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

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Joint Tactical Radio SystemJoint Tactical Radio System

Embedded in various military platforms

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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

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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