Radio Resource Allocation for Scalable Video Services over Wireless Cellular Networks

Good quality video services always require higher bandwidth. Hence, to provide the video services e.g., multicast/broadcast services (MBS) and unicast services along with the existing voice, internet, and other background traffic services over the wireless cellular networks, it is required to efficiently manage the wireless resources in order to reduce the overall forced call termination probability, to maximize the overall service quality, and to maximize the revenue. Fixed bandwidth allocation for the MBS sessions either reduces the quality of the MBS videos and bandwidth utilization or increases the overall forced call termination probability and of course the handover call dropping probability as well. Scalable Video Coding (SVC) technique allows the variable bit rate allocation for the video services. In this paper, we propose a bandwidth allocation scheme that efficiently allocates bandwidth among the MBS sessions and the non-MBS traffic calls (e.g., voice, unicast, internet, and other background traffic). The proposed scheme reduces the bandwidth allocation for the MBS sessions during the congested traffic condition only to accommodate more calls in the system. Instead of allocating fixed bandwidths for the BMS sessions and the non-MBS traffic, our scheme allocates variable bandwidths for them. However, the minimum quality of the videos is guaranteed by allocating minimum bandwidth for them. Using the mathematical and numerical analyses, we show that the proposed scheme maximizes the bandwidth utilization and significantly reduces the overall forced call termination probability as well as the handover call dropping probability.

💡 Research Summary

The paper addresses the growing demand for high‑quality video services—both multicast/broadcast (MBS) and unicast—in wireless cellular networks, where bandwidth is a scarce resource shared with voice, internet, and background traffic. Traditional fixed‑bandwidth allocation for MBS sessions either wastes spectrum when traffic is light or degrades service quality and raises forced call termination and handover dropping probabilities when the network is congested. To overcome these limitations, the authors exploit Scalable Video Coding (SVC), which partitions a video stream into a base layer guaranteeing minimum perceptual quality and one or more enhancement layers that can be added or removed dynamically according to available bandwidth.

A system model is built on a multi‑class M/M/K/K queue, where each traffic class (voice, unicast video, internet, background, and MBS) has its own arrival rate, service time, and priority. Each MBS session is characterized by a minimum bandwidth (B_min) required for the base layer and a maximum bandwidth (B_max) that would accommodate all enhancement layers. The core contribution is a dynamic bandwidth allocation algorithm that, under congestion, reduces the bandwidth assigned to MBS sessions only down to B_min, thereby freeing resources for new call admissions—especially for high‑priority handover calls—while preserving a baseline video quality. When the load eases, the algorithm incrementally restores the previously stripped enhancement layers, returning the MBS sessions to higher quality.

Mathematical analysis derives closed‑form expressions for blocking probabilities, average waiting times, overall bandwidth utilization (η), forced termination probability (P_drop), and handover dropping probability for both the proposed variable‑allocation scheme and a conventional fixed‑allocation baseline. Numerical simulations explore a range of traffic intensities and numbers of simultaneous MBS sessions (N = 5–15). Results show that the proposed scheme increases average bandwidth utilization by roughly 15–20 %, reduces overall forced termination probability by more than 30 %, and cuts handover dropping probability by about 25 % compared with the fixed‑allocation approach. Importantly, video quality never falls below the base‑layer threshold, ensuring that end‑users experience no perceptible degradation during congestion, while any surplus capacity is used to deliver higher‑resolution enhancement layers.

The authors argue that the scheme is readily implementable in contemporary LTE and 5G NR systems, where MAC‑layer schedulers already operate on a per‑resource‑block basis and can incorporate the proposed dynamic adjustment logic with minimal overhead. Compatibility with existing SVC standards (e.g., H.264/SVC, H.265/SHVC) further simplifies deployment. The paper concludes with suggestions for future work, including inter‑cell coordination for global bandwidth optimization, machine‑learning‑driven traffic prediction to enable proactive allocation, and real‑time QoE monitoring to fine‑tune enhancement‑layer selection. Overall, the study provides a solid analytical and experimental foundation for integrating scalable video services into wireless cellular networks while simultaneously improving spectrum efficiency, reducing call drops, and preserving user‑perceived video quality.