Spatio-Temporal Scheduling Prediction Under Backhaul Delay for Resilient Coordinated Beamforming
Coordinated beamforming in distributed 5G networks relies on the timely exchange of inter-cell scheduling information, but backhaul latency makes this information stale. Even a single transmission time interval (TTI) of delay can reduce CBF-SLNR performance below the uncoordinated baseline, because the precoder suppresses interference toward users that are no longer active. Coordination on stale information is therefore worse than no coordination at all. To address this, we propose a two-stage predictive framework in which a Spectral Temporal Graph Neural Network (StemGNN) predicts future user equipment (UE) scheduling states from delayed historical observations, and the predictions repla...
| Authors | Prashant Kumar Singh, Shubham Vaishnav, Ahmet Hasim Gökceoglu et al. |
|---|---|
| Primary category | cs.NI |
| Published | 9 July 2026 |
| Last updated at source | 9 July 2026 |
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