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Utility Function Selection for Streaming Videos with a Cognitive Engine Testbed

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Abstract

Cognitive Radio (CR) is a new wireless communication and networking paradigm that is enabled by the Software Defined Radio (SDR) technology and the recent change in spectrum regulation policy. As the first commercial application of CR technology, IEEE 802.22 wireless regional area networks (WRAN) aim to offer broadband wireless access by efficiently utilizing the unoccupied TV channels. In this paper, we investigate the problem of utility function selection and its impact on streaming video quality through an IEEE 802.22 WRAN base station (BS) cognitive engine (CE) testbed developed at Wireless@Virginia Tech. We find that significant improvement on received video quality can be achieved when CE adopts a dynamic, content-aware, video-specific utility function rather than a static, predefined, general purpose utility function. This work indicates the importance of video distortion modeling and cross-layer design, and the need for employing dynamic content-aware utility functions at the CE for cognitive streaming video communication networks.

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Acknowledgements

Youping Zhao’s work had been supported in part by Electronics and Telecommunications Research Institute (ETRI), Texas Instruments (TI), and Wireless@Virginia Tech Partners. He would like to thank Joseph Gaeddert, Lizdabel Morales, and Kyung K. Bae for their discussions and collaboration on the development of the WRAN BS CE Testbed at Wireless@Viginia Tech. The work of Jeffrey H. Reed was supported in part by the Wireless@Virginia Tech Partners Program. This work is also is supported in part by the US National Science Foundation under Grant ECCS-0802113 and through the Wireless Internet Center for Advanced Technology (WICAT) at Auburn University. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the authors and do not reflect the position of their sponsors or affiliations.

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Zhao, Y., Mao, S., Reed, J.H. et al. Utility Function Selection for Streaming Videos with a Cognitive Engine Testbed. Mobile Netw Appl 15, 446–460 (2010). https://doi.org/10.1007/s11036-009-0200-7

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