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simulation-based approach for performance evaluation of sdr - - PowerPoint PPT Presentation

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A simulation-based approach for performance evaluation of sdr baseband architectures Brussels, Belgium 28 th June, 2012 Goal and objectives Trends in the field of radio communication Mobile devices with more and more wireless

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SLIDE 1

A simulation-based approach for performance evaluation

  • f

sdr baseband architectures

Brussels, Belgium 28th June, 2012

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SLIDE 2

Goal and objectives

2

  • Trends in the field of radio communication

Mobile devices with more and more wireless interfaces, user applications and adaptation capabilities Parallel architectures clustered by application category to implement mobile terminals

  • Goal of our work

To facilitate performance evaluation of SDR baseband architectures

  • Objectives of this presentation

To propose simulation-based approach to analyze and compare the growing number

  • f potential architectures

To illustrate benefits of this approach with a realistic adaptive multi-service system

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SLIDE 3

Model requirements

3

  • Specification design step

Definition of the system properties and its performance requirements Executable model to evaluate and compare performances of candidate architectures

  • Fundamental criteria to respect

Quick-to-develop and lightweight to decrease modeling effort of the designer Accuracy and simulation speed for different use cases

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SLIDE 4

F11 F12 P1 Mem. Node F2 P2 A1

M3

A2 s0 s1 s2

M3 M4

t = Tk

M1

Considered system architecture Performance model of system architecture

CcA2=0; CcA2=Ccs1; k=N AND t = Tj t = Tl

s3

M4

CcA2=Ccs2; CcA2=Ccs3; k<N AND t=Tj

SA TCA2

TCA1

/ k:=k+1; t:=0; / k:=0; / t:=0; / t:=0;

A11 A12 TCA11

TCA12 M2

Considered modeling approach

4

  • Performance evaluation of system architectures
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SLIDE 5

Radio communication system

System data flow System management

Service management Downlink UTRA Service request RAT discovery RAT information Service response Uplink UTRA Downlink Wi-Fi Application request Application response Voice frame Web page Video frame Voice frame Active application Application and RAT QoS information RAT control Packet data voice Packet data web Packet data video Packet data voice Application processing Radio reception and transmission RAT management Switching request Voice QoS Web QoS Video QoS

Network environment User

Voice processing Web processing Video processing Voice processing UTRA reception WiFi reception UTRA transmission

Considered case studied

5

  • Activity diagram of an adaptive multi-standard and multi-application

system and its environment

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SLIDE 6

Modeling the system environment

6

  • Modeling technique based on scenario files

Network environment User

WiFi Transmission

Radio communication system

Application requests

Waiting Application request

Send request

Application request

Network environment control

Waiting Max rate radio links

Update Rat data rate

UTRA Transmission

Max rate radio links Downlink UTRA Downlink WiFi

reading reading

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SLIDE 7

Radio reception

WiFi reception UTRA reception

Demux & Assemb

Stopped

RAT control=start

Started

RAT control

Downlink WiFi Packet data voice 10ms up to 480 bytes Downlink UTRA up to 347µs

t1 t2

up to 2347 bytes 1

t1 t2

1 20 ms 244 bits

t1 t2

1 1s ≈12000 bytes 1

t1 t2

1 s 8000 bytes

t1 t2

1

RAT control=stop

Cond1

DownlinkUTRA

Cond2 Cond3 Cond4 Packet data web Packet data video

Packet data voice Packet data web Packet data video

[UTRA] [WIFI]

Modeling the communication interfaces

7

  • Activity diagram of adaptive radio interfaces
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SLIDE 8

Generation and simulation

  • f the performance model

8

  • Graphical modeler and ANSI C/C++ code editor to capture the

performance model

  • Generation of executable SystemC code from capture model
  • Simulation of the executable SystemC program according to complex use

case scenarios

Evaluation of real time performances Evaluation of the expected ressources

Specification SystemC executable code Graphical modeler and code editor C++ code Functional verification and performance evaluation Use cases scenario

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SLIDE 9

Service request System management Service response RAT discovery RAT control Application response Application request Service management Web page WiFi reception Video frame UTRA reception Voice frame Switching request User 60 50 40 30 10 20 Time (s) 60 50 40 30 10 20 Time (s) 200 400 600 800 1000 Web Voice Video Latency (ms) Threshold video 500ms Threshold Web 1s Threshold voice 20ms 1s VoiceCall Start 15s WebSession Start 16s VideoStreaming Start 2s WebSession Stop 25s VideoStreaming Stop 8s VoiceCall Stop UTRAN WLAN 0s UTRAN 384 30s WLAN 1500 9s UTRAN 130 130 kbps 1500 kbps 0 kbps 384 kbps

Temporal behavior analysis

  • f the system

9

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SLIDE 10

Performance evaluation

  • f the flexible baseband architecture

10

P1

WiFi reception UTRA reception

Downlink WiFi Packet data voice

Radio reception and transmission

Downlink UTRA Packet data web Packet data video

Studied architecture Performance model of radio reception and transmission architecture

WiFi baseband functions TCWiFi TCUTRA UTRA baseband functions

  • Studied architecture to perform baseband processing related to

activities UTRA and WiFi reception

Architecture based on a set of dedicated hardware resources Performance model express computational complexity per time unit each function causes on the resources when executed

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SLIDE 11

Simulation results of the model

11 t(ms) Global computational complexity per time unit (MOPS) 40040 40080 100 200 300 400 500 600 600 700 800 900 1000 1100 1200 1300 40060

77 MOPS 1260 MOPS 1183 MOPS

UTRA decoding Wi-Fi decoding

(1) (2) (3)

  • Evolution in time of the required computational complexity per time

unit (in MOPS) for UTRA and WiFi decoding

Observation for studied architecture and operating scenario considered Maximal computational complexity per time unit observed Resource utilization of P1

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SLIDE 12

Sum-up and conclusion

12

  • Sum-up

Simulation-based approach and modeling technique to evaluate efficiently performances of candidate SDR baseband architectures Simulate easily multiple complex use cases Study dynamic and non determinist ic effects in the architecture model

  • Further work

Validation of estimates providing by simulation Applying the same modeling principle to other non functional properties such as dynamic power consumption

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SLIDE 13

A simulation-based approach for performance evaluation

  • f

sdr baseband architectures

Brussels, Belgium 28th June, 2012