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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.

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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

*Rockwell Collins, Inc

MILCOM

November 2, 2004

joint tactical radio system
Joint Tactical Radio System

Embedded in various military platforms

slide3
JTRS
  • 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
outline
Outline
  • Motivation and Goal
  • Methodology
  • Tool: ImpacctPro
  • Simulation Results
  • Conclusion
example jtrs radio
Example 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
challenges for power reduction

Power

Amplifier

Transceiver

Modem

Black

Processor

Channel 4

(MilStar)

Red

Processor

Red

Power

Power

Amplifier

Transceiver

Modem

Black

Processor

Channel 3

(ATC)

Red

Processor

Red

I/O

Power

Amplifier

Transceiver

Modem

Black

Processor

Channel 2

(SATCOM)

Red

Processor

Power

Amplifier

Transceiver

Modem

Black

Processor

Channel 1

(Link 16)

Red

Processor

Black

I/O

Black

Power

Time Base

/ GPS

Encryption

Domain

Controller

System

Power

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
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
overview

Radio

Model

Simulation

Engine

Overview

Tool

(CORBA client)

JTRS

Status &

Measurement

(CORBA Server)

CORBA

Control

Commands

steps in methodology

(1)

(2)

ImpacctPro

Steps in Methodology
  • Design Time
    • System Modeling
    • Power Optimization
  • Runtime
    • Simulation or Measurement
    • Profiling
    • Visualization
system modeling
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)

Proc

Modem

on

on

Modem

2W/0.1ms

on

stb

4W/1us

System Modeling

Time La.. Lo. Al. Wf

0.11 0.31 -0.34 1000ft Link16

0.20 0.31 -0.34 1000ft Link16

0.21 0.31 -0.34 1000ft Link16

0.41 0.32 -0.34 1000ft Link16

0.51 0.32 -0.34 1001ft Link16

0.64 0.33 -0.34 1001ft Link16

0.71 0.33 -0.34 1001ft Link16

1.11 0.41 -0.34 1001ft Link16

2.11 0.41 -0.34 1001ft Link16

power 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

Power Optimization
power optimization1
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

sleep

off

power

on

on

on

off

sleep

time

power saving

Power Optimization

task

Resource

Full-ON

power optimization2
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

power

requirement

power saving

power

time

full-on

mid-on

low-on

Power Optimization

scenario parameters

task

Resource

Full-ON

example pa algorithm

Power

(dBW)

Distance

(ft)

A

A

A

Time

(sec)

Example: PA algorithm

1. Get distance from mission profile

2. Translate distance to the min. TX power using communication equation

3. Get timestamped msg. groups from mission profile

4. Assign Active PA modes

power

high

low

example pa algorithm1

1. Get distance from mission profile

A

I

2. Get timestamped msg. groups from mission profile

A

I

3. Translate distance to the min. TX power using communication equation

A

I

I

I

4. Assign Active PA modes

I

I

I

Time

(sec)

Example: PA algorithm

Power

(dBW)

5. Assign optimal Idle PA modes

power

high

low

example mission aware pa algorithm

Time

(sec)

Example: Mission-aware PA algorithm

1. Get distance from mission profile

2. Get timestamped msg. groups from mission profile

3. Translate distance to the min. TX power using communication equation

4. Assign Active PA modes

5. Assign optimal Idle PA modes

6. Output power command sequence for PA

power

high

low

design tool impacctpro
Design 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
simulation
Simulation
  • 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
  • Our technique applied on Rockwell Collins Step-2B prototype
result 1 energy savings
Result 1. Energy Savings

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).

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%

result 3 simulation speed
Result 3. Simulation Speed

90 times faster

than real time!

conclusion
Conclusion
  • 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
related work

System Level

Related 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
  • This work
  • Captures all devices and their inter-dependencies
  • Overhead is modeled
  • Mission aware
pa transmission power
PA 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