The proliferation of wireless-enabled applications with divergent quality of service (QoS) requirements necessitates tailored QoS provisioning. With the growing complexity of wireless infrastructures, application-specific QoS perceived by a user equipment (UE) is jointly determined by its association with the supporting base station in heterogeneous networks (HetNets) and the amount of resource allocated to it. However, conventional application-agnostic objective-based user association and resource allocation often ignore the differences among applications' specific requirements for resources, inevitably preventing tailored QoS provisioning. Hence, in this paper, the problem of joint user association and resource allocation with application-specific objectives is investigated for achieving tailored QoS provisioning in 6G HetNets. This problem is intrinsically difficult to solve directly due to the extremely large solution space and the combination of discrete and continuous variables. Therefore, we decompose the original problem into two subproblems, i.e. user association and resource allocation, and propose an interactive optimization algorithm (IOA) to solve them iteratively in an interactive way until convergence is achieved. Specifically, matching theory is utilized to solve resource allocation and user association is solved heuristically. Extensive experimental results confirm that IOA algorithm outperforms several baseline algorithms in terms of both average utility and UE satisfaction ratio.

翻译：随着具有不同服务质量需求的无线应用激增，定制化QoS保障变得不可或缺。随着无线基础设施日益复杂，用户设备感知到的应用特定QoS由异构网络中其与支持基站之间的关联关系以及分配给它的资源量共同决定。然而，传统的基于非应用感知目标的用户关联与资源分配方法往往忽略不同应用对资源的特定需求差异，不可避免地阻碍了定制化QoS的供给。为此，本文研究面向6G异构网络中实现定制化QoS保障的、具有应用特定目标的联合用户关联与资源分配问题。由于解空间极其庞大且涉及离散与连续变量的组合，该问题直接求解存在本质困难。因此，我们将原问题分解为用户关联与资源分配两个子问题，并提出一种交互式优化算法，通过迭代交互方式求解直至收敛。具体而言，利用匹配理论求解资源分配问题，并采用启发式方法求解用户关联问题。大量实验结果表明，所提出的IOA算法在平均效用和用户满意度比率方面均优于多种基线算法。