establishing and maintaining broadcast quality video over ip yannick le dreau 4 september 2010

Establishing and Maintaining Broadcast Quality Video over IPYannick LE DREAU

4 September 2010

Establishing and Maintaining Broadcast Quality Video over IP2

Agenda

Attracting and retaining subscribers– What can we realistically do to maintain the best delivery quality to our

subscribers ?– What do we mean by Quality of Service and Quality of Experience ?

The IP Video Ecosystem– Garbage in, Garbage out– What can we measure and how ?

A system wide view - where do we look and what do we look at ?

Putting it the Big Picture together– Finding and resolving customer impacting issues quickly– Using distributed monitoring and diagnostics– Element/Network Management systems– Proactive, not reactive; keep your subscriber away from his phone

Conclusion


Attracting and retaining subscribers

What are subscribers REALLY interested in ?– Getting the right program– Good picture quality– Synchronised audio and video

All these factors impact Quality of Experience (QoE)


Quality of Service & Quality of Experience

Quality of Service (QoS)– In network traffic engineering, QoS can be used provide various priorities

to differing data flows, or guarantee a certain level of performance to a data flow.

– In IP Video systems, this prioritization is critical to achieve good quality service delivery.

– Can be objectively measured by the provider himself

Quality of Experience (QoE)– Closely related, but subtly different– Focused on the overall performance of the delivery system from the end-

users perspective.

QoE is a subjective measurement of the perceived value of the overall service, and customer experience.


Quality of Service & Quality of Experience

QoS and QoE are inextricably linked !

Increasing video compression reduces bandwidth and can therefore improve QoS

The end user perceives lower quality video, therefore QoE is reduced

IP Video Ecosystem


IPTV Ecosystem


The primary functions of the IP Video headend

Digital program acquisition:– Content from the satellite or terrestrial sources, and the preparation of

that content for digital delivery (National or regional).

Digital program storage:– Storage and insertion of additional, non-live broadcast programming like

local content, video-on-demand or advertising.

Digital program distribution and delivery:– Program preparation and aggregation, rate-shaping, modulation,

encapsulation (encoding), encryption and other technical processes for program delivery.


IP Video Headend


Headend Ingest - RF

Various RF parameters can be proactively used to measure RF signal quality;

– Modulation Error Ratio (MER)– Error Vector Magnitude (EVM)– Bit Error Rate (BER)

MER particularly is defined as a ‘single figure of merit’ of the RF signal

Measurement trending can be used to identify signal degradation


Headend Ingest – IP traffic

QoS refers to the ability of a service provider to support users’ requirements with regard to at least 4 service categories;

– Bandwidth– Latency or delay– Jitter– Traffic Loss

Measurement Category

Key Performance Indicators

Bandwidth Total Line Bitrate

IP Session Bitrate

TS Bitrate

Program Bitrate

PID Bitrate

Latency/Delay Max/Min Packet Inter-arrival Time (PIT)

Jitter Max/Min Packet Inter-arrival Time (PIT)

PCR_OJ, PCR Inaccuracy

PCR-PTS values

Traffic/Packet Loss RTP Lost Rate/Count

RTP Out of Order Rate/Count

Frame Checksum errors

TS Continuity Count errors


Headend Ingest - SDI

Multi source, multi format feeds need to be checked as they are brought into the plant.

Origination may be 3G-SDI

Rapid problem location by tracking video presence and format, luma and gamut errors, and CRC statistics.

Comprehensive audio information including clips, mutes, over and silence conditions can be summarized by individual audio channel.


Headend Ingest – File Based

Multi source, multi format feeds need to be checked as they are brought into the plant.

Using automated file-based QC solutions can reduce your end-to-end file time, reduce the number of people in the workflow, and reduce churn by having your content accepted the first time.

Automated QC can scale with content growth, increase service quality, and get better leverage out of existing staff.


What and where can wemeasure ?


What can we measure – QoE Metrics

It is important to look at subjective customer impacting issues such as video and audio impairments.

These are the QoE issues most likely to cause customer dissatisfaction, increase churn and therefore directly impact ARPU.

Video impairments include;– Stuck/Frozen Video detection– Black Video detection– Blockiness and slice error detection– Tiling/pixelization detection– Display of video metadata; codec type, resolution, display area, aspect

ratio, bit rate, Frames per second, scan and AFD



Using these video measurements, it is possible to isolate encoding issues from transport issues

Examples;– Tiling effects are typically caused by insufficient bit-rate for required image detail

rather than any TS stream defect (PCR errors, dropped packets, etc).– Blockiness artifacts are typically due to data loss - dropped packets, PCR jitter, or

TS format problems. Normally very noticeable.



Audio impairment measurements should include;– True Peak & Loudness (ITU-1770/1771)– Clipping– Silence detection– Detection of phase problems– Display of audio metadata including codec type, number of channels, bit rate and

sample rate.


Quality of Experience Monitoring:Video & Audio QoE scoring

Score hundreds of video and audio streams, based on customers’ experiences (QoE), in real time continuously & simultaneously

Screen capture of a video clip with low VQoE score


IP Video Quality Measurements (Who Cares)

QoE Customer

QoS Network

Content MeasuresPicture Quality, Blocking, Blurring,

Visual Noise, Audio Drop-outs

Media Transport MeasuresPCR Jitter, Pixelization,

Sync Loss, Continuity Errors

IP Network MeasuresPacket Loss, Jitter, Delay

Control MeasuresIGMP Latency, RTSP Latency, Channel

Zap Time

Physical

Visual

Ethernet

IP

UDP

RTP

MPEG-TS

Content

Contr

ol


Engineering Troubleshooting QOE/QOS Correlation

Time-based root cause analysis

Triggered capture capability

60-day historical report

By program

By location

Bit rate

Audio/Video QoE

Audio loudness

Discontinuity event

IP statistics

Splicing event


Where can we measure ?


Taking a system wide view

It has been shown that automated conformance checking and monitoring is possible across all types of ingest.

Any point where content is changed is a possible failure point;– Re-multiplexing– Transrating & transcoding– IP encapsulation and transmission


QoE Monitoring & ReportingDashboard, Alert Analysis By Program/Location


Putting the Big Picture together


Using distributed monitoring probes can supply cross layer QoS/QoE metrics.

Operators need the ability to ‘tune’ the system to give focus to high priority assets.

How can you collate and sort all the information from these probes in order to quickly isolate problems ?

Putting the big picture together



An Element Management System (EMS) can give several layers of features;

Engineering– The ability to identify impacted services and enable engineers to drill

down for rapid root cause analysis of video service delivery issues is key.– Providing alarms, logs, trending and reporting of key performance metrics

Operations– Ability to view video from any probe within the network– Inclusion of integration for STBs or other Customer Premises Equipment

(CPE) in order to provide diagnostics from the subscriber network.

Management– Provide key video and audio impairment data– Are we meeting our SLAs ? Are our providers meeting theirs ?– Use service data to be proactive; act before your customer does



It can provide managers with the ability to track both network and service performance;

– Support for reporting through statistical logging and report generation– Trending analysis for tracking of management performance metrics and

service level agreements.


Conclusion

It is clear that carrying high quality digital video across IP networks is a challenging task.

Differentiated IP services such as High Speed Data, VoIP and video all have differing bandwidth and QoS requirements.

Video requires high availability (in bandwidth and time) which requires implementation of robust network management policies, along with suitable monitoring tools to ensure those policies are maintained 24/7

It has been shown that IP video cannot survive in a “Best Effort” environment - video packets need to arrive in sequence and with no losses.


Conclusion

Use of test equipment in this environment is essential and correctly placed monitoring probes across the network can provide important data in the form of KPIs for both QoS & QoE

Combined with the use of EMS/NMS, this can empower operators and engineers to efficiently manage network systems.

This can prevent degradation of signal quality which may result in errors which affect the end users experience and ultimately, Operator revenues.


Questions?

establishing and maintaining broadcast quality video over ip yannick le dreau 4 september 2010

Documents

broadcast quality video

lower quality video

video compression

ip video headendestablishing

ip video systems

ip video ecosystemgarbage

best delivery quality

good quality service