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Wireless Virtual Reality

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Federated Learning for Wireless Networks

Part of the book series: Wireless Networks ((WN))

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Abstract

This chapter introduce the use of federated learning (FL) for wireless virtual reality (VR) applications. In particular, we first explain why we use to use FL for wireless VR applications. Then, we provide a detailed literature review of using FL for VR applications. We then introduce a representative work that focuses on the use of FL for the analysis and predictions of orientation and mobility of VR users so as to reduce break in presences of VR users.

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Notes

  1. 1.

    Here, as the size of the recorded data increases, the ESNs can use more historical data to build a relationship between historical orientations and locations, and future orientations and locations. Hence, the ESN prediction accuracy improves.

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Authors and Affiliations

  1. Department of Computer Science & Engineering, Kyung Hee University, Seoul, South Korea, Gyeonggi-do, Korea (Republic of)

    Choong Seon Hong & Latif U. Khan

  2. Department of Electrical Engineering, Princeton University, Princeton United States, Princeton, NJ, USA

    Mingzhe Chen

  3. Department of Electrical & Computer Engineering, University of Houston, TX, United States, Houston, TX, USA

    Dawei Chen & Zhu Han

  4. Bradely Department of Electrical & Computer Engineering, Virginia Polytechnic Institute and State University, Blacksburg, United States, Blacksburg, VA, USA

    Walid Saad

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  1. Choong Seon Hong
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  2. Latif U. Khan
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  6. Zhu Han
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Seon Hong, C., Khan, L.U., Chen, M., Chen, D., Saad, W., Han, Z. (2021). Wireless Virtual Reality. In: Federated Learning for Wireless Networks. Wireless Networks. Springer, Singapore. https://doi.org/10.1007/978-981-16-4963-9_7

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  • DOI: https://doi.org/10.1007/978-981-16-4963-9_7

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-4962-2

  • Online ISBN: 978-981-16-4963-9

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