ECE 256

Diagnosing Wireless Packet Losses in 802.11: Separating Collision from Weak Signal

Presented By:

Jacob H. Cox Jr

For ECE 256: Wireless Networking and Mobile

Computing

February 10, 2009

ECE 256

Acknowledgments• Authors ~ Shravan Rayanchu, Arunesh

Mishra, Dheeraj Agrawal, Sharad Saha, Suman Banerjee

• Kuo-Chung Wang (Slide Presentation) – http://lion.cs.uiuc.edu/group_seminar_past/fall06/

group_seminar_slides/kim-rateadaptation06.ppt+RRAA

ECE 256

Presentation Outline• Packet Loss Problem• Current Rate Adaption Schemes• COLLIE Overview• COLLIE Metrics • COLLIE Analysis• Conclusion

ECE 256

Motivation

• Packet Loss2 Causes: Weak Signal and Collision

• 802.11 Solution Inadequatedefaults to BEB for a substantial number of packet

losses • Question:

– Does the type of packet loss matter?– What if we could determine its cause?

ECE 256

Problem Defined• Collision or Weak Signal, why does knowing

matter? Beamforming?

ECE 256

Fixing packet loss

• Appropriate actions–For collision

• BEB

CW

Max

RetriesREF: http://pages.cs.wisc.edu/~shravan/coll-infocom.pdf

ECE 256

Rate Adaptation

802.11 a/b/g standards allow for the use of multiple transmission rates

• 802.11a, 8 rate options (6,9,12,18,24,36,48,54 Mbps)• 802.11b, 4 rate options (1,2,5.5,11Mbps)• 802.11g, 12 rate options (11a set + 11b set)

Some papers report that rate adaptation is important yet unspecified in 802.11 standards

Reference: Robust Rate Adaptation in 802.11 Networks Presentation by Kuo-Chung Wang

ECE 256

Rate Adaptation Example• Rate adaptation affects throughput performance and

should be adjusted by channel condition

Sender Receiver

54MbpsSignal is goodSignal becomes weaker

12Mbps

Reference: Robust Rate Adaptation in 802.11 Networks Presentation by Kuo-Chung Wang

Rate Too High Rate Too LowIncreases Loss Ratio Capacity Under-Utilized

Decreased Throughput Decreased Throughput

ECE 256

Related WorkRate Adaptation Algorithms

–Differentiate between loss behaviors –Adapt to realistic scenarios–Handle hidden stations

ARF ~ Auto-rate FallbackCARA ~ Collision-Aware Rate AdaptationMRD ~ Multi-Radio DiversityRBAR ~ Receiver Based Auto RateRRAA ~ Robust Rate Adaptation Algorithm

ECE 256

RAA Problem

ReceiverSender

54MbpsSignal is good

12 Mbps

Sender54MbpsSignal is good

Sender

54MbpsSignal is good

Sender12MbpsSignal is still good

Sender12Mbps

Signal is still good

With hidden terminals, reducing the rate prolongs transmission time for each packet and results in more collisions

ECE 256

Introduction to COLLIE

• 802.11, CARA, and RRAA use multiple attempts to deduce cause of packet loss

• COLLIE uses a direct approach – Error packet kickback– Client analysis

ECE 256

COLLIE

• Collision Inferencing Engine– Utilizes receiver feedback– Analyzes:

• Bit and symbol level error patterns• Received signal strength

– Design:• Signal analysis algorithms• Link layer protocol which adjusts link layer

parameters

ECE 256

Link Adaptation Mechanism Enhancements

• Auto Rate Fallback (ARF)– Used in conjunction w/COLLIE for this paper– Rate adaption mechanism enhanced with

inferencing component– Using COLLIE, observed throughput gains of

20-60%

ECE 256

?Data

Feedback

Collision Inference Algorithm

Received Signal Strength

Bit error distribution and patterns

Symbol error patterns

X

Note: assumes Feedback is successfully received and sender’s MAC address is decoded correctly by the AP

Adjust Data Rate/Power

Or Contention Window

Client AP

COLLIE Continued

ECE 256

Metrics for Analysis• Received Signal Strength (RSS) = S + I

– S ~ Signal Strength– I ~ Interference

• Bit Error Rate (BER) = total % incorrect bits• Symbol level errors: errors within transmission

frame– Multiple tools used to analyze symbol-level errors

http://pages.cs.wisc.edu/~shravan/coll-infocom.pdf

ECE 256

Symbol-level Errors• Symbol Error Rate (SER)- % symbols received

in error• Errors Per Symbol (EPS)- average # errors

within each symbol• Symbol Error Score (S-score): , where

Bi is a burst of n bits

2

1

n

ii

B

ECE 256

S-Score

• 0011 0011 0011 0011 1101 0011

Collision

Channel Fluctuation

0011 0011 0011 0111 1011 0010

S-Score =

2 2 2 2

1

1 1 1 3n

ii

B

S-Score = 2 2 2 2

1

0 3 0 9n

ii

B

http://pages.cs.wisc.edu/~shravan/coll-infocom.pdf

ECE 256

Experimental Design

• Three possibilities at R:1. Packet received without error2. Packet received in error3. No packet received

ECE 256

Experimental Design

• Two transmitters, T1 and T2• Two receivers, R1 and R2• Receiver R hears all signals

ECE 256

Analysis of Results

Metric Collision Weak SignalRSS Higher (90% > -73dBm) Lower (98% < -73dBm)

BER Higher (24% =< 12% BER) Lower (98% =< 12% BER)

SER Unremarkable Unremarkable

EPS Higher (45% =< 28% EPS) Lower (98% =< 28% EPS)

S_Score Higher (28% =< 500) Lower (98% =< 500)

ECE 256

Analysis of Results

ECE 256

Begs the Question• Is it worth it? Successful almost 60%, false positive rate of 2.4%

Check out this accuracy?

ECE 256

Client Module

Design Components

ECE 256

Multi-AP COLLIE• Error packet sent to a central COLLIE server• Most important where the capture effect is dominant

ECE 256

Multi-AP Results

• Static situation averaged 30% gains in throughput

• For multiple collision sources and high mobility, throughput gains reached 15-60%

ECE 256

Collision Analysis

ECE 256

Some Problems

• Capture Effect• Packet size• Packet Kickback

ECE 256

Conclusions

• COLLIE implementation achieves increased throughput (20-60%) while optimizing channel use

• 40% reduction in retransmission costs• Implementation can be done over

standard 802.11, resulting in much lower startup costs than other protocols

ECE 256

Questions?