5 papers · 1 filter
Pruned Convolutional Attention Network Based Wideband Spectrum Sensing with Sub-Nyquist Sampling
Peihao Dong, Jibin Jia, Shen Gao +2
Wideband spectrum sensing (WSS) is critical for orchestrating multitudinous wireless transmissions via spectrum sharing, but may incur excessive costs of hardware, power and comput…
Mixed Attention Transformer Enhanced Channel Estimation for Extremely Large-Scale MIMO Systems
Shuang shuang Li, Peihao Dong
Extremely large-scale massive multiple-input multiple-output (XL-MIMO) is one of the key technologies for next-generation wireless communication systems. However, acquiring the acc…
Information Importance-Aware Defense against Adversarial Attack for Automatic Modulation Classification:An XAI-Based Approach
Jingchun Wang, Peihao Dong, Fuhui Zhou +1
Deep learning (DL) has significantly improved automatic modulation classification (AMC) by leveraging neural networks as the feature extractor.However, as the DL-based AMC becomes…
Collaborative Automatic Modulation Classification via Deep Edge Inference for Hierarchical Cognitive Radio Networks
Chaowei He, Peihao Dong, Fuhui Zhou +1
In hierarchical cognitive radio networks, edge or cloud servers utilize the data collected by edge devices for modulation classification, which, however, is faced with problems of…
Federated Transfer Learning Based Cooperative Wideband Spectrum Sensing with Model Pruning
Jibin Jia, Peihao Dong, Fuhui Zhou +1
For ultra-wideband and high-rate wireless communication systems, wideband spectrum sensing (WSS) is critical, since it empowers secondary users (SUs) to capture the spectrum holes…