3 papers
eess.SP2026
ConsisFormer: Compute-Efficient Transformer for Wireless Foundation Models Based on Channel Consistency
Yuwei Wang, Li Sun, Tingting Yang +4
Wireless foundation models (WFMs) have recently emerged as a promising paradigm for AI-native 6G networks, enabling universal channel representations adaptable to diverse communica…
eess.SP2026
SpikeWFM: Spiking-Aided Wireless Foundation Model for Robust Channel Prediction
Liwen Jing, Yisha Lu, Tingting Yang +5
This paper proposes SpikeWFM, a novel hybrid architecture that integrates spiking neural networks (SNNs) with conventional artificial neural network (ANN)-based transformers for wi…
eess.SP2025
Unfolded Deep Graph Learning for Networked Over-the-Air Computation
Xiao Tang, Huirong Xiao, Chao Shen +4
Over-the-air computation (AirComp) has emerged as a promising technology that enables simultaneous transmission and computation through wireless channels. In this paper, we investi…