Inductive Latent Context Persistence: Closing the Post-Handover Cold Start in 6G Radio Access Networks
Anubhab Banerjee, Daniyal Amir Awan

TL;DR
This paper introduces ILCP, a method that preserves mobility context across handovers in 6G RANs, significantly reducing ping-pong handovers and improving decision accuracy by transmitting compressed state information.
Contribution
ILCP models RAN as a dynamic graph, compresses and transports user state to address post-HO cold start, and demonstrates substantial improvements over measurement-only and baseline models.
Findings
ILCP achieves 0.0% ping-pong HOs versus 6.5% baseline.
Post-HO accuracy improves by +5.1 percentage points.
ILCP runs at 7.7 ms per handover decision on a GTX 1080.
Abstract
In modern radio access networks (RANs), rule-based handover (HO) decisions (e.g., A3/A5) depend on user equipment (UE) measurements only, so UEs at the same location can receive inconsistent HO outcomes. GNN-based methods improve HO KPIs using richer context than measurements alone. However, recurrent or graph models discard the per-UE recurrent state at HO and reinitialize at the target next-generation Node B (gNB), losing mobility history and forcing the target model to rebuild from post-HO measurements only. We address this post-HO cold start with Inductive Latent Context Persistence (ILCP), compressing the source recurrent state, transporting it on the 3GPP Xn as a 128-byte payload, and adapting it at the target gNB. We model the RAN as a dynamic heterogeneous graph over UE nodes, gNB nodes, measurement edges, and Xn edges. On a Vienna 4G/5G drive-test, ILCP achieves 0.0% ping-pong…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
