Power Consumption by Wireless
Communication
Lin Zhong
ELEC518, Spring 2011
Power consumption (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)
Power consumption (T-Mobile)
Cellular
Wi-Fi
10000
Bluetooth
1000
10
1
Transmission
Connected
Transmission
Connected
Transmission
Connected
Paging
Discoverable
Speaker
Keyboard lighting
LCD lighting
LCD
Computing
IDLE-Flight mode
3
Power consumption (Contd.)
• Theoretical limits
– Receiving energy per bit > N * 10-0.159
• N: Noise spectral power level
• Wideband communication
PTX∝ PRX
*da
PRX
Distance: d
Propagation constant: a (1.81-5.22)
4
Power consumption (Contd.)
• What increases power consumption
– Government regulation (FCC)
• Available spectrum band (Higher band, higher power)
• Limited bandwidth
• Limited transmission power
– Noise and reliability
– Higher capacity
• Multiple access (CDMA, TDMA etc.)
– Security
– Addressability (TCP/IP)
– More……
5
Wireless system architecture
Network protocol stack Hardware implementation
Application
Transport
Host computer
Network
Data link
Baseband
Network interface
Physical
RF front ends
6
Power consumption (Contd.)
Low-noise amplifier
Antenna
interface
Local Oscillator
(LO)
Intermediate
Frequency (IF)
signal processing
PA
Power amplifier
Physical Layer
IF/Baseband
Conversion
LNA
Baseband
processor
MAC Layer &
above
>60% non-display power consumed in RF
RF technologies improve much slower than IC
7
Power consumption (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
processing
5
Source: Li et al, 2004
8
Low-noise amplifier (LNA)
•
•
•
•
•
Bandwidth (same as the signal)
Gain (~20dB)
Linearity (IP3)
Noise figure (1dB)
Power consumption
Circuit power optimization
• Major power consumers
Low-noise amplifier
Huge dynamic
range 105
High duty cycle
Antenna
interface
Local Oscillator
(LO)
Almost always on
Intermediate
Frequency (IF)
signal processing
IF/Baseband
Conversion
LNA
Baseband
processor
PA
Power amplifier
High power
consumption
Physical Layer
MAC Layer &
above
10
Circuit power optimization (Contd.)
• Reduce supply voltage
– Negatively impact amplifier linearity
• Higher integration
– CMOS RF
– SoC and SiP integration
• Power-saving modes
11
Circuit power optimization (Contd.)
• Power-saving modes
– Complete power off
• (Circuit wake-up latency + network association latency)
on the order of seconds
– Different power-saving modes
• Less power saving but short wake-up latency
12
Power-saving modes
Radio Deep Sleep
Wake-up latency on the order of micro
seconds
Low-noise amplifier
Antenna
interface
Local Oscillator
(LO)
Intermediate
Frequency (IF)
signal processing
Baseband
processor
MAC Layer &
above
PA
Power amplifier
IF/Baseband
Conversion
LNA
Physical Layer
13
Power-saving modes (Contd.)
Sleep Mode
Wake-up latency on the order of
milliseconds
Low-rate clock with
saved network
association
information
Low-noise amplifier
Antenna
interface
Local Oscillator
(LO)
Intermediate
Frequency (IF)
signal processing
Baseband
processor
MAC Layer &
above
PA
Power amplifier
IF/Baseband
Conversion
LNA
Physical Layer
14
Network power optimization
• Use power-saving modes
– Example: 802.11 wireless LAN (WiFi)
• Infrastructure mode: Access points and mobile nodes
– Example: Cellular networks
15
802.11 infrastructure mode
• Mobile node sniffs based on a “Listen Interval”
– Listen Interval is multiple of the “beacon period”
• Beacon period: typically 100ms
• During a Listen Interval
– Access point
• buffers data for mobile node
• sends out a traffic indication map (TIM), announcing buffered
data, every beacon period
– Mobile node stays in power-saving mode
• After a Listen Interval
– Mobile node checks TIM to see whether it gets buffered
data
– If so, send “PS-Poll” asking for data
16
Buffering/sniffing in 802.11
Gast, 802.11 Wireless Network: The Definitive Guide
802.15.1/Bluetooth uses similar power-saving protocols: Hold and Sniff modes
17
Cellular networks
• Discontinuous transmission (DTX)
• Discontinuous reception (DRX)
Wireless energy cost
• Connection
– Establishment
– Maintenance
• Transfer data
– Transmit vs. receive
19
Energy per bit transfer
Oppermann et al., IEEE Comm. Mag. 2004
20
Wasteful wireless communication
Time
Micro power management
Spectrum
Efficiency-driven cognitive radio
Space
Directional communication
21
Space waste
• Omni transmission huge power by power amplifier (PA)
22
Time waste
• Network Bandwidth Under-Utilization
– Modest data rate required by applications
• IE ~ 1Mbps, MSN video call ~ 3Mbps
– Bandwidth limit of wired link
• 6Mbps DSL at home
Idle intervals in busy time (%)
1400
Data Size (Byte)
1200
1000
800
600
400
200
0
0
0.2
0.4
0.6
Time (s)
0.8
1
100
User1
User2
User3
User4
80
60
40
20
0
Time
23
Energy
23
Spectrum waste
24
Observed from an 802.11g user
Energy per bit
Distribution of observed 802.11g throughput
1.E+02
1.E+03
1.E+04
1.E+05
1.E+06
1.E+07
Throughout (bps)
25
Temporal waste
Radio Activity
1
0
0
0.2
0.4
0.6
0.8
1
Time(s)
90% of time & 80% of energy spent in idle listening
26
Four 802.11g laptop users, one week
Fundamental problem with CSMA
• CSMA: Carrier Sense Multiple Access
– Clients compete for air time
• Incoming packets are unpredictable
27
Fundamental problem with CSMA
28
Micro power management (µPM)
• Sleep during idle listening
• Wake up in time to catch retransmission
• Monitor the traffic not to abuse it
• ~30% power reduction
• No observed quality degradation
J. Liu and L. Zhong, "Micro power management of active 802.11 interfaces," in Proc. MobiSys’08.
29
Directional waste
Ongoing project with Ashutosh Sabharwal
Directional waste
Two ways to realize directionality
• Passive directional antennas
– Low cost
– fixed beam patterns
Desclos, Mahe, Reed, 2001
• Digital beamforming
– Flexible beam patterns
– High cost
32
Phased-array antenna system from Fidelity Comtech
Challenge I: Rotation!!!
Solution:
Don’t get rid of the omni directional antennas
Use multiple directional antennas
But can we select the right antenna in time?
33
Challenge II: Multipath fading
34
Challenge III
• Can we do it without changing
the infrastructure?
35
Characterizing smartphone rotation
• How much do they rotate?
• How fast do they rotate?
• 11 HTC G1 users, each one week
• Log accelerometer and compass readings
– 100Hz when wireless in use
36
Device orientation described by three
Euler angles
• θ and φ based on tri-axis accelerometer
• ψ based on tri-axis compass and θ and φ
37
Rotation is not that much
• <120° per second


100ms
1s
10s
0.3
PDF
PDF
0.3

0.4
0.2
0.1
0.4
100ms
1s
10s
0.3
PDF
0.4
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
Directionality indoor
5 dBi
8 dBi
39
8dBi antenna
5dBi antenna
Measurement setup
• RSSI measured at both ends
Data packets
ACK packets
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)
Field collected rotation traces replayed
43
RSS is predictable (to about 100ms)
5dBi
100
Error(dB)
Zero order
First order
1
0.01
10ms
100ms
1s
10s
Prediction Intervals(s)
44
Multi-directional antenna design (MiDAS)
• One RF chain, one omni antenna, multiple directional antennas
Omni-directional antenna
Antenna switch
Transceiver
...
Directional
antennas
RSSI
Antenna selection
• Directional ant. only used for data transmit and ACK Reception
– Standard compliance
– Tradeoff between risk and benefit
45
Packet-based antenna selection
• Assess an antenna by receiving a packet with it
– Leveraging channel reciprocity
• Continuously assess the selected antenna
• Find out the best antenna by assessing them one
by one
– Potential risk of missing packets
• Stay with omni antenna when RSS changes
rapidly
• No change in 802.11 network infrastructure
46
Symbol-based antenna selection
• Assess all antennas through a series of PHY symbols
– Similar to MIMO antenna selection
• Needs help from PHY layer
Antenna training
packet
Regular packet
SEL
ACK
47
Trace based evaluation
• Rotation traces replayed on the motor
• RSSI traces collected for all antennas
• Algorithms evaluated on traces offline
-45
RSS(dB)
Dir 3
-50
Omni
-55
-60
0
Dir
1
Dir
3
5
10
15
20
time(second)
48
An early prototype
1 omni antenna
3 directional antennas
WARP
Laptop
Controllable motor
Finalist of MobiCom’08 Best Student Demo
49
The busier the traffic, the better
6
Gain(dB)
5
Upper bound
Symbol-based
Packet-based
4
3
2
1
0
10ms
100ms
1s
10s
Average Packet Interval
50
Two 5dBi antennas enough
6
Gain(dB)
5
Upper bound
Symbol-based
Packet-based
4
3
2
1
0
three
two-opp
two-adj
one
Antenna Configuration
51
Two 5dBi antennas enough
NLOS ind. / 5dBi antenna
6
Upper bound
Symbol-based
Packet-based
-30
-40
Dir-Client
Dir-AP
Omni-Client
Omni-AP
-50
-60
4
0
3
-20
2
1
0
60 120 180 240 300 360
Direction()
NLOS ind. / 8dBi antenna
RSS(dBm)
Gain(dB)
5
RSS(dBm)
-20
-30
-40
Dir-Client
Dir-AP
Omni-Client
Omni-AP
-50
-60
5dBi
8dBi
Antenna Gain
0
60 120 180 240 300 360
Direction()
52
Real-time experiments: 3dB gain
Avg. RSS(dB)
-45
Omni
Multi antenna
-60
-75
NLOS ind.
LOS ind.
Environment
•
•
•
•
Packet-based antenna selection
Three 5dBi antennas
Continuous traffic (1400 byte packets)
Field collected rotation trace
53
Throughput improvement
Throughput(Mbps)
4
Omni
Multi antenna
3
2
1
0
NLOS ind.
LOS ind.
Environment
54
SNR vs. transmission rate (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, and K. Shin, 2002)
55
MiDAS+rate adaptation+power control
• Recall200that RSS is quite predictable up to 100ms
Goodput Gain-Upper bound
Goodput Gain-MiDAS
TX power reduction-Upper bound
TX power reduction-MiDAS
%
150
100
50
0
0
10
20
30
40
Omni SNR(dB)
56
Protocol waste
Cellular network
Transmission
efficiency
Connection
Availability
WLAN (Wi-Fi)
How to combine the strength of both
Wi-Fi and Cellular network?
Estimate Wi-Fi network condition
WITHOUT powering on Wi-Fi interface
58
Use context to predict WiFi availability
• Visible cellular network towers
• Motion
• Time of the day, day of the week
Statistical learning
Context
Wi-Fi
Conditions
P(WiFi|Context)
Ahmad Rahmati and Lin Zhong, "Context for Wireless: Context-sensitive energy-efficient wireless data transfer," in Proc. MobiSys’07.
Journal version with new results to appear in IEEE TMC
59
Cellular network offers clues
Cellular network offers clues
We don’t move that much
50%
40%
30%
20%
10%
0%
moving
(1, 5]
(5, 10]
(10, 30] (30, 60] (60, 120] (120, inf)
Length of motionless period (minute)
Data collected from 2 smartphone users 2006
Shoehorned smartphone with
accelerometer
62
Our life is repetitive
Probability of same Wi-Fi availability
(normalized autocorreletaion)
1
0.9
0.8
0.7
0.6
0.5
0
1
2
3
4
Time (days)
Data collected from 11 smartphone users
63
Prediction accuracy of Wi-Fi
availability
WiFi availability is HIGHLY predictable
1
0.9
0.8
0.7
0.6
0.5
0
120
240
360
Time (minutes)
480
600
• Application
– Mobile EKG monitoring
– 35% battery life improvement (12 to 17 hours)
64