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arXiv · 2510.11150

WiNPA: Wireless Neural Processing Architecture

Sai Xu·Yanan Du
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Abstract

This article presents a wireless neural processing architecture (WiNPA), providing a novel perspective for accelerating edge inference of deep neural network (DNN) workloads via joint optimization of wireless and computing resources. WiNPA enables fine-grained integration of wireless communication and edge computing, bridging the research gap between wireless and edge intelligence and significantly improving DNN inference performance. To fully realize its potential, we explore a set of fundamental research issues, including mathematical modeling, optimization, and unified hardware--software platforms. Additionally, key research directions are discussed to guide future development and practical implementation. A case study demonstrates WiNPA's workflow and effectiveness in accelerating DNN inference through simulations.

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Sai Xu, Yanan Du. 2025-10-13. WiNPA: Wireless Neural Processing Architecture. https://arxiv.org/abs/2510.11150

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