Clustering- and Graph-Coloring-Based Inter-Network Interference Mitigation for Wireless Body Area Networks

In dense Wireless Body Area Network (WBAN) environments, inter-network interference significantly degrades the reliability of medical data transmission. This paper proposes a novel MAC layer interference mitigation strategy that integrates interference-priority-weighted K-means++ clustering with graph-coloring-based time slot allocation. Unlike traditional coexistence schemes, our two-phase approach first partitions the network using a weighted metric combining physical distance and Interference Signal Strength (ISS), ensuring a balanced distribution of high-priority WBANs. Subsequently, we employ an enhanced Priority-Weighted Welch–Powell algorithm to assign collision-free time slots within each cluster. Simulation results demonstrate that the proposed strategy outperforms IEEE 802.15.4, CSMA/CA, and random coloring benchmarks. It reduces inter-network interference by 26.7%, improves priority node distribution balance by 65.7%, and maintains a transmission success rate above 80% under high-load conditions. The proposed method offers a scalable and low-complexity solution for reliable vital sign monitoring in crowded healthcare scenarios.