Energy Efficiency for Future Wireless Broadband Networks
IEEE 802.16 Presentation Submission Template (Rev. 9)
Document Number:
IEEE C802.16-10/0008r1
Date Submitted:
2010-01-12
Source:
Nageen Himayat, Shilpa Talwar, Kerstin Johnsson,
E-mail: nageen.himayat@intel.com
Shantidev Mohanty, Muthaiah Venkatachalam, Hujun Yin, David Bormann, Intel Corporation
Sergey Andreev, Pavel Gonchukov, Andrey Turlikov, SUAI, Russia
Guowang Miao, Geoffrey Li, Georgia Institute of Technology
Venue:
San Diego, CA, USA
Base Contribution:
None
Purpose:
For discussion in the Project Planning Adhoc
Notice:
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listed in the “Source(s)” field above. It is offered as a basis for discussion. It is not binding on the contributor(s), who reserve(s) the right to add, amend or
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Energy Efficiency for Future Wireless
Broadband Networks
Input for 802-wide Tutorial in March
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Agenda
•
•
•
•
Current Trends
Measuring Energy Efficiency
Techniques for Energy Efficiency
Summary & Recommendations
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Current Trends in Wireless Energy Efficiency
•
Mobile devices are battery constrained
– Slow improvements in battery technology
– Growing data rates and usage with multi-media rich applications
– Growth in multi-protocol devices
•
Wireless network energy consumption increasingly important
– “Green Networks”
– Exponential growth in traffic drives up power consumption
– Growth in density of infrastructure elements and hardware complexity
•
M2M usages require ultra low power (sensors, embedded devices etc.)
•
Significant but insufficient advances in power management techniques
•
Current systems “orders of magnitude” away from theoretical numbers
Systematically target energy efficiency for future wireless
broadband systems
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Measuring Energy Efficiency
Power
Active State (TX/RX)
Power required
for reliable reception
of information
(TX power dominates
power budget)
Transmit RF
Power
Processing
Power (TX/RX)
Idle Power
Idle State
Time
Power consumed in
transmit/receive
electronics
Overhead power
consumed during
control signaling
E total  PActive RFTActive  PProces sin g TActive  PidleTidle  PcontrolTcontrol
Energy required for reliable
transmission of information
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Energy overhead of
transmitting information
Challenging to Track “Implementation Dependent” Energy Efficiency
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Metrics for Wireless Energy Efficiency
•Theoretical benchmark available from Shannon’s Law
•Minimum energy to receive an information bit reliably (ignore all overhead)
Eb,min  kT ln( 2) ( Joule / bit )
 2.87 x1012 nJ / bit
T=300K
K= 1.381 10^(-23) J/K
Example Metrics
Eb ,ave  Ave. Power / Ave. Goodput ( Joule / bit )
•
User Metrics:
•
Network Metrics: Suitable aggregation of per user metrics
•
Relative Metrics: Absolute Energy Efficiency*
dB  10 log 10( Eb , Ave / Eb ,min )
•
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*source: U. of Essex
Other variations are possible: bits/Joule (similar to Joules/bit, power/user etc.)
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Example Efficiency of Systems
Aggressive estimates
for 802.16m Uplink:
Median Absolute
Energy Efficiency
~142 dB (Eb: 500 nJ/bit)
Source: An Absolute Energy Efficiency Metric, Green Grids, 2009 (Parker, Walker, U. of Essex)
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Example: Energy Efficiency for 802.16m Uplink
•500 meter cell (reuse1)
• Uplink Variable SINR Target Power Control
•TX Processing power 100mW, Idle power = 10 mW, Amplifier Efficiency =20%
•No control overhead or traffic model assumed
•Additional simulation assumptions in backup
Percentile
Energy Efficiency
(Mbits/Joule)
Energy Efficiency
(Micro-Joules/bit)
Absolute Energy
Efficiency (dB)
90%
5
0.2
138
50%
2
0.5
142
10%
0.5
2
148
X% CDF points of individual user energy efficiency
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Energy Efficient Technologies
Category
Techniques
Advantages
Issues
Link
Optimizations
(PHY)
MIMO
Lower transmit power
Overhead in RF chains
Energy-Aware Link Adaptation
Turn off MIMO RX chains
Loss in coverage/throughput
Link
Optimizations
(MAC)
Adv. Power Management
Prolonged sleep/ idle
cycles
Protocol complexity, latency
Adv. Radio Resource Management
Energy efficient resource
allocation
Loss in coverage/throughput
Multi-tier Network Architectures
Lower transmit power
Overhead of increased
network elements
Centralized Network Architecture
(w/ distributed antennas)
Lower transmit
power/reduced overhead
Complexity and latency
Cooperative Protocols
Lower transmit power
Cooperation overhead
Load Dependent Network
Availability
Power down network
elements for light loads
Protocol complexity
Spectrum Aggregation
Lower transmit power
Overhead of multiple protocols
Limit “control” interfaces
Lower power with reduced
control overhead
Protocol Complexity
Network
Optimizations
(Low duty cycle)
(Client, Network)
Heterogeneous
Networks
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Summary & Recommendations
• Continued improvements in wireless broadband energy efficiency are
required to address:
– Increased traffic demand
– Limited battery capacity
– New M2M usage models
• Establish metrics to target systematic energy-efficient design
• Develop evaluation methodology to measure energy efficiency
• Establish energy efficiency targets for future wireless broadband standards
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Backup
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Simulation Assumptions
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System Parameter
Values
Cell geometry
19 cell system w/ wrap around, 3 sectors,
reuse 1
Intersite Distance
500m
Carrier Frequency
2.5 GHZ
System Bandwidth
10 MHz (1024 FFT size)
Power Control
Variable SINR Target
Number of Users/Sector
10
Scheduling
Proportional Fair
MIMO configuration
1x2
Circuit Power, Idle Power
100 mW, 10 mW
Maximum Transmit Power
23 dBm
Channel Model
ITU-Ped B, 3 kph
Link to System Mapping
RBIR
Link Adaptation Metric for EE
Mutual Information
HARQ
Enabled
Sub-channel Permutation
DRU
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