Towards Massively Parallel HyperDimensional Computing Architectures for Intelligent Satellite Links
Hubless full-mesh VSAT modems require rapid receiver-gain adaptation under dynamic channel impairments, where conventional rule-based automatic gain control (AGC) becomes less effective at high symbol rates. This paper presents a Hyperdimensional Computing (HDC) accelerator architecture for VSAT modems. The proposed method integrates a policy-based reinforcement learning algorithm for AGC together with a configurable encoder and similarity-checking accelerator. The design enables low-latency, high-throughput online decision making for burst-mode satellite networks. The accelerator achieves a throughput of 380k inferences/s and an energy efficiency of 15.2 GIPS/W, while reducing bit errors by 89% compared to the baseline under real-world conditions.
Citation
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@inproceedings{mohsen2026TowardsMassivelyParallelHyperDimensionalComputingArchitecturesforIntelligentSatelliteLinks2026,
title = {Towards Massively Parallel HyperDimensional Computing Architectures for Intelligent Satellite Links},
author = {Mohsen Asghari and Masoud Rahimi and Sébastien Le Beux and Otmane Ait Mohamed and Cos Modafferi and Ron Mankarious},
booktitle = {CF '26: Proceedings of the 22nd ACM International Conference on Computing Frontiers},
year = {2026}
} Remerciements
Ces travaux ont été soutenus en partie par le Conseil de recherches en sciences naturelles et en génie du Canada (CRSNG) et par le Fonds de recherche du Québec — Nature et technologies (FRQNT).