video capacity of wlans with a multiuser perceptual quality constraint
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1
Video Capacity of WLANs with a Multiuser Perceptual Quality Constraint
Authors:Jing Hu, Sayantan Choudhury, Jerry D. Gibson
Presented by:Vishwas Sathyaprakash, Aditya Sharma
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Overview
• Introduction & Motivation• Experiment – Simulation Setup• Results of Simulation– Packet Loss and Video Quality– Video Data Rate
• Suggested Improvements• Determining Video Capacity• Applications• Conclusion
3
Introduction
• Wireless LANs gaining popularity• Multimedia - Large part of WLAN traffic• How many users can be supported ?• Video Quality - as perceived by users• Fine Balance - Capacity v/s Quality• Authors Define this fine balance in terms of
perceived quality of the video being delivered to r% of the users– Example: Streaming a video in this class
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Motivation
• Video Compression Variable Size & Quality• Measuring video quality: – Mean Squared Error & Peak Signal-to-Noise Ratio– Poor co-relation to perceived video quality– HVS : Computationally Expensive
• Capacity, Encoding and transfer rates– Capacity calculation not defined clearly– Transfer rate/Capacity depends on codec used
• First effort to relate Quality and Capacity: Not been studied yet
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Overview Introduction & MotivationExperiment – Simulation Setup• Results of Simulation– Packet Loss and Video Quality– Video Data Rate
• Suggested Improvements• Determining Video Capacity• Applications• Conclusion
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Video Over WLAN: Simulation Setup
• Video Codec: H.264– Packetized Video; Many coding schemes/options
• GOPs of 10, 15, 30, 45• 3 Videos: 90 Frames each– Silent.cif; Paris.cif; Stefan.cif
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Video Over WLAN: Simulation Setup
• WLAN: IEEE 802.11a (5GHz; 54 Mbps)• Quantization Parameters (QP): 26 (fine) & 30
(coarse)• Payload Size (PS) of 100 and 1100 bytes• Noise: Additive White Gaussian Noise (AWGN)• Packet Loss Compensation: Base Model– I-Frame: Recovery of MB by Spatial Interpolation– P-Frame: Copying MB from reference frames– Lost Frame: Entire frame is copied
• Measurements: SNR, PER and Data Rates (DR)
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Overview Introduction & MotivationExperiment – Simulation SetupResults of Simulation
Packet Loss and Video Quality Video Data Rate
• Suggested Improvements• Determining Video Capacity• Applications• Conclusion
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Results of Simulation: Packet Loss (1)N
umbe
r of R
ealiz
ation
s
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• CDFs of PER > 0 at 0 realizations• CDFs of PER < 1 for realizations <1 • Average PER over realizations of multipath fading not an
appropriate indicator of channe performance• Variation of PER of AWGN channel is less, ranges from
1% to 3%• Avg. PER of multipath channels = 5.5% This represents
only a small number of total realizations • Avg. PER of AWGN channel is much lower than Avg. PER
of channels with fading
Results of Simulation: Packet Loss (2)
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Results of Simulation: Packet Loss (3)
70%: No Packet Loss
90%: Packet Loss < 2%
Num
ber o
f Rea
lizati
ons
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Results of Simulation: Packet Loss (3)…contd.
• Video: Silent.cif• QP = 26, 30• GOP = 15• PS = 100• Fading Channels• Thick lines represent
Average PSNR• ‘+’ marks: 70% of the
overlapping realizations with no packet loss
Frame Index; QP = 26
PSN
R of
eac
h fra
me
PSN
R of
eac
h fra
me
Frame Index; QP = 30
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• Video: Silent.cif• QP = 26, 30• GOP = 15• PS = 100• Shows behavior of
noise channels (AWGN)• Prediction in video
encoding causes realizations with similar PER: yet, completely different video quality
Results of Simulation: Packet Loss (4)PS
NR
of e
ach
fram
ePS
NR
of e
ach
fram
e
Frame Index; QP = 26
Frame Index; QP = 30
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Results of Simulation: Data Rate (1)
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Results of Simulation: Data Rate (2)
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Overview Introduction & MotivationExperiment – Simulation SetupResults of Simulation
Packet Loss and Video QualityVideo Data Rate
Suggested Improvements• Determining Video Capacity• Applications• Conclusion
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PSNRr,f & Perceptual Quality of Multiple Users MOSr
• Defined as the PSNR achieved by f% of the frames in each one of the r% realizations
• f%: Captures the majority of the frames• r%: Captures the reliability of a channel over many users • Claim: Quality Perception doesn’t change for high ‘f’• Observations behind the claim:
– Poor quality frames dominate viewers’ experience– Quality drop in a very small number of frames is not perceivable
by the human viewer– PSNR > threshold Increase in PSNR doesn’t translate to
increase in perceptual quality
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PSNRf and Perceived Video Quality (1)
• Experiment to prove the claim:– Same video sequences played side-by-side– Left: Raw video / Perfect Quality– Right: Compressed Video with recovered packet
losses and concealment– 3 humans: Rate the videos from 0 – 100%– Scores plotted
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PSNRf and Perceived Video Quality (2)
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• Of all f values, f=90% correlates to best opinion score• Mean Opinion Score achieved by r% of the transmissions is
given by:
• Dotted Lines = Average PSNR (existing)• Problem with regular PSNR:
– Quantitative measure of Quality– Underestimates the quality at high quality levels– Overestimates the quality at low quality levels
• Thick lines = PSNRf (proposed)– Serves as effective quality measure: correctly estimates low quality
and high quality as perceived by HVS
PSNRf and Perceived Video Quality (3)
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Overview Introduction & MotivationExperiment – Simulation SetupResults of Simulation
Packet Loss and Video QualityVideo Data Rate
Suggested ImprovementsDetermining Video Capacity• Applications• Conclusion
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Video Capacity of WLAN with DCF (1)
• Thumb-rule: Video frames must arrive at the buffers before the playback deadline.
• DCF: Distributed Coordination Function: based on CSMA/CA
• Requirement to know the number of users supported:– Network operators get an idea of number of users that can
be supported for identical traffic (capacity planning)– Mix of users having different traffic demands capacity is
approximated to an interpolation of capacity values for each traffic category
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• Video capacity with no buffer at receiver– I-Frame and P-Frame sizes differ greatly– What happens when:• All users are transmitting I-Frame? - Worst Case
• All users coordinate I-Frame transmission ? - Best Case
Video Capacity of WLAN with DCF (2)
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• Video capacity with play-out buffer at receiver (Cb)– Play-out buffer b is the length of the buffer (ms)– It is used only for the frames that have more bits
than the other frames (I-Frame)– How buffer length compares with SI/SP : Plot– Cb fluctuates between CM and a lower bound given
by:
Video Capacity of WLAN with DCF (2)
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• Length of buffer required for video capacity to reach upper bound, for typical SI/SP values:
Video Capacity of WLAN with DCF (2)
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Overview Introduction & MotivationExperiment – Simulation SetupResults of Simulation
Packet Loss and Video QualityVideo Data Rate
Suggested ImprovementsDetermining Video CapacityApplications• Conclusion
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Quality Constrained Video Capacity and its Applications (1)
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Quality Constrained Video Capacity and its Applications (2)
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• Observations:– Users watching silent.cif Excellent Quality– Users watching paris.cif Average Quality– Users watching stefan.cif Poor Quality
• Applications:– Link Adaptation based on capacity– System performance evaluation– Accurate System Design
Quality Constrained Video Capacity and its Applications (3)
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Overview Introduction & MotivationExperiment – Simulation SetupResults of Simulation
Packet Loss and Video QualityVideo Data Rate
Suggested ImprovementsDetermining Video CapacityApplicationsConclusion
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Conclusion• Average PER / Average PSNR Not a suitable indicator of
video quality• They should not serve as the basis for video quality
assessment• Proposed ‘perceptual’ quality indicator matches the
quality with the human vision system’s quality perception• Video Capacity with/without buffering• Quality Indicator + Video Capacity design better WLAN
communication system with importance to both quality and efficient capacity utilization
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Conclusion (2)• Some observations:
– Video Quality Perception is a highly subjective test – Only 3 human ‘testers’ considered: Results could vary with more
humans testing the theory– Ideal test conditions assumed:
• Packets/Frames received without errors• Collisions are not considered• Single Hop networks considered. More Packet errors / losses in multi-hop
networks: Losses affect video quality directly– 802.11a has been used for testing; Widespread use of 802.11g/n today:
Multipath Fading parameters may change due to operating frequency in 802.11g/n (2.4GHz) + Interference
– Little description of actual applications of the proposed method– Portability of proposed method assumed: Same results expected in
other video coding methods (MPEG-2) but not proved
Q&A33Note: All images are the property of the respective owners. Images used for non-profit / educational purposes only.
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