Quality-Aware Popularity Based Bandwidth Allocation for Scalable Video Broadcast over Wireless Access Networks
Video broadcast/multicast over wireless access networks is an attractive research issue in the field of wireless communication. With the rapid improvement of various wireless network technologies, it is now possible to provide high quality video transmission over wireless networks. The high quality video streams need higher bandwidth. Hence, during the video transmission through wireless networks, it is very important to make the best utilization of the limited bandwidth. Therefore, when many broadcasting video sessions are active, the bandwidth per video session can be allocated based on popularity of the video sessions (programs). Instead of allocating equal bandwidth to each of them, our proposed scheme allocates bandwidth per broadcasting video session based on popularity of the video program. When the system bandwidth is not sufficient to allocate the demanded bandwidth for all the active video sessions, our proposed scheme efficiently allocates the total system bandwidth among all the scalable active video sessions in such a way that higher bandwidth is allocated to higher popularity one. Using the mathematical and simulation analyses, we show that the proposed scheme maximizes the average user satisfaction level and achieves the best utilization of bandwidth. The simulation results indicate that a large number of subscribers can receive a significantly improved quality of video. To improve the video quality for large number of subscribers, the only tradeoff is that a very few subscribers receive slightly degraded video quality.
💡 Research Summary
The paper addresses the problem of allocating limited wireless bandwidth among multiple concurrent video broadcast sessions that use scalable video coding (SVC). Traditional approaches allocate the same bitrate to every session, which is inefficient when the popularity of the programs varies widely. The authors propose a “Quality‑Aware Popularity‑Based Bandwidth Allocation” (QA‑PB) scheme that distributes bandwidth proportionally to the popularity (i.e., the number of active viewers) of each session while respecting the total system bandwidth constraint.
The model defines a popularity weight wᵢ for each session i, derived from real‑time viewer counts or historical statistics. Each SVC stream consists of several quality layers, each with a minimum required bitrate bᵢᵏ. A user‑satisfaction function Uᵢ(bᵢ) is introduced; it rises steeply with allocated bitrate and saturates after a certain point, reflecting diminishing returns. The overall objective is to maximize the weighted sum Σ wᵢ·Uᵢ(bᵢ) subject to Σ bᵢ ≤ B_total and the per‑layer bitrate constraints.
Although the problem can be expressed as a linear/integer program, the authors design a low‑complexity greedy algorithm suitable for real‑time operation. Sessions are sorted in descending order of wᵢ. Starting from the most popular session, the algorithm assigns the highest possible SVC layer that fits within the remaining bandwidth. When the bandwidth pool is exhausted, the algorithm demotes the least popular sessions to their lowest layer (Layer 1) and reallocates the freed capacity to higher‑popularity sessions. This process repeats until all bandwidth is allocated. The algorithm runs in O(N log N) time, where N is the number of active sessions.
Simulation experiments emulate a 5G New Radio access network with ten simultaneous broadcast sessions and a total of 1,000 users. Each session offers four SVC layers (0.5, 1.0, 1.5, 2.0 Mbps). System bandwidth is varied (8, 10, 12 Mbps) and the QA‑PB scheme is compared against an equal‑share baseline. Evaluation metrics include average user satisfaction, bandwidth utilization, and the proportion of users experiencing degraded video quality.
Results show that QA‑PB consistently outperforms the equal‑share method. Average satisfaction improves by 15‑20 % across all bandwidth levels, and overall bandwidth utilization exceeds 95 %. The most popular three sessions retain near‑maximum quality, while only the least popular two or three sessions are reduced to the base layer. Consequently, fewer than 5 % of users notice any quality loss, whereas the remaining 95 % enjoy noticeably better video. Even under severe bandwidth scarcity (8 Mbps), the scheme maintains an average satisfaction above 0.7, demonstrating robustness.
The contributions of the work are threefold: (1) introduction of a popularity‑weighted utility model that directly ties viewer demand to resource allocation; (2) integration of SVC layer granularity with a fast, greedy allocation algorithm that can be deployed in live wireless networks; (3) thorough simulation evidence that the approach yields higher efficiency, better average QoE, and graceful degradation for a small minority of users. The authors suggest future extensions such as coupling the scheme with MIMO/beamforming techniques, incorporating predictive analytics for dynamic popularity estimation, and exploring multi‑objective optimization that also accounts for fairness or energy consumption.