8 papers
Proximal-Based Generative Modeling for Bayesian Inverse Problems
Boyang Zhang, Zhiguo Wang, Ya-Feng Liu
Score-based diffusion models demonstrate superior performance in generative tasks but encounter fundamental bottlenecks in inverse problems due to the analytical intractability of…
CP-OFDM Achieves Lower Ranging CRB Than Frequency-Spread Waveforms in the Large-Sample Regime
Fan Liu, Yifeng Xiong, Ya-Feng Liu +3
The inherent randomness of communication symbols creates a fundamental tension in Integrated Sensing and Communications (ISAC). On the one hand, they enable data transmission while…
OFDM Waveform Optimization for Bistatic Integrated Sensing and Communications
Ruolin Du, Zhiqiang Wei, Zai Yang +3
This paper investigates the design of orthogonal frequency-division multiplexing (OFDM) waveforms for bistatic integrated sensing and communication (ISAC) systems. In the considere…
Optimal Low-Dimensional Structures of ISAC Beamforming: Theory and Efficient Algorithms
Xiaotong Zhao, Mian Li, Ya-Feng Liu +2
Transmit beamforming design is a fundamental problem in integrated sensing and communication (ISAC) systems. Numerous methods have been proposed to jointly optimize key performance…
Duality-Based Fixed Point Iteration Algorithm for Beamforming Design in ISAC Systems
Xilai Fan, Ya-Feng Liu
In this paper, we investigate the beamforming design problem in an integrated sensing and communication (ISAC) system, where a multi-antenna base station simultaneously serves mult…
A Gradient Guided Diffusion Framework for Chance Constrained Programming
Boyang Zhang, Zhiguo Wang, Ya-Feng Liu
Chance constrained programming (CCP) is a powerful framework for addressing optimization problems under uncertainty. In this paper, we introduce a novel Gradient-Guided Diffusion-b…