6 papers
Sensing-Aided Channel Estimation for Near-Field MIMO ISAC Systems via Cross-Attention Transformer
Peihao Dong, Renbin Li, Shen Gao +4
Near-field integrated sensing and communication (ISAC) can deliver the high spatial resolution and transmission capability with the shared spectrum and hardware. Due to the partial…
LLM4XCE: Large Language Models for Extremely Large-Scale Massive MIMO Channel Estimation
Renbin Li, Shuangshuang Li, Peihao Dong
Extremely large-scale massive multiple-input multiple-output (XL-MIMO) is a key enabler for sixth-generation (6G) networks, offering massive spatial degrees of freedom. Despite the…
Explainable Deep Learning Based Adversarial Defense for Automatic Modulation Classification
Peihao Dong, Jingchun Wang, Shen Gao +2
Deep learning (DL) has been widely applied to enhance automatic modulation classification (AMC). However, the elaborate AMC neural networks are susceptible to various adversarial a…
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…