10 papers · 1 filter
Reducing Pilots in Channel Estimation with Predictive Foundation Models
Xingyu Zhou, Le Liang, Hao Ye +3
Accurate channel state information (CSI) acquisition is essential for modern wireless systems, which becomes increasingly difficult under large antenna arrays, strict pilot overhea…
Super-Resolution ISAC Receivers: An MCMC-Based Gridless Sparse Bayesian Learning Approach
Keying Zhu, Xingyu Zhou, Jie Yang +2
Integrated sensing and communication (ISAC) is crucial for low-altitude wireless networks (LAWNs), where the safety-critical demand for high-accuracy sensing creates a trade-off be…
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…
Robust MIMO Channel Estimation Using Energy-Based Generative Diffusion Models
Ziqi Diao, Xingyu Zhou, Le Liang +1
Channel estimation for massive multiple-input multiple-output (MIMO) systems is fundamentally constrained by excessive pilot overhead and high estimation latency. To overcome these…
Low-Complexity MIMO Channel Estimation with Latent Diffusion Models
Xiaotian Fan, Xingyu Zhou, Le Liang +1
Deep generative models offer a powerful alternative to conventional channel estimation by learning the complex prior distribution of wireless channels. Capitalizing on this potenti…
Next-Generation AI-Native Wireless Communications: MCMC-Based Receiver Architectures for Unified Processing
Xingyu Zhou, Le Liang, Jing Zhang +2
The multiple-input multiple-output (MIMO) receiver processing is a key technology for current and next-generation wireless communications. However, it faces significant challenges…
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…
A Wireless Foundation Model for Multi-Task Prediction
Yucheng Sheng, Jiacheng Wang, Xingyu Zhou +4
With the growing complexity and dynamics of the mobile communication networks, accurately predicting key system parameters, such as channel state information (CSI), user location,…
Unsupervised Learning-Based Joint Resource Allocation and Beamforming Design for RIS-Assisted MISO-OFDMA Systems
Yu Ma, Xingyu Zhou, Xiao Li +2
Reconfigurable intelligent surfaces (RIS) are key enablers for 6G wireless systems. This paper studies downlink transmission in an RIS-assisted MISO-OFDMA system, addressing resour…
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…