and job creation


Putting Energy Performance on the agenda



LTE Rel‐8 (2008‐2009)― “CRS all the time over all the bandwidth” was identified as a problem very late

― No recognized models or methodology for evaluating NW energy consumption

No agreement to change Rel‐8 specifications late in the 3GPP process!

― “Backward compatibility” prevented us from doing it for later LTE releases

― Investigated and formulated the problem and started to build consensus…

Specifying 4G/LTE in 3GPP

Dense UrbanUrban

Suburban

Rural

SuperDenseUrban

Energy Efficiency Evaluation Framework (E3F)Deployment models Traffic scenarios

Power models 24h traffic profile


Dense UrbanUrban

Suburban

Rural

SuperDenseUrban

―Typical European country (excluding Nordic countries and Russia)

―NB: Extremely small share of Super Dense Urban

―Extremely large share of “wilderness”―43% area coverage, 89% population coverage

Large scale deployment model

Area type Pop. density[citizens/km2]

Area share [%]

Super dense urban 20000 0,05

Dense urban 3000 0,95

Urban 1000 2

Sub‐urban 500 4

Rural 100 36

Wilderness 25 57Source: The world bank, “population density”

61% of the population lives in the cities (SDU, DU, U, SU) in 7% of the area.

Data traffic demand per areaTypical European, 2014‐2020

Area 2014 2017 2020

Super Dense Urban 200 400 750

Dense Urban 30 60 110

Urban 10 20 40

Suburban 5 10 20

Rural 1 2 4

Wilderness 0,25 0,5 1

NB1. Figures show total demand. Should be multiplied by operator market share (default 1/3).NB2. Assumed device mix: 60% smartphone, 30% mobile PC, 10% tabletNB3. Figures are peak busy hour demand.

Device Type 2014 2017 2020

Mobile PC 4300 8031 15000

Smartphone 900 1775 3500

Tablet 1900 3800 7600

MB/month for different device types Peak traffic demand per area type [Mbps/km2]

―Traffic is un‐evenly distributed ―Many sites with low traffic

―Low and high traffic is everywhere

―On a millisecond time‐scale most cells are empty―Networks dimensioned for future peak‐hour traffic ―High traffic is rare and average traffic load is fairly low

Data Traffic


Low traffic dominates

Cells sorted in increasing average throughput [%]

Tim

e so

rted

in in

crea

sing

thro

ughp

ut [%

]

0 10 20 30 40 50 60 70 80 90 100

0

10

20

30

40

50

60

70

80

90

100 0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Cells sorted w.r.t. increasing average throughput [% of cells]

Two weeks of traffic measurements from 670 cells in a metropolitan area

Sort

ed s

ampl

es p

er c

ell [

% o

f tim

e] Load relative to cell capacity

› Low average traffic

› Large variations

› Peak dimensioning

Characteristics


24h traffic model


―EARTH developed common power models

―We found that power consumption was approximately linear with load

―For Macro Base Stations ―Dominant consumer = Power amplifier (PA)

The Macro base station power model


Traffic vs energy consumption

Networks dimensioned for peak traffic demand

Network Traffic Load50%40%30%20%10%0%

Network Energy Consumption

Normal traffic Very high traffic Extreme traffic

Low average resourceutilization

Considerable static energyconsumption in networks

Improve load dependence!

Normal traffic Very high traffic Extreme traffic


from Always‐onto Always‐available


Improving energy performance

“Reduce overall energy consumption in case of excess capacity”

Network management power

load

“Design energy efficient systems from the start”

System design and standardization power

load

“State of the art energy lean hardware and software”

Products and solutions power

load


Why does idle mode network energy consumption dominate in LTE?

“Empty” LTE radio‐frame

RF output power

Full load

Active

RBS power usage

Ref. Symbols, Sync, Sys Info

Sleep mode

Time‐scale matters

Antenna muting

Dynamic psi‐omni

Cell DTX

Ref. Cell DTX

Antenna muting

DynamicPsi‐omni

0%‐2%

‐6%

User p

erform

ance

s

10 ms

>100 ms

Source: EARTH

How quickly can this be turned on? Tr

affic

Low

Hig

h

freq.

freq.


―Circuits should be prepared for no or minimum leakage when not used

―Multiple power‐supply domains to allow parts of the board to be powered off

―Clock domains to allow parts of the board to be halted

―Intra‐connect with bypass possibilities allowing processing nodes to sleep while maintaining communication between remaining processing nodes

Proper HW Architecture


Proper SW Architecture

―SW architecture for need to support energy efficiency in an HW agnostic way―Differences in HW generations and HW version must be possible to hide from the SW

― Dynamic baseband resource allocation should be default―SW needs to ensure that it does not prevent idling HW from entering sleep state

―SW functions shall not spread out over more cores than needed



Operating closer to our highest potential


NR: Energy performance embedded in standard

Load adaptiveenergy consumption

Only transmit whenand where needed

From always available to always optimized!


5G: One network – multiple use cases

@

A common network platform with dynamic and secure network slices



―Specifying 3GPP New Radio, 2016‐2017

―Network energy consumption established as: “key performance criterion for IMT 2020”

―Ericsson successfully pushed for long DTX in 5G NR standard

―Now 20ms maximum SSB periodicity for standalone operation …and 160ms for non‐standalone!

Specifying 5G/NR in 3GPP

High level NR EE principles supported in Rel‐15―Time‐domain

―DTX ―stand‐alone operation with 20 ms DTX―non‐standalone operation with 160 ms DTX

―high rate and capacity enable “rush to sleep”―Frequency domain

―BWP adaptation―fast carrier aggregation activation―sparse grid for initial cell search

―Antenna domain―MIMO sleep (single antenna port for idle mode signals and channels)―support for wide‐beams (less beam‐sweeping)―beamforming to increase ISD

―Network domain ―network slices: one network multiple services


What to expect in short term

~ 2018:LTE +

time‐to‐market optimized NR

Early NR product consume more than mature LTE productsNR bandwidth significantly wider (up to 25 times more BW)Many more radio chains (due to massive MIMO)

~2020:LTE + energy performanceoptimized NR

Future:Energy optimized site

Today:LTE‐only

NR utilizing “ultra lean design” possibilities

Site ene

rgy consum

ption


ALL INFORMATION SHALL BE CONSIDERED SPEAKER PROPERTY UNLESS OTHERWISE SUPERSEDED BY ANOTHER DOCUMENT.32

Conclusions― Typically low load dependence of

network‐energy consumption today

― Energy performance requires addressing low traffic cases

― Large energy‐saving potential in legacy NW parts― Dynamic on‐demand activation― The faster the better

― Key technical enablers for enhanced network‐energy performance in 5G― Ultra‐lean design: Longer and more DTX― Massive MIMO Beamforming: Increased ISD


Thanks a lot for your time and attention!

Any questions and/or comments?

33

Q & A

from always‐on to always‐available to always‐optimized! · nb2. assumed device mix: 60%...

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