arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2403.03492cs.NI

面向6G异构网络中定制化QoS保障的用户关联与资源分配联合优化

Joint User Association and Resource Allocation for Tailored QoS Provisioning in 6G HetNets

Yongqin Fu, Xianbin Wang

AI总结:

针对6G异构网络中传统方案难以实现定制化QoS保障的问题,提出将联合问题分解为两个子问题并通过交互优化算法迭代求解,实验验证其在平均效用和用户满意度上优于基线算法。

摘要:

具备差异化服务质量(QoS)需求的无线应用的普及,使得定制化QoS保障成为必要。随着无线基础设施复杂度不断提升,用户设备(UE)感知到的应用专属QoS,由其在异构网络(HetNets)中与支撑基站的关联状态、以及分配到的资源量共同决定。然而,传统的基于应用无关目标的用户关联与资源分配方案,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保障的实现。因此,本文针对6G异构网络中的定制化QoS保障需求,研究了具备应用专属目标的用户关联与资源分配联合问题。该问题的解空间极大,且同时包含离散与连续变量,本质上难以直接求解。为此,我们将原问题分解为用户关联和资源分配两个子问题,并提出一种交互优化算法(IOA),以交互方式迭代求解两个子问题直至收敛。具体而言,我们利用匹配理论求解资源分配子问题,采用启发式方法求解用户关联子问题。大量实验结果证实,IOA算法在平均效用和UE满意度两个指标上均优于多种基线算法。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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