SYSTEMS AND METHODS FOR IMPLEMENTING MODEL-BASED QOE SCHEDULING

• US 20150341594A1
• Filed: 11/15/2013
• Published: 11/26/2015
• Est. Priority Date: 11/16/2012
• Status: Abandoned Application

• Current Assignee: VID SCALE Inc. (InterDigital, Inc.)
• Original Assignee: VID SCALE Inc. (InterDigital, Inc.)
• Inventors: Ma, Liangping, Sternberg, Gregory, Zeira, Ariela, Balasubramanian, Anantharaman, Rapaport, Avi, Xu, Tianyi
• Application Number:
  US14/442,073
• Publication Number:
  US 20150341594A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: H04L 65/403 Arrangements for multi-party communication, e.g. for conferences data switching systems for conference H04L12/18; arrangements for connecting several subscribers to a common circuit, i.e. affording conference facilities H04M3/56; television conferencing systems H04N7/15
• CPC Class Codes: H04L 65/70 Media network packetisation
• CPC Class Codes: H04L 65/752 adapting media to network capabilities
• CPC Class Codes: H04L 65/765 intermediate
• CPC Class Codes: H04L 65/80 Responding to QoS
• CPC Class Codes: H04L 69/22 Parsing or analysis of headers
• CPC Class Codes: H04N 19/132 Sampling, masking or truncation of coding units, e.g. adaptive resampling, frame skipping, frame interpolation or high-frequency transform coefficient masking
• CPC Class Codes: H04N 19/154 Measured or subjectively estimated visual quality after decoding, e.g. measurement of distortion use of rate-distortion criteria H04N19/147
• CPC Class Codes: H04N 19/164 Feedback from the receiver or from the transmission channel
• CPC Class Codes: H04N 19/172 the region being a picture, frame or field
• CPC Class Codes: H04N 19/46 Embedding additional information in the video signal during the compression process H04N19/517, H04N19/68, H04N19/70 take precedence
• CPC Class Codes: H04N 21/234381 by altering the temporal resolution, e.g. decreasing the frame rate by frame skipping
• CPC Class Codes: H04N 21/64738 Monitoring network characteristics, e.g. bandwidth, congestion level data switched network analysis H04L41/14; monitoring functioning in data switched networks H04L43/0817; flow control in packet networks H04L47/10
• CPC Class Codes: H04N 21/64792 Controlling the complexity of the content stream, e.g. by dropping packets intermediate media network packet handling H04L65/765; proxy provisioning conversion or adaptation for reducing the amount or size of exchanged application data H04L67/5651; negotiation of resources in wireless networks H04W28/16
• CPC Class Codes: H04N 7/147 Communication arrangements, e.g. identifying the communication as a video-communication, intermediate storage of the signals selecting H04Q
• CPC Class Codes: H04N 7/152 Multipoint control units therefor
• CPC Class Codes: H04W 28/0268 using specific QoS parameters for wireless networks, e.g. QoS class identifier [QCI] or guaranteed bit rate [GBR] negotiating SLA or negotiating QoS H04W28/24

Abstract

Disclosed herein are systems and methods for implementing model-based quality-of-experience (QoE) scheduling. An embodiment takes the form of a method carried out by at least one network entity. The method includes receiving video frames from a video sender, which had first annotated each of the frames with a set of video-frame annotations including a channel-distortion model and a source distortion. The method also includes identifying all subsets of the received video frames that satisfy a resource constraint. The method also includes selecting, from among the identified subsets, based at least in part on the video-frame annotations, a subset that maximizes a QoE metric. The method also includes forwarding only the selected subset of the received video packets to a video receiver for presentation.

Claims

1. A method carried out by at least one network entity, the at least one network entity comprising a communication interface, a processor, and data storage containing instructions executable by the processor for carrying out the method, the method comprising:

receiving, via the communication interface and a communication network, video frame data from a video sender, the video frame data including a set of video-frame annotations, the set of video-frame annotations including at least one channel-distortion model parameter and a source distortion;

identifying subsets of the received video frames that satisfy a resource constraint;

selecting, from among the identified subsets, based at least in part on the video-frame annotations, a subset that maximizes a quality-of-experience (QoE) metric; and

forwarding, via the communication interface and the communication network, only the selected subset of the received video packets to a video receiver for presentation.

2. The method of claim 1, wherein selecting the subset of the received video frames that maximizes the QoE metric comprises:

calculating, based at least in part on the video-frame annotations, a per-frame peak signal-to-noise ratio (PSNR) time series corresponding to each identified subset of received video frames; and

identifying the subset corresponding to the highest per-frame PSNR time series as the selected subset.

3. The method of claim 1, wherein the resource constraint relates to network congestion.

4. The method of claim 1, wherein the at least one network entity comprises one or more network entities selected from the group consisting of a router, a base station, and a Wi-Fi device.

5. The method of claim 1, wherein the video sender comprises one or more video senders selected from the group consisting of a user equipment and a multipoint control unit (MCU).

6. The method of claim 1, the video sender having also captured the video frames.

7. The method of claim 1, wherein the communication network comprises one or more networks selected from the group consisting of a cellular network, a Wi-Fi network, and the Internet.

8. The method of claim 1, wherein the video sender annotates the frames in one or more headers selected from the group consisting of an Internet Protocol (IP) packet header extension and a Real-time Transport Protocol (RTP) packet header extension field.

9. The method of claim 1, wherein the channel-distortion model comprises one or more of a channel-distortion prediction formula, a set of one or more characteristic features of a video-encoding process used in connection with the frame, a channel distortion, an error-propagation exponent, and a leakage value.

10. The method of claim 1, wherein the video-frame annotations indicate whether, with respect to the channel-distortion model, the intra macroblock refresh is cyclic or pseudo-random.

11. A system comprising at least one network entity, the at least one network entity comprising:

a communication interface;

a processor; and

data storage containing instructions executable by the processor for carrying out a set of functions, the set of functions including;

receiving, via the communication interface and a communication network, video frames from a video sender, the video sender having first annotated each of the frames with a set of video-frame annotations, the set of video-frame annotations including a channel-distortion model and a source distortion;

identifying one or more subsets of the received video frames that satisfy a resource constraint;

selecting, from among the identified subsets, based at least in part on the video-frame annotations, a subset that maximizes a quality-of-experience (QoE) metric; and

forwarding, via the communication interface and the communication network, only the selected subset of the received video packets to a video receiver for presentation.

12. The system of claim 11, wherein selecting the subset of the received video frames that maximizes the QoE metric comprises:

calculating, based at least in part on the video-frame annotations, a per-frame peak signal-to-noise ratio (PSNR) time series corresponding to each identified subset of received video frames; and

identifying the subset corresponding to the highest per-frame PSNR time series as the selected subset.

13. The system of claim 11, wherein the resource constraint relates to network congestion.

14. The system of claim 11, wherein the at least one network entity comprises one or more network entities selected from the group consisting of a router, a base station, and a Wi-Fi device.

15. The system of claim 11, wherein the video sender comprises one or more video senders selected from the group consisting of a user equipment and a multipoint control unit (MCU).

16. The system of claim 11, the video sender having also captured the video frames.

17. The system of claim 11, wherein the communication network comprises one or more networks selected from the group consisting of a cellular network, a Wi-Fi network, and the Internet.

18. The system of claim 11, wherein the video sender annotates the frames in one or more headers selected from the group consisting of an Internet Protocol (IP) packet header extension and a Real-time Transport Protocol (RTP) packet header extension field.

19. The system of claim 11, wherein the channel-distortion model comprises one or more of a channel-distortion prediction formula, a set of one or more characteristic features of a video-encoding process used in connection with the frame, a channel distortion, an error-propagation exponent, and a leakage value.

20. The system of claim 11, wherein the video-frame annotations indicate whether, with respect to the channel-distortion model, the intra macroblock refresh is cyclic or pseudo-random.