This paper proposes a unified RF map construction framework using physics-informed neural networks and graph neural networks, achieving high-fidelity RF map construction under sparse observations.

This paper proposes an online method, M-OSVGP with GOIPS, for efficiently updating radio maps from streaming spectrum measurements.

This paper presents a portable, battery-powered RF capture system using a HackRF One SDR, Raspberry Pi 5, GNSS receiver, and high-speed storage for recording geotagged IQ data in real-world environmen…

RemoteRF is an open-source platform for creating and managing large-scale testbeds of distributed software-defined radios (SDRs) that can be accessed remotely over the internet.

The paper proposes a lightweight, self-adaptive framework using LoRA to efficiently extract and aggregate radio frequency fingerprints for robust open-set authentication in dynamic wireless environmen…

The paper proposes GUIDE, a physics-guided deep unfolding framework that enables practical, real-time cross-band channel prediction for AI-RAN by embedding wireless channel physics, significantly impr…

This paper proposes CR-CMAB, a framework for jointly optimizing base station deployment and UAV flight corridors in urban environments to minimize infrastructure investment and flight distance while s…

This paper proposes DANCE, a diffusion-based channel estimator for OFDM systems using a sparse linear inverse problem and a noise-adaptive posterior correction.

The paper introduces RadioMaster, a novel multi-agent system that successfully translates high-level user intents into physically viable, real-world radio signals, significantly outperforming existing…

This paper proposes a physical layer authentication mechanism using integrated sensing and communication (ISAC) to reconstruct environment layout, infer propagation channels, and authenticate transmit…

This paper analyzes direction-of-arrival estimation using a tunable receive-side lossless reciprocal MiLAC combiner for antenna arrays and shows it can achieve the digital Cramér-Rao bound with fewer…

The paper proposes RA-LWLM, a retrieval-augmented in-context localization framework that enables training-free, cross-scene wireless localization by externalizing scene-specific data into a fingerprin…

The paper introduces CAFOSat, a large-scale, strongly annotated, and infrastructure-aware dataset designed to improve the accuracy of mapping Concentrated Animal Feeding Operations (CAFOs) from high-r…