This document discusses blind compensation and traffic shaping techniques for video streaming in automobile applications. It proposes using forward error correction, blind compensation, and traffic shaping to address problems with interference, packet loss, and network congestion over wireless links. The techniques are analyzed using MATLAB and simulated using an OPNET model of a vehicular communications system with cars acting as peers in an ad hoc WiMax network. The goal is to develop an advanced vehicular communications platform to promote safety.

1. BLIND COMPENSATION AND SHAPING
FOR VIDEO USAGE IN AUTO
APPLICATION
Jun Huang
Adjunct Professor
The Ottawa-Carleton Institute for Electrical and Computer Engineering
Chief Architect
www.genieview.com
Prepared for UCSD ECE Seminar
on April 30, 2009

2. Where is Ottawa – Small Town Story

3. Table of Content
•Project: Advanced Vehicular Communications Platform
– Objective: Promote Safe Community
– Experimental: Police Car Application
•Problems Encountered:
– Layer 1: Link with interference and fading
– Layer 2: Path that could add or drop bytes
– Layer 3: Network that could congested
•Solutions Proposed:
– Forward Error Correction
– Blind Compensation
– Traffic Shaping
•Methodology
– MATLAB calculation
– OPNET simulation

4. Project: Auto21 Webpage
Wife s/w, me h/w, kids on road, dad retired, students testing!

5. Industry: 180 Companies!

6. Academic: 44 Universities

7. 55 Projects

8. Our Sole Goal for Telematics over WiFi and
WiMax Adhoc Networks
• Objectives
o Develop an Advanced Vehicular Communications
Platform (AVCP)
Scalable
Reliable
Secure
o Promote safe road and safe community

9. Highway Chain Accident – Dozen Cars
Trashed!

10. Adhoc Prevent Highway Chain Accident
Crash
Slow down And stop
Maximum 75 mph – 111 feet per second
Minimum 30 frame per second
3.7 feet per frame machine reflex
Hop 1 Hop 2
Hop 3

11. • Integrate WiFi and WiMax multi-hop
technologies with existing WANs
• Develop real time video and vehicular
sensor applications
• Video over WiMax OPNET Model
• Develop advanced security protocols
Eyeballs for Telematics over WiMax
Multihop

12. Example of Your Future Smart Car
- It will drive by itself, to allow you sleep over for destination …

13. SWAT Experiments on Today’s Road
Tx Rx Laptop
Handheld
e.g.BlackBerry
CDMA
Network
End-To-
End
Encrypt-ed
GSM
Network
FHSS
Radio

14. Battles around the Buildings with RCMP
Cellular
Network
Cellular
Network
CBRN Sensors --- GenieView – RIM partner

15. Problems Encountered
• We see interferences from embassies and DoD
or DnD buildings/ Towers
• Packet insertion and deleting from Bell, Roger
and Telus, China Unicom, AT&T …
• Rush hour congestions from Arizona Dessert or
Downtown Ottawa

16. Baked/Frozen in the Cruiser Physically!
• Radio smoked under the Africa hot tower
• Battery died North Pole frozen icy rain
• 400MHZ is good for outdoor
• 2.4GHz is good for indoor
• 900MHz is good for both
• FHSS is better than DSSS
• GSM is tougher than CDMA
Note: The conclusion may only valid for UK police trial.

17. Random Drops and Insertions
• Network overlayed has random byte
drops and insertions
• Rush hour congestion make it even
worse
• It happens at bit level, byte level, frame
level, packet level and even session
level …
• Mass up the video streaming
Note: The conclusion may only valid for police trials.

18. Solution Suggested – Three Guns Together
• Strong FEC – but with bandwidth overhead
• Blind Compensation – add latency overhead
• Traffic Shaping – buy back time and band.

19. LDGM Code
• For short headers (MPEG4 headers, sensors)
• Easy codec (faster, less battery drain)
• Low error floor (nuclear sensors, robots)

20. Blind Compensation
• At source side, extract the structure of the information,
e.g. JPEG has the Block Marks, count the distance
between each marks, encapsulate it in packet
• At receiving end, LDGM decode the structure
information first. And use the structure information to
guide the impairment compensation, e.g. search for
mark, if it shows up earlier, that means some bytes got
lost, we add a random byte …
• The random byte is generated and the resulting “blind”
byte is checked against predefined rules, to make sure
the byte is a acceptable best guess for the MPEG
decoder

21. Traffic Shaping
• Watch for latency, by checking the time stamps,
targeting for 100ms human reflex time.
• Frame based shaping, drop P frames at source,
whenever necessary
• Adjust size of I frame when network down to
dial up or old satellite speed
• Will implement classic PI based rate control to
improve loop stability

22. Research Methodology
• Collect video trace from a real-time wireless
streaming system
• Pareto video conference model mapping with
MATLAB analysis
• Integrating the WiMax adhoc technology into
OPNET model
• Simulation testing and road validation

23. Pareto unfair Phenomenon
• Created by an Economist to describe the
distribution of wealth in society
• 80% of your sales comes from 20% of your
clients
• Self similar model (includes burst, long
range dependency)
• 80% of bandwidth is occupied by 20%
of folks
• 80% gasoline is burned off by 20% drivers!

24. Why Pareto Model?
• Best describes the inter arrival time and/or
packet size
• f(x) stays steady at the tail end as opposed
to dying as seen in an exponential model
• Heavy tailed distribution
• Self similar

25. Pdf of MPEG video packet inter arrival
time

26. MATLAB Analysis
Shaping alters local Hurst parameter

27. Video over WiMax OPNET Model
Objectives
• Real world scenario of cars on the road
• Cars acting as peers (P2P)
• integrate the adhoc WiMax model
Scenarios
• Emergencies ahead
• Road blocks
• Natural disasters

28. OPNET model
• To obtain a model that is close to the real
world scenario
• Model the inter arrival time of packets and
the size of packets using the Pareto model
• Incorporate the WiMax IEEE802.16e adhoc
technology
• Deploy different scenarios
– Light traffic
– Heavy traffic

29. Preliminary Models

30. References
•·Jun Huang, F. Lawal, L. Jin & Oliver Yang, “Content-based Blind Compensation
and Shaping for Streaming Video”, IEEE 22nd Canadian Conference on Electrical
and Computer Engineering, May 2009.
•V.C.M. Leung, “Telematics over WiFi & WiMax Multihop Networks,” [online
available: http://auto21.ca/research/intelligent-systems-and-sensors/telematics-
over-wifi-wimax-multihop-networks/ ], June 11, 2008.
•I. Barbieri, P. Lambruschini, M. Raggio, and R. Stagnaro, "Real-Time
Transmission and Storage of Video, Audio, and Health Data in Emergency and
Home Care Situations", University of Genova, EURASIP Journal on Advances in
Signal Processing, Volume 2007.
•W. Zhong and J. Garcia-Frias, “LDGM codes for channel coding and joint source
channel coding of correlated sources”, EURASIP Journal on Applied Signal
Processing, pp. 942-953, May 2005.
•Y. Mao, A. Banihashemi, and M. Landolsi, “Comparison between low-density
parity-check codes and turbo product codes for delay and complexity sensitive
applications”, in Proc. 20th Biennial Symp. Comm. Kingston, Canada, May 2000,
pp.151-153.

31. Conclusion
•The compensation for live video dedicated to the auto
community has its own specific requirements and needs a
special attention to design
•We believe that a highly customized e.g. content-based
algorithm combines LDGM code; Blind Compensation and
Traffic Shaper will improve performance for such application
• We are developing an OPNET model to model the complete
end-to-end system
•Contact
– steed@genieview.com
Reliable Secure WirelessReliable Secure Wireless
VideoVideo …… Anywhere | AnytimeAnywhere | Anytime