AI & ML
System-Level Evaluation of Uplink Access Schemes for Ambient IoT
arXiv cs.NI0 views
arXiv:2610.30856v1 Announce Type: new Abstract: Ambient Internet of Things (A-IoT) devices operate under stringent energy constraints, relying on harvested power in the $\mu$W-to-mW range and limited energy storage. The A-IoT air interface for active devices is still under development; we therefore use Narrowband Internet of Things (NB-IoT) as an implementable reference for evaluating autonomous Uplink (UL) access under harvested energy. Under these conditions, the standard NB-IoT contention-based Random Access (RA) procedure incurs substantial per-packet overhead, making UL access in dense A-IoT networks increasingly energy-expensive. Context-retaining UL access schemes reduce this overhead, but their energy-latency trade-offs are insufficiently studied in literature under realistic harvesting and protocol constraints. To address this gap, we extend the LENA-NB ns-3 module with solar energy harvesting, supercapacitor storage, and a hysteretic brown-out mechanism, and propose Hybrid Scheduling Request (HSR), a hybrid UL access scheme combining reserved request occasions with opportunistic contention. We compare RA, Scheduling Request (SR), HSR and an Idealized Fast Uplink Grant (FUG) serving as a performance bound. Results show that HSR reduces mean packet delay by up to 69% and SR reduces energy per delivered bit by up to 24%, both relative to RA.
Source:https://arxiv.org/abs/2610.30856PreviousOMRC: Multipath Reliability for Direct-Connect Optical InterconnectsNextAERIAL: Mission-Aware LLM Selection for Language-Driven UAV Control in Flying Networks
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