基于QoE感知的星地一体化网络公平资源分配策略

QoE-Aware Fair Resource Allocation Strategy for Integrated Satellite and Terrestrial Networks

星地一体化网络是卫星网络和地面网络互联,实现卫星网络和地面网络优势互补的一体化网络。随着无线通信的快速发展,卫星网络和地面网络的同频复用技术可有效提升资源利用效率,满足日益增长的无线数据业务需求。但由于无线数据业务类型的多样化和频谱资源的稀缺性,如何实现用户数据服务的服务体验质量(Quality of experience,QoE)和公平性提升也成为星地一体化网络亟待解决的关键问题。本文综合考虑信道时变性、服务体验多样性和服务公平性,提出了一种基于QoE感知的星地一体化网络资源分配策略。为此,将目标问题描述为基于时间平均的服务体验质量的网络公平效用最大化,并利用李雅普诺夫优化理论,将复杂的动态原始优化问题进一步转化并分解为3个瞬时优化子问题,每个子问题可以在每个时隙独立求解。同时,由于无线资源分配为典型的非凹混合组合优化问题,推导了一个低复杂度的两步算法来求解第三个资源分配子问题。仿真结果揭示了在不同的公平性参数下用户的长时QoE与公平性之间的折衷情况。

Integrated satellite and terrestrial networks are the integrated networks in which the satellite network and the terrestrial network are interconnected to realize the complementary advantages of the satellite network and the terrestrial network.With the rapid development of wireless communication,the co-frequency multiplexing technology of integrated satellite and terrestrial networks can effectively improve the resource utilization efficiency and meet the growing demands of wireless data services.However,due to the diversity of wireless data services and the scarcity of spectrum resources,how to improve the quality of experience(QoE)and fairness has become a key problem to be solved in the integrated satellite and terrestrial networks.We investigate a general QoE-aware dynamic resource allocation strategy with consideration of the time-varying channels,diversified user’s quality of experience and fairness for the integrated satellite and terrestrial networks.To do so,we formulate the objective problem as the maximization of the network fairness utility based on the time-averaged QoE.By using the Lyapunov optimization theory,we further transform and decompose the initial problem into three subproblems which can be independently solved at each slot.Meanwhile,we derive a low complexity two-step algorithm to solve the third resource allocation subproblem which is a non-concave mix combination optimization problem.The simulation results reveal the tradeoff between user’s long-term time-averaged QoE and fairness performance under different fairness parameters.