QoE-Aware Bandwidth Resource Allocation Strategy for Ultra-High-Definition Video Services in B5G: A Game Theoretic Approach
Zaijian Wang, X. Liu, Huanhuan Gu, Shiwen Mao, Zikang Peng · IEEE Internet of Things Journal · 2024
With ultra-high-definition (UHD) video services developing in B5G networks, such as an UHD video surveillance system with a resolution of$7680\times 4320$p, that generates video data 24/7, the high-service overhead caused by the bandwidth resource bottleneck will greatly affect the performance of video services. Network slice provider (NSP) focuses on the overall revenue. However, network slice user (NSU) emphasizes task requirements and cost. A crucial challenge to find a desirable tradeoff between NSPs and NSUs since the objective of NSPs’ Quality of Experience (QoE) is partially in conflict with the objective of NSUs’ QoE. In order to investigate the performance of data transmission for UHD video from the perspective of QoE, a Stackelberg game model is leveraged to achieve the optimization goals after constructed a novel QoE model. After analyzing the game process, Nash equilibrium can be achieved that indicates a relatively optimal state. A problem of maximizing the overall effective QoE is formulated by jointly optimizing NSPs’ QoE, NSUs’ QoE and the bandwidth resource allocation. To tackle the nonconvex formulated problem, a QoE-Aware Game-theoretic Band-width Resource Allocation Strategy for UHD Video Services named “QAGBRAS” is proposed. Extensive experiments are conducted to evaluate performance of the proposed approach against the state-of-the art solutions in terms of network congestion control, bandwidth utilization, and QoE factors, including NSP’s revenue, NSU’s task requirements, and cost. Simulation results show that our proposed approach can effectively achieve the optimal solution in the context of QoE.