Supporting Wireless Video Growth and Trends 4G Americas Whitepaper April 2013 IEEE CVT meeting, September 2013

Transcription

1 Supporting Wireless Video Growth and Trends 4G Americas Whitepaper April 2013 IEEE CVT meeting, September 2013 Kamakshi Sridhar, Ph.D Director, Wireless CTO Alcatel-Lucent Whitepaper jointly led with Gautam Talagery Director, Mobile Broadband, Ericsson

2 Contributors and Reviewers Whitepaper benefited from active participation and contributions from operators (TEF, Rogers, Lime), vendors (ALU, Ericsson), device manufacturer (QCOM) leading to very good discussions addressing different perspectives. Javier Lorca - Telefonica Tony Lutz Qualcomm Dave Robinson Alcatel-Lucent Harish Viswanathan Alcatel- Lucent Barry Pratt Rogers Cleverston Miller Lime Ram Venkatramani previously from Openwave Mobility Karri Kuoppamaki T-Mobile Gautam Talagery Ericsson Kamakshi Sridhar - ALU

3 4G Americas Whitepaper Supporting Wireless Video Growth and Trends 4G Americas Whitepaper April Supporting%20Mobile%20Video%20Growth%20and%20Trends%20April% pdf

4 Goals Fact: Mobile video is growing driven by smartphones and tablets, and new apps. What enables the successful, mass adoption of mobile video? White paper examines issues specific to video that affect its delivery over wireless networks. Drivers and trends Types of video Short/long form, HTTP-Adaptive Streaming and HTTP Progressive Download RF and core challenges and solutions: Spectral efficiency, Varying channel, Mobility Signaling and battery issues Backhaul limitations HAS, TCP interactions, and role of client optimizations Video QoE metrics Impact of Codecs Architectures: HET-NET, CDN and embms Role of Video playout buffers LTE QCI, and GBR We provide recommendations to app developers, and on bit rates for various codecs.

5 Market trends in Video Delivery/Market analysis Streaming traffic during live events is high (2009 statistics) Key trends from Sandvine report, Ooyala, BBC statistics summarized to illustrate growth of mobile video. Video/Audio streaming is growing You-Tube and Real Time Entertainment traffic is growing

6 Types of video Video content can be classified as: Short form content, Long form content (based on duration) Operator video and OTT video (delivered by the service provider or not) Best Effort video and Guaranteed Bit Rate video (based on quality) Video for real time communication and for entertainment (based on usage) Major video delivery technologies: Non-HTTP Real time streaming protocols (RTP/RTSP delivered video). To stream live video content to proprietary clients. HTTP Progressive Download (HTTP-PD): Access before download HTTP Adaptive Streaming (HAS): Video divided into chunks. MPEG DASH (Dynamic Adaptive Streaming over HTTP) is a standard for adaptive streaming over HTTP that replaces existing proprietary technologies A unified standard is helpful to content publishers, who could produce one set of files that play on all DASH-compatible devices.

7 Key requirements of mobile video delivery Video flows are typically long duration flows. Video QoE must be sustained over long durations, over RF, core. For good video QoE, RF, backhaul and core challenges must be addressed e2e. Video must adapt to changes in link bandwidth. Video quality during handoffs must be managed Video quality as the cell becomes increasingly congested must be maintained. Must maintain the video quality (data rate, jitter specifications), fairness Video places demanding requirements on bit rate, jitter, and latency Must differentiate video quality according to subscription level Need to provide scalable solutions with large number of video flows. and competing traffic flows Need to consider impact of video and audio codec performance Must identify proper metrics to assess video QoE. Need to address impact of user device screen size, client on video QoE.

8 Impact of mobility, backhaul and wireless core on video delivery Data and throughput consumed by streaming applications is High, particularly for Tablets Paper examines: RF impact on mobile video. Spectral efficiency of 3G/4G cellular technologies Mobility, Handovers, retransmissions, varying channel quality Paper addresses Air interface latency: Challenge for interactive wireless - highquality videoconferencing or online gaming Progressive download video not so sensitive Signaling challenges for Video - limited Adaptive streaming - best for battery consumption and network load Backhaul congestion impact, and role of traffic shaping on video QoE. Encryption, Content rights management Application Throughput (Mbps) Stereo Music Small Screen Video (e.g. Feature Phone) Medium Screen Video (e.g. Smartphone) Medium Screen Video (e.g. Tablet) Larger Screen Video (e.g. High Quality on Tablet) MByte/Hour Hrs./day GB/month

9 Video codecs and HTTP Adaptive Streaming (HAS) Popular video codecs include H.264, VP6, VP8, etc. Codec (compression/decompression) algorithms play a key role. New/Upcoming codecs (HEVC): HEVC is a successor to the current state of the art video coder - H.264/AVC video coding standard. With large consumption rates, HEVC would result in significant reduction in infrastructure costs due to lower bandwidth required. HAS works by breaking the video into chunks, and each chunk is encoded and sent out at an appropriate bit rate based on the channel quality as estimated by the client. Without buffering at the client end (like in PD), HAS is able to provide adequate QoE at the user end, without freezing video frame All HAS solutions have the same underlying architecture - server side contains segmented video sequences and manifest file that describes content properties and lists segment URLs. Segments are offered at different bit rate levels which allow switching between bitrates when needed.

10 HTTP Adaptive Streaming (HAS) The paper also describes the BEHAVIOR OF VIDEO HAS CHUNKS WITH TCP/IP particularly with poorly designed HAS clients. Issues such as Unfairness and Instability: Under Utilised TCP throughput due to the interactions between HAS rate determining algorithm and TCP congestion control resulting in downward spiral are described. We note that the important role of well designed clients and how they can overcome these issues with HAS/TCP. Through subjective testing, it has been shown that HAS delivers an acceptable video quality over a range of typical network conditions. A well-designed HAS client should be able to work well and share fairly with other HTTP flows without knowing about the other devices that share the network. The network fairly provides as much data downloading capacity as it can to each end device. The HAS client on the device then decides which bit rates to download at each point in time to provide the best quality experience to the end user (i.e., no stalls or skips and a playback quality that pretty much matches the current download rate of the HAS client).

11 Video Quality of Experience: metrics and monitoring Typical video QoE problems: Blurring, blocking, stall, skips, encoding dependencies Must consider the impact of: Device size, viewing distance Playout issues, and varying image quality due to adaptive streaming The algorithm used in the buffering or playout of video from a source can influence: Network bandwidth use; battery usage; QoE with buffered or delayed video Metrics for characterizing video QoE MOS: average and standard deviation Three classes of monitoring Video QoE as: Full/Reduced/Non Reference Main factors that influence end user QoE of streamed video are identified, including device and media factors and network factors. 3GPP parameters for HAS content. Work by the NGMN P-SERQU maps video chunk quality to a predicted MOS Recommendation: Monitoring of Video QoE through monitoring the quality of HTTP chunks rather than individual radio and TCP parameters is preferred option.

12 Architectures for mobile video delivery Cellular (HET-NET) and WiFi offload architectures: Macro/pico/femtos, role of WiFi LTE broadcast architecture embms embms can support live streaming of sports, high attach rate content such as breaking news, and background file delivery. Content Delivery Networks HetNet Distributed caches containing copies of data, to avoid server bottlenecks LTE RAN Macro/ Pico/Femto 3G RAN Macro/ Metro/Femto WiFi APs Home Home Macros Macros 3G Femto 4G Femto S1-MME 4G Pico 3G Metro HSS S1-U S6a MME S11 SGW RNC/ SC GW Iu SGSN Gn Operator IP services Rx PCRF Gx S5/S8 PGW To PCRF GGSN ANDSF server embms SGi CDN

13 Optimization and Mitigation techniques The main method of video optimization at the base station is by controlling the data rate delivered to the device. LTE provides powerful QoS mechanisms. End-to-end QoS support in LTE for video delivery must consider: Role of LTE QCI and LTE guaranteed bit rate bearers Parameter settings for HAS: GBR, MBR, Differentiation and fairness with GBR service Limitations of GBR bearer Adapting Video usage behavior through yield management techniques. QCI Resource Type Priority Packet Delay Budget (NOTE 1) Packet Error Loss Rate (NOTE 2) Example Services ms 10-2 Conversational Voice ms 10-3 Conversational Video (Live Streaming) GBR ms 10-3 Real Time Gaming ms 10-6 Non-Conversational Video (Buffered Streaming) ms 10-6 IMS Signalling Video (Buffered Streaming) Voice, Video (Buffered Streaming) ms 10-6 TCP-based (e.g., www, e-mal, chat, ftp, p2p file sharing, progressive video, etc.) 7 Non-GBR ms 10-3 Video (Live Streaming) Interactive Gaming ms 10-6 TCP-based (e.g., www, , chat, ftp, p2p file 9 9 sharing, progressive video, etc.) LTE QCIs: 3GPP TS

14 Non-RF specific optimizations for video delivery Transcoding Adapting encoding of video stream to available bandwidth at the device. Transrating - Changing resolution, fidelity, frame rate without full decode / encode Rate capping An intermediate node adjusts the sending rate of a progressively downloaded video Scalable Video Codecs (SVC): The content encoded using a base layer and one or more enhancement layers Content caching in the network useful but does not solve RAN congestion. Time shifting or side loading (over WiFi) supported by content caching in the UE downloading, caching video content to the device during off-peak times or when the device is connected to WiFi. Congestion Triggered Optimization (for HTTP-PD) - Video Optimization engine dynamically starts optimizing (transrating/transcoding) video traffic during periods of congestion. Microbursting - High video data rate, within a short time to fill up the client buffers

15 Video delivery with CDNs Content capture and ingestion. Video is compressed and transmitted to content ingestion sites Coding the video into multiple versions for different codec technologies, container formats, resolutions, and content variances (e.g. trailers or short clips, embedded captions) etc. Application of Digital Rights Management technology adopted. Access policies, restrictions control access to the published contents and advertisement placements. Content distribution to local video headends follows the content ingestion: Video created sent over high speed networks to different video headends. Video delivery begins in video head end with supporting caching CDN nodes. Transcoding content into format appropriate for a particular device. The CDN server processes the request from end device, extracts device information from a subscription data base and delivers the video, transcoding if necessary. The delivery server maintains the session with the end device streaming the video as the end device consumes the content. The video server may additional invoke the APIs provided by the mobile core to establish QoS for the session.

16 Recommendations on bit rates for various codecs and screen sizes/device types The choice of bit rate for the audio and video streams is a compromise between quality and bandwidth used for streaming. The device screen size and viewing distance are a critical aspect in determining the bandwidth needed for encoding the video. Scenes with high motion or scenes with a lot of detail require more bandwidth. Chaotic motion is the hardest to encode and requires higher bandwidth Compression efficiency of the video codec impacts the bandwidth needed to encode a video quality with a given fidelity. The Content Provider may encode their content in multiple forms Video Level Quality Video (kbps) Total (kbps) Comments VQ Smartphone VQ Tablet / Smartphone VQ Tablet / Smartphone VQ SD 480P TV screen through games console and STBs, Connected TVs, PCs and Tablets VQ HD 72P TV screen through games console and STBs, Connected TVs, PCs and tablets VQ Full HD 1080P, TV screen through games console and STB, Connected TVs, PCs with General Processor Units.

17 Recommendations for video application developers Both the video delivery algorithm and the network configuration must be optimized. Video application developers need to consider the challenges in operating over a network with mobile devices. Applications must be adaptable to changing access capabilities, and access types. Utilize APIs between the Application Layer and Access Drive the creation of APIs to demand QoS from the network Mobile operators could provide the development space and environment for realistic simulations Chunk size: Ensure that video servers deliver chunks of video in small regular intervals ~10 seconds. The most optimal value of chunk size depends on, amongst other things, the enodeb timer value settings. Video sources with significant inactivity periods between chunks of data can waste signaling resources and device battery. Ensure that polling requests from the devices to the network are bundled to maximize use of seized resources.

18 Summary & Conclusions For Operators Architecture choices and improvements in both access and content. Work smartly with available and forecasted mobile broadband. For Vendors Areas for cooperation, integration in content generation and delivery Improvement and optimization in devices and networks. For Application developers and architects Optimize design of video applications to minimize effect on mobile networks For Industry analysts The state of video on mobile broadband is described, trends identified. For Device manufacturers Evolution in video processing technology and codecs.

19 Thank you