TARMM uses a temporal graph to model RAN dynamics and MARL with action masking for proactive mobility management in 5G O-RAN, reducing tail latency by up to 44% and packet loss by up to 56% on a multi-cell testbed for VR workloads.
Decentralized han- dover parameter optimization with marl for load balanc- ing in 5g networks
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TARMM: Scaling Delay-Critical Edge AI Offloading in 5G O-RAN via Temporal Graph Mobility Management
TARMM uses a temporal graph to model RAN dynamics and MARL with action masking for proactive mobility management in 5G O-RAN, reducing tail latency by up to 44% and packet loss by up to 56% on a multi-cell testbed for VR workloads.