Ultra-Dense Networks (UDNs) have been proposed to meet the ultra-high system capacity and ultra-high user experience rate requirements of sixth generation (6G) mobile networks. However, ultra-dense base stations (BSs) deployment poses challenges for cell-edge users such as BS selection, severe interference, resource allocation, and inter-cell handover. To tackle these obstacles, this paper formulates a joint BS clustering and resource allocation problem for cell-edge users in a 6G heterogeneous UDN system. For efficient resolution, this problem is decoupled into two sub-problems to be solved independently. We first propose a user-centric BS clustering algorithm based on many-to-many matching for the BS clustering problem in the heterogeneous UDN system; This algorithm considers the constraint of the system capacity. A many-to-many stable matching between users and small cell BSs is constructed under the optimization objective of maximizing the achievable user rate. Furthermore, we analyze the effectiveness, stability, convergence, and complexity of the BS clustering algorithm. Given established small cell BS clusters, we also propose a user-centric resource allocation algorithm based on network partitioning. This algorithm accounts for the interference of all users in the heterogeneous UDN system and maximizes intra-sub-network interference while minimizing inter-sub-network interference via a spectral clustering-based sub-network partitioning algorithm. Next, orthogonal allocation of resource blocks (RBs) is implemented within each sub-network, and RBs are spatially multiplexed between sub-networks. Numerical results confirm the benefits of the proposed methods: our algorithms outperform benchmark solutions in terms of the sum achievable system rate, average achievable user rate, and user spectral efficiency.

超密集网络(UDNs)被提出来满足第六代(6G)移动网络的超高系统容量和超高用户体验速率要求。然而，超密集基站 (BS) 部署给小区边缘用户带来了挑战，例如 BS 选择、严重干扰、资源分配和小区间切换。为了解决这些障碍，本文为 6G 异构 UDN 系统中的小区边缘用户制定了联合 BS 聚类和资源分配问题。为了有效解决，这个问题被分离成两个独立解决的子问题。针对异构UDN系统中的BS聚类问题，我们首先提出了一种基于多对多匹配的以用户为中心的BS聚类算法；该算法考虑了系统容量的约束。在最大化可实现的用户速率的优化目标下，构建用户和小小区BS之间的多对多稳定匹配。此外，我们分析了 BS 聚类算法的有效性、稳定性、收敛性和复杂性。给定已建立的小型基站集群，我们还提出了一种基于网络分区的以用户为中心的资源分配算法。该算法考虑了异构UDN系统中所有用户的干扰，并通过基于频谱聚类的子网划分算法最大化子网内干扰，同时最小化子网间干扰。接下来，在每个子网络内实现资源块（RB）的正交分配，并且RB在子网络之间进行空间复用。