A Graph Clustering-Based Resource Reservation Solution for Low-Latency Networks in Massive MIMO Systems

We present a graph clustering-based resource reservation solution for low-latency networks (LLNs) in massive multiple input multiple output (MIMO) systems, addressing the inadequacies of traditional dynamic resource allocation methods in meeting stringent latency requirements. While resource reservation allows data transmission without dynamic scheduling requests, timing discrepancies between the next Generation Node B (gNodeB) and user equipment (UE) often lead to excessive resource reservations, causing inefficiencies. Our proposed method utilizes a graph clustering approach to identify multi-user sets based on probabilistic multiplexing gain, optimizing resource use by grouping UEs with high co-transmission probabilities and low interference. Additionally, a frequency-spatial resource orchestration scheme is introduced to further minimize resource waste. Simulation results indicate that our solution significantly outperforms conventional methods in terms of resource efficiency and latency assurance.