6 papers
A Gaussian Perspective for Distributional Discrepancy in Generative Diffusion Models
Qiang Sun, H. Vincent Poor, Wenyi Zhang
This paper introduces an analytical approach to quantifying and optimizing the distributional discrepancy in generative diffusion models. For a multivariate Gaussian source, we exp…
Neuromorphic Wireless Split Computing with Resonate-and-Fire Neurons
Dengyu Wu, Jiechen Chen, H. Vincent Poor +2
Neuromorphic computing offers an energy-efficient alternative to conventional deep learning accelerators, particularly for real-time processing of time-series data. However, many e…
FDD CSI Feedback under Finite Downlink Training: A Rate-Distortion Perspective
Shuao Chen, Junyuan Gao, Yuxuan Shi +4
This paper establishes the theoretical limits of channel state information (CSI) feedback in frequency-division duplexing (FDD) multi-antenna orthogonal frequency-division multiple…
Joint Lossy Compression for a Vector Gaussian Source under Individual Distortion Criteria
Shuao Chen, Junyuan Gao, Yuxuan Shi +4
This paper investigates the joint compression problem of a vector Gaussian source, where an individual distortion constraint is imposed on each source component. It is known that t…
Finite-Blocklength Information Theory
Junyuan Gao, Shuao Chen, Yongpeng Wu +4
Traditional asymptotic information-theoretic studies of the fundamental limits of wireless communication systems primarily rely on some ideal assumptions, such as infinite blocklen…
Decision Transformers for RIS-Assisted Systems with Diffusion Model-Based Channel Acquisition
Jie Zhang, Yiyang Ni, Jun Li +6
Reconfigurable intelligent surfaces (RISs) have been recognized as a revolutionary technology for future wireless networks. However, RIS-assisted communications have to continuousl…