LTE Network Resource Management for Live Video Streaming in Dense Area

Moonphala, Borirak; Jansang, Aphirak; Tangtrongpairoj, Withawat; Jaikaeo, Chaiporn; Phonphoem, Anan

doi:10.1109/cyberneticscom55287.2022.9865381

Cited by 1 publication

(1 citation statement)

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“…A resource allocation algorithm for live video streaming that allocates resources based on the channel quality and priority of UEs is proposed in [6]. The proposed policy makes use of streaming statistics to reserve resources for UEs that have priority in the system.…”

Section: Resource Allocationmentioning

confidence: 99%

Optimal Resource Allocation for Loss-Tolerant Multicast Video Streaming

Zuhra

Besser

Chaporkar

et al. 2023

Entropy

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In video streaming applications, especially during live streaming events, video traffic can account for a significant portion of the network traffic and can lead to severe network congestion. For such applications, multicast provides an efficient means to deliver the same content to a large number of users simultaneously. However, in multicast, if the base station transmits content at rates higher than what can be decoded by users with the worst channels, these users will experience outages. This makes the multicast system’s performance dependent on the weakest users in the system. Interestingly, video streams can tolerate some packet loss without a significant degradation in the quality experienced by the users. This property can be leveraged to improve the multicast system’s performance by reducing the dependence of the multicast transmissions on the weakest users. In this work, we design a loss-tolerant video multicasting system that allows for some controlled packet loss while satisfying the quality requirements of the users. In particular, we solve the resource allocation problem in a multimedia broadcast multicast services (MBMS) system by transforming it into the problem of stabilizing a virtual queuing system. We propose two loss-optimal policies and demonstrate their effectiveness using numerical examples with realistic traffic patterns from real video streams. It is shown that the proposed policies are able to keep the loss encountered by every user below its tolerable loss. The proposed policies are also able to achieve a significantly lower peak SNR degradation than the existing schemes.

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Section: Resource Allocationmentioning

confidence: 99%