TY - GEN
T1 - Resource Allocation for Improved User Experience with Live Video Streaming in 5G
AU - Mehmeti, Fidan
AU - La Porta, Thomas F.
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/11/22
Y1 - 2021/11/22
N2 - Providing a high-quality real-time video streaming experience to mobile users is one of the biggest challenges in cellular networks. This is due to the need of these services for high rates with low variability, which is not easy to accomplish given the competition among (usually a high number of) users for constrained network resources and the high variability of their channel characteristics. A way of improving the user experience is by exploiting their buffers and the ability to provide a constant data rate to everyone, as one of the features of 5G networks. However, the latter is not very efficient. To this end, in this paper we provide a theoretical-analysis framework for resource allocation in 5G networks that leads to an improved user experience when watching live video. We do this by solving three problems, in which the objectives are to provide the highest achievable video resolution to all one-class and two-class users, and to maximize the number of users that experience a given resolution. The analysis is validated by simulations that are run on traces. We also compare the performance of our approach against other techniques for different QoE metrics. Results show that the performance can be improved by at least 15% with our approach.
AB - Providing a high-quality real-time video streaming experience to mobile users is one of the biggest challenges in cellular networks. This is due to the need of these services for high rates with low variability, which is not easy to accomplish given the competition among (usually a high number of) users for constrained network resources and the high variability of their channel characteristics. A way of improving the user experience is by exploiting their buffers and the ability to provide a constant data rate to everyone, as one of the features of 5G networks. However, the latter is not very efficient. To this end, in this paper we provide a theoretical-analysis framework for resource allocation in 5G networks that leads to an improved user experience when watching live video. We do this by solving three problems, in which the objectives are to provide the highest achievable video resolution to all one-class and two-class users, and to maximize the number of users that experience a given resolution. The analysis is validated by simulations that are run on traces. We also compare the performance of our approach against other techniques for different QoE metrics. Results show that the performance can be improved by at least 15% with our approach.
UR - http://www.scopus.com/inward/record.url?scp=85121688977&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85121688977&partnerID=8YFLogxK
U2 - 10.1145/3479242.3487316
DO - 10.1145/3479242.3487316
M3 - Conference contribution
AN - SCOPUS:85121688977
T3 - Q2SWinet 2021 - Proceedings of the 17th ACM Symposium on QoS and Security for Wireless and Mobile Networks
SP - 69
EP - 78
BT - Q2SWinet 2021 - Proceedings of the 17th ACM Symposium on QoS and Security for Wireless and Mobile Networks
PB - Association for Computing Machinery, Inc
T2 - 17th ACM Symposium on QoS and Security for Wireless and Mobile Networks, Q2SWinet 2021
Y2 - 22 November 2021 through 26 November 2021
ER -