PowerConsumptionbyWireless
Communication
LinZhong
ELEC518,Spring2011
Powerconsumption(SMT5600)
Flight mode: Sleep, 3,
0%
Lighting: Keyboard,
73, 3%
Lighting: Display
I, 148, 5%
Cellular network, 17,
1%
Lighting: Display II,
61, 2%
LCD, 13, 0%
Compute, 370, 13%
Speaker, 45, 2%
Bluetooth, 440, 16%
GPRS, 1600, 58%
2
100
Power (mW)
Powerconsumption(T-Mobile)
Cellular
Wi-Fi
Bluetooth
10000
1000
10
1
Transmission
Connected
Transmission
Connected
Transmission
Connected
Paging
Discoverable
Speaker
Keyboard lighting
LCD lighting
LCD
Computing
IDLE-Flight mode
3
Powerconsumption(Contd.)
• Theoreticallimits
– Receivingenergyperbit>N*10-0.159
• N:Noisespectralpowerlevel
• Widebandcommunication
PTX∝ PRX
*da
PRX
Distance:d
Propagation constant:a(1.81-5.22)
4
Powerconsumption(Contd.)
• Whatincreasespowerconsumption
– Governmentregulation(FCC)
• Availablespectrumband(Higherband,higherpower)
• Limitedbandwidth
• Limitedtransmissionpower
– Noiseandreliability
– Highercapacity
• Multipleaccess(CDMA,TDMAetc.)
– Security
– Addressability(TCP/IP)
– More……
5
Wirelesssystemarchitecture
Networkprotocolstack Hardwareimplementation
Application
Transport
Hostcomputer
Network
Datalink
Baseband
Physical
Networkinterface
RFfrontends
6
Powerconsumption(Contd.)
Low-noiseamplifier
Antenna
interface
LocalOscillator
(LO)
Intermediate
Frequency (IF)
signalprocessing
PA
Poweramplifier
PhysicalLayer
IF/Baseband
Conversion
LNA
Baseband
processor
MACLayer&
above
>60%non-display powerconsumed inRF
RFtechnologies improve muchslowerthanIC
7
Powerconsumption(Contd.)
1%
6%
8%
PA
FS
18%
67%
Mixer
Components
Power (mW)
Power amplifier
(PA)
246
Frequency
synthesizer
(VCO/FS)
67.5
Mixer
30.3
LNA
20
Baseband Amplifier
5
Source:Lietal,2005
http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=1579876
8
Low-noiseamplifier(LNA)
•
•
•
•
•
Bandwidth(sameasthesignal)
Gain(~20dB)
Linearity(IP3)
Noisefigure(1dB)
Powerconsumption
Circuitpoweroptimization
• Majorpowerconsumers
Low-noiseamplifier
Hugedynamic
range105
High dutycycle
Antenna
interface
LocalOscillator
(LO)
Almostalwayson
Intermediate
Frequency (IF)
signalprocessing
IF/Baseband
Conversion
LNA
Baseband
processor
PA
Poweramplifier
High power
consumption
PhysicalLayer
MACLayer&
above
10
Circuitpoweroptimization(Contd.)
• Reducesupplyvoltage
– Negativelyimpactamplifierlinearity
• Higherintegration
– CMOSRF
– SoCandSiPintegration
• Power-savingmodes
11
Circuitpoweroptimization(Contd.)
• Power-savingmodes
– Completepoweroff
• (Circuitwake-uplatency+networkassociationlatency)
ontheorderofseconds
– Differentpower-savingmodes
• Lesspowersavingbutshortwake-uplatency
12
Power-savingmodes
RadioDeepSleep
Wake-uplatencyontheorderofmicro
seconds
Low-noiseamplifier
Antenna
interface
LocalOscillator
(LO)
Intermediate
Frequency (IF)
signalprocessing
PA
Poweramplifier
PhysicalLayer
IF/Baseband
Conversion
LNA
Baseband
processor
MACLayer&
above
13
Power-savingmodes(Contd.)
SleepMode
Wake-uplatencyontheorderof
milliseconds
Low-rateclockwith
savednetwork
association
information
Low-noiseamplifier
Antenna
interface
LocalOscillator
(LO)
Intermediate
Frequency (IF)
signalprocessing
PA
Poweramplifier
PhysicalLayer
IF/Baseband
Conversion
LNA
Baseband
processor
MACLayer&
above
14
Networkpoweroptimization
• Usepower-savingmodes
– Example:802.11wirelessLAN(WiFi)
• Infrastructuremode:Accesspointsandmobilenodes
– Example:Cellularnetworks
15
802.11infrastructuremode
• Mobilenodesniffsbasedona“ListenInterval”
– ListenIntervalismultipleofthe“beaconperiod”
• Beaconperiod:typically100ms
• DuringaListenInterval
– Accesspoint
• buffersdataformobilenode
• sendsoutatrafficindicationmap(TIM),announcingbuffered
data,everybeaconperiod
– Mobilenodestaysinpower-savingmode
• AfteraListenInterval
– MobilenodechecksTIMtoseewhetheritgetsbuffered
data
– Ifso,send“PS-Poll”askingfordata
16
Buffering/sniffingin802.11
Gast,802.11WirelessNetwork:TheDefinitiveGuide
802.15.1/Bluetooth usessimilarpower-savingprotocols: HoldandSniff modes
17
Cellularnetworks
• Discontinuoustransmission(DTX)
• Discontinuousreception(DRX)
Wirelessenergycost
• Connection
– Establishment
– Maintenance
• Transferdata
– Transmitvs.receive
19
Energyperbittransfer
Oppermann etal.,IEEEComm.Mag.2004
20
Wastefulwirelesscommunication
Time
Micropowermanagement
Spectrum
Efficiency-drivencognitiveradio
Space
Directionalcommunication
21
Spacewaste
• Omnitransmissionèhugepowerbypoweramplifier(PA)
22
Timewaste
• NetworkBandwidthUnder-Utilization
– Modestdataraterequiredbyapplications
• IE~1Mbps, MSNvideocall~3Mbps
– Bandwidthlimitofwiredlink
• 6Mbps DSLathome
1400
Data Size (Byte)
1200
1000
800
600
400
200
0
)
%
(
e 80
m
it
y
s 60
u
b
n
i
sl 40
av
re
t 20
n
i
el
d
I 0
100
0
0.2
0.4
0.6
Time (s)
0.8
1
User1
Time
User2
User3
23
User4
Energy
23
Spectrumwaste
24
Observedfroman802.11guser
Energyperbit
Distribution ofobserved 802.11gthroughput
1.E+02
1.E+03
1.E+04
1.E+05
1.E+06
1.E+07
Throughout(bps)
25
Temporalwaste
Radio Activity
1
0
0
0.2
0.4
0.6
0.8
1
Time(s)
90%oftime&80%ofenergyspentinidlelistening
26
Four802.11glaptopusers,oneweek
FundamentalproblemwithCSMA
• CSMA:CarrierSenseMultipleAccess
– Clientscompeteforairtime
• Incomingpacketsareunpredictable
27
FundamentalproblemwithCSMA
28
Micropowermanagement(µPM)
• Sleepduringidlelistening
• Wakeupintimetocatchretransmission
• Monitorthetrafficnottoabuseit
• ~30%powerreduction
• Noobservedqualitydegradation
J.LiuandL.Zhong,"Micropowermanagementofactive802.11interfaces,"inProc.MobiSys’08.
29
Directionalwaste
OngoingprojectwithAshutosh Sabharwal
Directionalwaste
Twowaystorealizedirectionality
• Passivedirectionalantennas
– Lowcost
– fixedbeampatterns
Desclos,Mahe,Reed,2001
• Digitalbeamforming
– Flexiblebeampatterns
– Highcost
32
Phased-arrayantennasystemfromFidelityComtech
ChallengeI:Rotation!!!
Solution:
Don’t getridoftheomni directionalantennas
Usemultiple directionalantennas
Butcanweselecttheright antennaintime?
33
ChallengeII:Multipathfading
34
ChallengeIII
• Canwedoitwithoutchanging
theinfrastructure?
35
Characterizingsmartphonerotation
• Howmuchdotheyrotate?
• Howfastdotheyrotate?
• 11HTCG1users,eachoneweek
• Logaccelerometerandcompassreadings
– 100Hzwhenwirelessinuse
36
Deviceorientationdescribedbythree
Eulerangles
• θ andφ basedontri-axisaccelerometer
• ψ basedontri-axiscompassandθ andφ
37
Rotationisnotthatmuch
• <120° persecond
θ
0.3
0.2
0.1
ψ
0.4
100ms
1s
10s
0.3
PDF
PDF
0.3
0.4
100ms
1s
10s
PDF
0.4
φ
0.2
0.1
100ms
1s
10s
0.2
0.1
0 -4
-3
-2
-1
0
1
2
3
10 10 10 10 10 10 10 10
0 -4
-3
-2
-1
0
1
2
3
10 10 10 10 10 10 10 10
0 -4
-3
-2
-1
0
1
2
3
10 10 10 10 10 10 10 10
Rotational speed(°/s)
Rotational speed(°/s)
Rotational speed(°/s)
38
Directionalityindoor
5dBi
8dBi
39
8dBiantenna
5dBiantenna
Measurementsetup
• RSSImeasuredatbothends
Datapackets
ACKpackets
41
Directional channel still reciprocal
NLOS ind. / 5dBi antenna
RSS(dBm)
-20
-30
-40
Dir-Client
Dir-AP
Omni-Client
Omni-AP
-50
-60
0
60 120 180 240 300 360
Direction(°)
42
Directional beats omni close to half of the time
5dBi
30
total time(%)
25
20
15
10
5
0
[0,0.1)
[0.1,1)
[1,10)
[10,inf)
superiority intervals(s)
Fieldcollectedrotationtracesreplayed
43
RSSispredictable(toabout100ms)
5dBi
Error(dB)
100
Zero order
First order
1
0.01
10ms
100ms
1s
10s
Prediction Intervals(s)
44
Multi-directionalantennadesign(MiDAS)
• OneRFchain,oneomniantenna,multipledirectionalantennas
• Directionalant.onlyusedfordatatransmitandACKReception
– Standardcompliance
– Tradeoffbetweenriskandbenefit
45
Packet-based antenna selection
• Assessanantennabyreceivingapacketwithit
– Leveragingchannelreciprocity
• Continuouslyassesstheselectedantenna
• Findoutthebestantennabyassessingthemone
byone
– Potentialriskofmissingpackets
• Staywithomni antennawhenRSSchanges
rapidly
• Nochangein802.11networkinfrastructure
46
Symbol-basedantennaselection
• AssessallantennasthroughaseriesofPHYsymbols
– SimilartoMIMOantennaselection
• NeedshelpfromPHYlayer
Antenna training
packet
Regular packet
SEL
ACK
47
Tracebasedevaluation
• Rotationtracesreplayedonthemotor
• RSSItracescollectedforallantennas
• Algorithmsevaluatedontracesoffline
-45
RSS(dB)
Dir 3
-50
Omni
-55
-60
0
Dir
1
Dir
3
5
10
15
time(second)
20
48
Anearlyprototype
1 omni antenna
3 directional antennas
WARP
Laptop
Controllable motor
FinalistofMobiCom’08BestStudentDemo
49
Thebusierthetraffic,thebetter
6
Gain(dB)
5
Upper bound
Symbol-based
Packet-based
4
3
2
1
0
10ms
100ms
1s
10s
Average Packet Interval
50
Two 5dBiantennasenough
6
Gain(dB)
5
Upper bound
Symbol-based
Packet-based
4
3
2
1
0
three
two-opp
two-adj
one
Antenna Configuration
51
Two5dBi antennasenough
NLOS ind. / 5dBi antenna
6
Upper bound
Symbol-based
Packet-based
4
-30
-40
Dir-Client
Dir-AP
Omni-Client
Omni-AP
-50
-60
0
60 120 180 240 300 360
Direction(°)
3
NLOS ind. / 8dBi antenna
-20
2
RSS(dBm)
Gain(dB)
5
RSS(dBm)
-20
1
0
5dBi
8dBi
Antenna Gain
-30
-40
Dir-Client
Dir-AP
Omni-Client
Omni-AP
-50
-60
0
60 120 180 240 300 360
Direction(°)
52
Real-timeexperiments:3dBgain
Avg. RSS(dB)
-45
Omni
Multi antenna
-60
-75
NLOS ind.
LOS ind.
Environment
•
•
•
•
Packet-basedantennaselection
Three5dBiantennas
Continuoustraffic(1400bytepackets)
Fieldcollectedrotationtrace
53
Throughputimprovement
Throughput(Mbps)
4
Omni
Multi antenna
3
2
1
0
NLOS ind.
LOS ind.
Environment
54
SNRvs.transmissionrate(802.11a)
Goodput (Mbps)
35
30
25
20
15
10
6Mbps
9Mbps
12Mbps
18Mbps
24Mbps
36Mbps
48Mbps
54Mbps
5
0
0
10
20
30
SNR (dB)
(D.Qiao,S.Choi,andK.Shin,2002)
55
MiDAS+rate adaptation+power control
• RecallthatRSSisquitepredictableupto100ms
200
Goodput Gain-Upperbound
Goodput Gain-MiDAS
TXpowerreduction-Upper bound
TXpowerreduction-MiDAS
%
150
100
50
0
0
10
20
30
40
OmniSNR(dB)
56
Protocolwaste
Cellularnetwork
Transmission
efficiency
Connection
Availability
WLAN(Wi-Fi)
Howtocombinethestrengthofboth
Wi-FiandCellularnetwork?
EstimateWi-Finetworkcondition
WITHOUTpoweringonWi-Fiinterface
58
UsecontexttopredictWiFi availability
• Visiblecellularnetworktowers
• Motion
• Timeoftheday,dayoftheweek
Statisticallearning
Context
Wi-Fi
Conditions
P(WiFi|Context)
AhmadRahmatiandLinZhong,"ContextforWireless:Context-sensitiveenergy-efficientwirelessdatatransfer," inProc.MobiSys’07.
JournalversionwithnewresultstoappearinIEEETMC
59
Cellularnetworkoffersclues
Cellularnetworkoffersclues
Wedon’tmovethatmuch
50%
40%
30%
20%
10%
0%
moving
(1,5]
(5,10]
(10,30] (30,60] (60,120] (120,inf)
Lengthofmotionlessperiod(minute)
Datacollectedfrom 2smartphone users2006
Shoehorned smartphonewith
accelerometer
62
Ourlifeisrepetitive
ProbabilityofsameWi-Fiavailability
(normalizedautocorreletaion)
1
0.9
0.8
0.7
0.6
0.5
0
1
2
3
4
Time(days)
Datacollectedfrom 11smartphone users
63
PredictionaccuracyofWi-Fi
availability
WiFi availabilityisHIGHLYpredictable
1
0.9
0.8
0.7
0.6
0.5
0
120
240
360
Time(minutes)
480
600
• Application
– MobileEKGmonitoring
– 35%batterylifeimprovement(12to17hours)
64