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User-Cognizant Scalable Video Transmission over Heterogeneous Cellular Networks

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Handbook of Cognitive Radio

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Abstract

With the increase of mobile video applications in people’s daily life as well as industrial manufacture, such as video streaming, surveillance, and so on, video has been the main service in cellular networks. Operators and service providers are struggling to enhance the mobile video service, while user requirements for abundant, high-definition, and low-delay video have nearly drained the transmission capacity of current networks. Moreover, the large population of user equipments (UEs) exhibit differentiated video demands and various network transmission environments. Traditional networking, which is static and base station (BS) concentric, can hardly deal with these challenges. Thus, adaptive video transmission schemes are needed by jointly considering the interplay among user demand, video source characteristics, and networking. This work focuses on user-cognizant scalable video transmission over heterogeneous cellular networks. The video source is encoded using scalable video coding, which enables dynamic adaption of source information to the requirements of UEs and is suitable for cellular networks in which the transmission link quality varies substantially over space and time. Three novel transmission schemes are proposed, layered digital transmission, layered hybrid digital-analog transmission, and cooperative digital transmission. Leveraging tools from stochastic geometry, a comprehensive analysis is conducted focusing on three key performance metrics: outage probability, high-definition probability, and average distortion. The associated spectrum allocation and video transmission are chosen based on the user-cognizant information, such as the requirements for video service, wireless channel status, and the connections with the BSs. The results show that the proposed user-cognizant transmission schemes can provide a scalable video experience for UEs.

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Author information

Authors and Affiliations

  1. Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China

    Liang Wu

  2. Huawei Technologies, shanghai, China

    Liang Wu

  3. Key Laboratory of Wireless-Optical Communications, Chinese Academy of Sciences, Hefei, China

    Wenyi Zhang

  4. Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China

    Wenyi Zhang

Authors
  1. Liang Wu
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  2. Wenyi Zhang
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Corresponding author

Correspondence to Liang Wu .

Editor information

Editors and Affiliations

  1. School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney, NSW, Australia

    Wei Zhang

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Wu, L., Zhang, W. (2019). User-Cognizant Scalable Video Transmission over Heterogeneous Cellular Networks. In: Zhang, W. (eds) Handbook of Cognitive Radio . Springer, Singapore. https://doi.org/10.1007/978-981-10-1394-2_36

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