![]() |
|||
|
|||
![]() In This Issue October 2010 Vol. 8, Issue 3 Texas Wireless Summit to be held Nov. 16 on UT Campus WNCG Professors Receive $900,000 Intel and Cisco Video Grant Award WNCG Receives $2.84m in Prestigious NSF Grants Texas Instruments Funds 60 GHz RFIC Design and Antenna Research 4G Cellular Textbook Now Available Air Force Grant Awarded to WNCG Professors Bovik and Caramanis Professor Evans Releases Underwater Acoustic Communications Dataset Professor de Veciana and Madrid Collaborators Receive ACM Best Paper Award Best Paper Award for Dr. Bilal Sadiq and Professor Gustavo de Veciana Professor Andrews and Motorola to Collaborate on Femtocell Research Professor Robert W. Heath, Jr. Named Technical Program Chair for Asilomar 2011 Gutierrez Receives Texas Instruments Diversity Fellowship Visit WNCG |
WNCG Professors Receive $900,000 Intel and Cisco Video Grant Award ![]() Professors Gustavo de Veciana, Robert W. Heath, Jeffrey G. Andrews, Constantine Caramanis Professors Robert W. Heath Jr., Jeffrey G. Andrews, Alan Bovik, Constantine Caramanis, and Gustavo de Veciana were selected to receive a $900,000 gift over three years from Intel and Cisco to develop novel algorithms for Perceptual Optimization of Wireless Video Networks. From laptops, to the now-pervasive smart-phones and other portable devices capable of displaying, streaming, generating and also sharing video, wireless networks are fast becoming the dominant means for video content delivery. Unfortunately, the application-agnostic approach of current data networks is not well-suited to meet projected growth in video traffic volume, nor is it capable of leveraging unique characteristics of real-time and stored video to deliver video more efficiently. UT's innovative approach to improving wireless video capacity is built on a foundation of providing high perceptual quality. The research agenda is aligned along three critical research directions. The first is developing video quality metrics for 2-D and 3-D video with the end goal of providing high (human) visual quality. Another direction is in spatio-temporal interference management with the objective of predicting and scheduling video more efficiently over long time periods with less interference. The third direction involves using performance data generated to help the network adapt and deliver video more efficiently. UT's team believes that fundamental advances in the areas of video quality, interference management, and learning will allow wireless networks to meet the anticipated increases in demand for high quality video delivered over wireless networks. |
||
![]() |