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：随着无线赋能应用的激增及其对服务质量（QoS）需求的差异化，定制化的QoS保障变得至关重要。随着无线基础设施日益复杂，用户设备（UE）所感知的特定应用QoS由其在异构网络（HetNet）中与支持基站的关联方式以及所分配的资源量共同决定。然而，基于传统应用无关目标的用户关联与资源分配方法往往忽略了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的保障。为此，本文研究了面向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。由于解空间极大且包含离散与连续变量的组合，该问题本质难以直接求解。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（IOA），通过迭代交互求解直至收敛。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，IOA算法在平均效用和UE满意度比率方面均优于多种基线算法。