A Novel Spectrum Allocation Approach Using Hypergraph Matching in Dense Access Networks

This study explores an industrial Internet of Things (IIoT) scenario characterized by the dense deployment of femtocells within a macrocell coverage area. To address the critical challenges of inter-device interference and spectral efficiency optimization, we propose a novel D2D group architecture that integrates non-orthogonal multiple access (NOMA) technology for efficient group communications. However, the complex cumulative interference caused by channel sharing in such a network severely impairs the system performance, which was seldom considered in the previous study. To mitigate this issue, our framework proposes an innovative hypergraph-based spectrum allocation algorithm, where femtocell access points (FAPs) are represented as vertices and interference relationships are captured as hyperedges, enabling the application of hypergraph theory to formulate the optimal resource allocation problem. Comprehensive experimental evaluations demonstrate that the proposed scheme significantly improves the spectral efficiency compared to traditional graph-based spectrum allocation schemes.