auto21 ucsd
TRANSCRIPT
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
Where is Ottawa – Small Town Story
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
Project: Auto21 Webpage
Wife s/w, me h/w, kids on road, dad retired, students testing!
Industry: 180 Companies!
Academic: 44 Universities
55 Projects
Our Sole Goal for Telematics over WiFi and WiMax Adhoc Networks
• Objectiveso Develop an Advanced Vehicular Communications
Platform (AVCP)� Scalable� Reliable� Secure
o Promote safe road and safe community
Highway Chain Accident – Dozen Cars Trashed!
Adhoc Prevent Highway Chain Accident
CrashSlow 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 2Hop 3
• 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
Example of Your Future Smart Car
- It will drive by itself, to allow you sleep over for destination …
SWAT Experiments on Today’s Road
Tx Rx Laptop
Handheld
e.g.BlackBerry
CDMA
Network
En
d-T
o-
En
d
En
cryp
t-ed
GS
M
Netw
ork
FH
SS
Rad
io
Battles around the Buildings with RCMP
Cellular
Network
Cellular
Network
CBRN Sensors --- GenieView – RIM partner
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
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.
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.
Solution Suggested – Three Guns Together
• Strong FEC – but with bandwidth overhead• Blind Compensation – add latency overhead• Traffic Shaping – buy back time and band.
LDGM Code
• For short headers (MPEG4 headers, sensors)• Easy codec (faster, less battery drain)• Low error floor (nuclear sensors, robots)
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
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
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
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!
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
Pdf of MPEG video packet inter arrival time
MATLAB Analysis
Shaping alters local Hurst parameter
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
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
Preliminary Models
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.
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
Reliable Secure Wireless Reliable Secure Wireless Video Video …… Anywhere | Anytime Anywhere | Anytime