6 papers
Selective Depthwise Separable Convolution for Lightweight Joint Source-Channel Coding in Wireless Image Transmission
Ming Ye, Kui Cai, Cunhua Pan +3
Depthwise separable convolutional (DSConv) layers have been successfully applied to deep learning (DL)-based joint source-channel coding (JSCC) schemes to reduce computational comp…
Near-Field Wideband Channel Estimation for XL-MIMO Systems via Denoising Diffusion Model
Qingxia Feng, Yin Fang, Meng Hua +4
Extremely large-scale multiple-input multiple-output (XL-MIMO) is a key enabling technology for sixth-generation (6G) communication systems. Nevertheless, the increase in array ape…
Adaptive Structured Sparse Bayesian Learning for Near-Field Non-Stationary Channel Estimation in XL-MIMO Systems
Qingxia Feng, Pan Fang, Meng Hua +3
Extremely large-scale multiple-input multiple-output (XL-MIMO) is a key enabler for sixth-generation (6G) communications. However, near-field channel estimation is particularly cha…
JSSAnet: Theory-Guided Subchannel Partitioning and Joint Spatial Attention for Near-Field Channel Estimation
Zhiming Zhu, Shu Xu, Chunguo Li +2
The deployment of extremely large-scale antenna array (ELAA) in sixth-generation (6G) communication systems introduces unique challenges for efficient near-field channel estimation…
U-Net-Based Generative Joint Source-Channel Coding for Wireless Image Transmission
Ming Ye, Kui Cai, Cunhua Pan +3
Deep learning (DL)-based joint source-channel coding (JSCC) methods have achieved remarkable success in wireless image transmission. However, these methods either focus on conventi…
A Multi-Scale Spatial Attention Network for Near-field MIMO Channel Estimation
Zhiming Zhu, Shu Xu, Jiexin Zhang +3
The deployment of extremely large-scale array (ELAA) brings higher spectral efficiency and spatial degree of freedom, but triggers issues on near-field channel estimation. Existing…