CORTEXA
← Browse
arxiveess.SPcs.LG2026-07-05

AI-RAN on NPUs: Baseband Processing Without Baseband Chips

Shilong Zhang, Luping Xiang, Jienan Chen, Kun Yang

AI-RAN aims to unify artificial intelligence and radio access network workloads on a shared compute substrate. While this paradigm has so far been demonstrated primarily on Graphics Processing Units (GPUs), it remains unclear whether Neural Processing Units (NPUs), which are AI accelerators optimized for inference, can also support wireless baseband processing. Here, we provide the first affirmative answer by resolving the fundamental mismatch between baseband workloads and NPU architecture. A computational isomorphism exists: matrix and vector engines NPUs dedicate to inference inherently cover physical-layer operations. Yet NPU architectures are natively shaped for dense-tensor AI inference, not baseband. This architectural mismatch surfaces as opposing optimization objectives: traditional baseband minimizes arithmetic operations, whereas NPU performance demands maximizing engine utilization. We close this gap by reconstructing communication algorithms onto AI compute primitives, prioritizing engine utilization over arithmetic count. We validate this with a complete OFDM transceiver on an Ascend 310B1 edge NPU, demonstrating end-to-end over-the-air transmission via USRP X300 at 3.0 GHz.

View free PDFSource page

Related papers

arxiveess.SP2026-07-24

Innovation-Domain Decision-Directed Phase Tracking for Wiener Phase Noise in Fast Rayleigh Fading

Ura Klongklaew, Nithiroth Pornsuwancharoen, Phichai Youplao

This letter proposes an innovation-domain decision-directed phase tracking (ID-DDPT) architecture for coherent detection over Rayleigh fading channels with temporally correlated phase evolution and Wiener phase noise. By reformulating phase tracking into the innovation domain, re…

View free PDFSource page
arxiveess.SPphysics.app-ph2026-07-24

Noise-Robust Frequency Estimation via Overlapped Sampling-Intervals Zero-Crossing Fitting

Phichai Youplao, Nithiroth Pornsuwancharoen, Yusaku Fujii

The trade-off between noise averaging and temporal resolution fundamentally limits conventional zero-crossing frequency estimators under dynamic and noisy conditions. This paper presents an overlapped sampling-intervals zero-crossing fitting method (OS-ZFM), which introduces a st…

View free PDFSource page
arxiveess.SP2026-07-24Cited by 132

Propagation models for IEEE 802.15.6 standardization of implant communication in body area networks

Raul Chavez-Santiago, Kamran Sayrafian-Pour, Ali Khaleghi, Kenichi Takizawa, Jianqing Wang, Ilangko Balasingham, et al.

A body area network is a radio communication protocol for short-range, low-power, and highly reliable wireless communication for use on the surface, inside, or in the peripheral proximity of the human body. Combined with various biomedical sensors, BANs enable realtime collection…

View free PDFSource page
arxiveess.SP2026-07-24

Continuous Intra-Symbol Phase Noise Tracking for THz OFDM via Polynomial Reconstruction

Sawatsakorn Chaiyasoonthorn, Ura Klongklaew, Phichai Youplao

Terahertz (THz) communication systems for sixth-generation (6G) networks are severely impaired by Wiener phase noise (WPN), whose innovation variance at sub-THz carriers is substantially larger than in millimeter-wave 5G systems. Conventional common-phase-error (CPE) compensation…

View free PDFSource page
arxiveess.SP2026-07-24Cited by 83

Ultra-wideband statistical propagation channel model for implant sensors in the human chest

Ali Khaleghi, Raúl Chávez-Santiago, Ilangko Balasingham

Implant medical wireless sensors for monitoring physiological parameters, automatic drug provision, and so on represent a new promising healthcare technology. Inherent characteristics of ultra-wideband (UWB) radio make this technology highly suitable for the wireless interface of…

View free PDFSource page