The paper introduces SpikeWFM, a novel hybrid architecture combining spiking neural networks (SNNs) and transformers, which significantly improves the robustness and accuracy of wireless foundation mo…

This paper proposes a model for cross-band CSI reconstruction in multi-band low-altitude wireless systems using radio-frequency metadata and pilot-guided cross-attention.

This survey examines explainable AI (XAI) in wireless PHY layers, formalizing goals, taxonomy, and applications.

This paper proposes a statistical framework for designing task-aware multiple-input multiple-output (MIMO) precoders in future wireless networks using statistical channel state information and trainin…

This paper proposes a protocol framework for making the 6G air interface AI-native, focusing on interoperability and preserving implementation freedom.

This paper proposes a new communication framework, TokCom, for 6G wireless networks where tokens from large language models become the fundamental entities for information exchange.

This paper proposes a generative AI framework using a cGAN for proactive interference mitigation in ultra-dense indoor networks, achieving significant SINR gain, packet-loss reduction, and CSI oracle…

This paper proposes FAConformer, a framework for auditory attention decoding using frequency-aware CNN-Transformer, which performs frequency-aware modeling and outperforms existing methods.

This paper proposes AirPASS, an alternating optimization framework for over-the-air federated learning in wireless systems using a multi-waveguide pinching antenna system.

This paper proposes a heterogeneous neural network accelerator for multi-task RF signal recognition, achieving high accuracy and low latency for automatic modulation recognition, hardware-Trojan cover…

The paper presents ReWiS, a reservoir framework for WiFi sensing that transforms channel state information into structured streams, encodes them with a graph-coupled reservoir, and adapts to new domai…

The paper proposes DRIFT, a lightweight joint channel estimation and prediction framework, to significantly reduce pilot overhead and boost spectral efficiency in power-constrained LEO Non-Terrestrial…

The paper introduces The AI Telco Engineer (AITE), a framework for autonomously designing wireless communication algorithms using large language models, achieving better performance and reduced latenc…

This paper proposes a lightweight, distributed machine learning framework for sub-centimeter indoor localization using D-MIMO in O-RAN architectures, reducing midhaul traffic by 100x while maintaining…

The paper proposes a lightweight Temporal Convolutional Network (TCN) that incorporates physical motion-aware attention mechanisms to efficiently and effectively perform WiFi CSI-based Human Activity…

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 a channel prediction-based Physical Layer Authentication (PLA) framework using a Transformer module to maintain robust authentication accuracy against consecutive spoofing attacks i…