360° mulsemedia experience over next generation wireless networks - a reinforcement learning approach

Comsa, Ioan-Sorin, Trestian, Ramona ORCID logoORCID: https://orcid.org/0000-0003-3315-3081 and Ghinea, Gheorghita (2018) 360° mulsemedia experience over next generation wireless networks - a reinforcement learning approach. 2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX). In: IEEE 10th QoMEX, 29 May - 01 June 2018, Italy. e-ISBN 9781538626054, e-ISBN 9781538626047, pbk-ISBN 9781538626061. [Conference or Workshop Item] (doi:10.1109/QoMEX.2018.8463409)

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The next generation of wireless networks targets aspiring key performance indicators, like very low latency, higher data rates and more capacity, paving the way for new generations of video streaming technologies, such as 360° or omnidirectional videos. One possible application that could revolutionize the streaming technology is the 360° MULtiple SEnsorial MEDIA (MULSEMEDIA) which enriches the 360° video content with other media objects like olfactory, haptic or even thermoceptic ones. However, the adoption of the 360° Mulsemedia applications might be hindered by the strict Quality of Service (QoS) requirements, like very large bandwidth and low latency for fast responsiveness to the users, inputs that could impact their Quality of Experience (QoE). To this extent, this paper introduces the new concept of 360° Mulsemedia as well as it proposes the use of Reinforcement Learning to enable QoS provisioning over the next generation wireless networks that influences the QoE of the end-users.

Item Type: Conference or Workshop Item (Paper)
Research Areas: A. > School of Science and Technology > Computer and Communications Engineering
Item ID: 24034
Notes on copyright: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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Depositing User: Ramona Trestian
Date Deposited: 29 Mar 2018 09:19
Last Modified: 07 Jun 2022 05:11
URI: https://eprints.mdx.ac.uk/id/eprint/24034

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