power reduction in jtrs radios with impacctpro
DESCRIPTION
Power Reduction in JTRS Radios with ImpacctPro. Jiwon Hahn , Dexin Li, Qiang Xie, Pai H. Chou, Nader Bagherzadeh, David W. Jensen*, Alan C. Tribble*. UC Irvine, EECS. *Rockwell Collins, Inc. MILCOM. November 2, 2004. Joint Tactical Radio System. Embedded in various military platforms. - PowerPoint PPT PresentationTRANSCRIPT
Power Reduction in JTRS Radios with ImpacctPro
Power Reduction in JTRS Radios with ImpacctPro
Jiwon Hahn, Dexin Li, Qiang Xie,
Pai H. Chou, Nader Bagherzadeh,
David W. Jensen*, Alan C. Tribble*
UC Irvine, EECS
November 2, 2004
*Rockwell Collins, Inc
MILCOM
2
Joint Tactical Radio SystemJoint Tactical Radio System
Embedded in various military platforms
3
JTRSJTRS
• Software Defined Radio (SDR) Technology earmarked for all DoD platforms by 2010
• Multi-band, multi-mode digital radio
• Layered open-architecture system
• Provides transmission interoperability between different networks such as army, legacy and commercial networks
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OutlineOutline
• Motivation and Goal
• Methodology
• Tool: ImpacctPro
• Simulation Results
• Conclusion
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Example JTRS RadioExample JTRS Radio
• JTRS Step 2B designed by Rockwell Collins• Consumes 9.7 MJ for realistic 10 hour mission!• No power management• Airborne radio form factor
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BlackPower
EncryptionDomain
ControllerTime Base
/ GPSBlack
I/O
PowerAmplifier
Transceiver ModemBlack
Processor
PowerAmplifier
Transceiver ModemBlack
Processor
PowerAmplifier
Transceiver ModemBlack
Processor
PowerAmplifier
Transceiver ModemBlack
Processor
RedProcessor
RedI/O
RedProcessor
RedProcessor
RedProcessor
Channel 4(MilStar)
Channel 3(ATC)
Channel 2(SATCOM)
Channel 1(Link 16)
RedPower
SystemPower
Challenges for Power Reduction
Challenges for Power Reduction
• Complex Architecture• 28 Subsystems• 4 Parallel Channels• 3 Shared resources
• Diverse Components• Different power manageability
• Power consumption levels • Number of power modes• Mode transition characteristics
• Dependencies
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Enhancing Power Management Features
Enhancing Power Management Features
• Development Cost • Hardware and software modifications• Extensive testing
• Evaluation• Not all power modes usable due to system
complexity• Analogy of Amdahl’s Law
• Need a methodology and tool
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OverviewOverview
Tool(CORBA client)
Radio
Control Commands
Status & Measurement
CORBA
(CORBA Server)
SimulationEngine
Model JTRS
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Steps in Methodology Steps in Methodology
• Design Time• System Modeling• Power Optimization
• Runtime• Simulation or Measurement• Profiling • Visualization
(1)
ImpacctPro(2)
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Time La.. Lo. Al. Wf0.11 0.31 -0.34 1000ft Link160.20 0.31 -0.34 1000ft Link160.21 0.31 -0.34 1000ft Link160.41 0.32 -0.34 1000ft Link160.51 0.32 -0.34 1001ft Link160.64 0.33 -0.34 1001ft Link160.71 0.33 -0.34 1001ft Link161.11 0.41 -0.34 1001ft Link162.11 0.41 -0.34 1001ft Link16
onon stbstb4W/1us
2W/0.1ms
Modem
Proc Modem
onon onon
• Architecture• Considers dependency in the system
level context
• Captures mode transition overhead
• Application• Parses mission profile to extract
scenario parameters and workload• eg., 3D location, waveform, SNR, etc
• eg., messages (task)
System ModelingSystem Modeling
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Power OptimizationPower Optimization
• Workload-driven• Exploit idle periods
• Savings rely on input pattern
• Utilize non-operational power modes
• Mission-aware• Exploit scenario knowledge
• Adapt to scenario parameters
• Save active power
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Power OptimizationPower Optimization
• Workload-driven• Exploit idle periods
• Savings rely on input pattern
• Utilize non-operational power modes
• Mission-aware• Exploit scenario knowledge
• Adapt to scenario parameters
• Save active power
Resource
Full-ON
time
power
on on on
offsleep
sleep
off
task
power saving
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Power OptimizationPower Optimization
• Workload-driven• Exploit idle periods
• Savings rely on input pattern
• Utilize non-operational power modes
• Mission-aware• Exploit scenario knowledge
• Adapt to scenario parameters
• Save active power
time
power
Resource
scenario parameters
task
Full-ON
powerrequirement
full-onmid-on
low-on
power saving
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Example: PA algorithmExample: PA algorithm
Time(sec)
Distance (ft)
1. Get distance from mission profile
4. Assign Active PA modes
2. Translate distance to the min. TX power using communication equation
3. Get timestamped msg. groups from mission profile
Power(dBW)
high lowpower
AA
A
15
II
Example: PA algorithmExample: PA algorithm
Time(sec)
1. Get distance from mission profile
4. Assign Active PA modes
2. Get timestamped msg. groups from mission profile
3. Translate distance to the min. TX power using communication equation
5. Assign optimal Idle PA modes
high lowpower
II
Power(dBW)
I
AA
A II
I
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Example: Mission-aware PA algorithm
Example: Mission-aware PA algorithm
Time(sec)
1. Get distance from mission profile
4. Assign Active PA modes
5. Assign optimal Idle PA modes
6. Output power command sequence for PA
2. Get timestamped msg. groups from mission profile
3. Translate distance to the min. TX power using communication equation
high lowpower
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Design Tool: ImpacctProDesign Tool: ImpacctPro
• Modeling• System description with power models
• Optimization• Optimized power control commands
• Simulation and Analysis• Hotspot identification• Power profiles of component, channel, system• Multi-granular, interactive GUI• Report generation
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ImpacctPro: System Description
ImpacctPro: System Description
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ImpacctPro: Real-time Simulation
ImpacctPro: Real-time Simulation
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ImpacctPro: Power ProfileImpacctPro: Power Profile
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ImpacctPro: Hotspot AnalysisImpacctPro:
Hotspot Analysis
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ImpacctPro: Report GenerationImpacctPro:
Report Generation
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SimulationSimulation
• Our technique applied on Rockwell Collins Step-2B prototype
• Simulated mission profiles including existing UCAV mission scenarios with communication activities• Variation of mission length: 30 sec ~ 10 hrs
• Variation of message density: 0.1 ~ 24.4 msg/sec
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Result 1. Energy SavingsResult 1. Energy Savings
Mission Length (sec)
Workload (msg/sec)
Baseline (J)
Optimized (J)
Energy Savings
m1 30 14.4 8136.9 1412.2 82.64 %
m2 80 24.4 21777.4 4572.9 79.00 %
m3 332 10.2 90330.5 17113.1 81.04 %
m4 480 12.3 130643.1 24960.0 80.89 %
m5 626 9.88 170184.2 30421.6 82.12 %
m6 3592 0.10 850921.0 91303/8 89.27 %
m7 35920 8.56 9750431.7 1617187.8 83.41 %
Baseline is the system’s power consumption without power management. In the baseline, PA is assumed to be on RX mode (5W) instead of TX mode (372W).
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Result 2. Hotspot Identification
Result 2. Hotspot Identification
Before After
PA was the largest power consumer before the optimization, which reduces its energy from 45% to below 10%
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Result 3. Simulation SpeedResult 3. Simulation Speed90 times fasterthan real time!
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ConclusionConclusion
• Power Saving• Integrated mission-aware and workload-driven power
management to achieve substantial power savings
• Experimental results on realistic mission profiles achieved 79%~89% energy reduction
• Tool• Captured the new methodology in ImpacctPro for
systematic power management policy generation
• Provided a powerful design exploration capability that guides the future system specifications
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Thank you !
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Related WorkRelated Work
• Dynamic Voltage Scaling (DVS)• Processor centric• May increase power consumption of other hw resources
due to extended execution time• Overhead is often ignored
• Dynamic Power Management (DPM)• I/O centric• Devices are treated independently
System Level
• This work• Captures all devices and their inter-dependencies• Overhead is modeled• Mission aware
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PA Transmission PowerPA Transmission Power
• Minimum required PA transmission power can be calculated by the following equation:
• Equation derived by our assumptions:• Transmission Power depends only on the communication Distance
and the operating Frequency
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Simulation TimeSimulation Time