5 papers
Low-Overhead Receiver Design for Data-Dependent Superimposed Training via Deep Learning
Xinjie Li, Xingyu Zhou, Jing Zhang +3
Superimposed pilot (SIP) transmission improves spectral efficiency by eliminating the dedicated pilot overhead required in orthogonal pilot (OP)-based schemes. However, SIP suffers…
Conditional Diffusion Model-Enabled Scenario-Specific Neural Receivers for Superimposed Pilot Schemes
Xingyu Zhou, Le Liang, Xinjie Li +4
Neural receivers have demonstrated strong performance in wireless communication systems. However, their effectiveness typically depends on access to large-scale, scenario-specific…
Learning-Aided Iterative Receiver for Superimposed Pilots: Design and Experimental Evaluation
Xinjie Li, Xingyu Zhou, Yixiao Cao +4
The superimposed pilot transmission scheme offers substantial potential for improving spectral efficiency in MIMO-OFDM systems, but it presents significant challenges for receiver…
Partial-Wetting Phenomena in Active Matter
Jing Zhang, Zhixin Liu, Shengda Zhao +5
Abundant interfacial phenomena in nature, such as water droplets on lotus leaves and water transport in plant vessels, originate from partial-wetting phenomena, which can be well d…
Joint Channel Estimation and Signal Detection for MIMO-OFDM: A Novel Data-Aided Approach with Reduced Computational Overhead
Xinjie Li, Jing Zhang, Xingyu Zhou +2
The acquisition of channel state information (CSI) is essential in MIMO-OFDM communication systems. Data-aided enhanced receivers, by incorporating domain knowledge, effectively mi…