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Non-Coherent Over-the-Air Decentralized Gradient Descent
March 20, 2024, 4:43 a.m. | Nicolo Michelusi
cs.LG updates on arXiv.org arxiv.org
Abstract: Decentralized Gradient Descent (DGD) is a popular algorithm used to solve decentralized optimization problems in diverse domains such as remote sensing, distributed inference, multi-agent coordination, and federated learning. Yet, executing DGD over wireless systems affected by noise, fading and limited bandwidth presents challenges, requiring scheduling of transmissions to mitigate interference and the acquisition of topology and channel state information -- complex tasks in wireless decentralized systems. This paper proposes a DGD algorithm tailored to wireless …
abstract agent algorithm arxiv bandwidth challenges cs.it cs.lg decentralized distributed diverse domains eess.sp federated learning gradient inference interference math.it multi-agent noise optimization popular scheduling sensing solve systems type wireless
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