Cross-Layer Link Adaptation for Wireless Video

Current link adaptation algorithms for IEEE 802.11 WLANs exhibit behavior which makes them unsuitable for transmission of multiple simultaneous real-time uplink video streams. First, these algorithms do not consider the properties of the video codec, and hence, are unaware of the impact of PHY rate selection on the perceptual quality of the received video. Second, they do not differentiate between channel errors and collisions, and hence severely malfunction when the collision probability is non-negligible. In this paper, we propose a link adaptation strategy that not only optimizes the perceptual quality of the received video, but also maintains network stability by preventing catastrophic failure due to collisions. We show that switching to a lower PHY rate improves the SNR/BER performance, but increases channel contention (and hence the collision probability). Then, we use this information plus knowledge of the video codec and network transport protocol to estimate the received perceptual video quality at the current and adjacent PHY rates. The PHY rate that yields the best perceptual quality is chosen for each Group of Pictures (GOP). We support the proposed algorithm through experiments with real wireless cameras on which we have implemented our algorithm.

[1]  Leo Monteban,et al.  WaveLAN®-II: A high-performance wireless LAN for the unlicensed band , 1997, Bell Labs Technical Journal.

[2]  Stephan Wenger,et al.  H.264/AVC over IP , 2003, IEEE Trans. Circuits Syst. Video Technol..

[3]  Seongkwan Kim,et al.  CARA: Collision-Aware Rate Adaptation for IEEE 802.11 WLANs , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[4]  David R. Bull,et al.  Distortion-Based Link Adaptation for Wireless Video Transmission , 2008, EURASIP J. Adv. Signal Process..

[5]  Seung-Woo Seo,et al.  Collision detection based on transmission time information in IEEE 802.11 wireless LAN , 2006, Fourth Annual IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOMW'06).

[6]  Jenq-Neng Hwang,et al.  Distributed Cross Layer Congestion Control for Real-Time Video over WLAN , 2008, 2008 IEEE International Conference on Communications.

[7]  Andrea J. Goldsmith,et al.  Cross-layer design of ad hoc networks for real-time video streaming , 2005, IEEE Wireless Communications.

[8]  Michael Loiacono,et al.  The Snowball Effect: Detailing Performance Anomalies of 802.11 Rate Adaptation , 2007, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[9]  A. Girotra,et al.  Performance Analysis of the IEEE 802 . 11 Distributed Coordination Function , 2005 .

[10]  Reginald L. Lagendijk,et al.  Optimized video streaming over 802.11 by cross-layer signaling , 2006, IEEE Communications Magazine.

[11]  Jenq-Neng Hwang,et al.  Airtime Fair Distributed Cross-Layer Congestion Control for Real-Time Video Over WLAN , 2009, IEEE Transactions on Circuits and Systems for Video Technology.

[12]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[13]  Miska M. Hannuksela,et al.  H.264/AVC in wireless environments , 2003, IEEE Trans. Circuits Syst. Video Technol..

[14]  Reginald L. Lagendijk,et al.  Automatic IEEE 802.11 rate control for streaming applications , 2005, Wirel. Commun. Mob. Comput..

[15]  Wolfgang Kellerer,et al.  Application-driven cross-layer optimization for video streaming over wireless networks , 2006, IEEE Communications Magazine.