11 papers
Large-System Analysis of Sparse Bayesian Learning
Fangqing Xiao, Dirk T. M. Slock
Sparse Bayesian learning is widely used for sparse linear inverse problems, yet its large-system stationary behavior remains poorly understood because all variance hyperparameters…
Single-Base-Station Indoor Localization via Super-Resolved Relative Power Delay Profiles
Fangqing Xiao, Dirk T. M. Slock
Indoor multipath is shaped by surrounding reflectors, scatterers, and blockages, so a relative power-delay profile (PDP) can serve as a location fingerprint without an identifiable…
Gaussian-Process Dynamics of Diagonal Expectation Propagation under Variance-Profile Gaussian Measurements
Fangqing Xiao, Dirk T. M. Slock
State-evolution analyses of approximate-message-passing and expectation-propagation-type algorithms rely on an effective-channel principle: after a suitable Onsager, orthogonal, or…
Performance Benchmarks for Line Spectral Estimation: Ordered Ziv-Zakai Characterization and Plug-In Amplitude Error Analysis
Fangqing Xiao, Dirk T. M. Slock
Line spectral estimation (LSE) involves estimating both spectral frequencies and their associated complex amplitudes. Existing Fisher-information-based benchmarks are local and the…
Avoiding Non-Integrable Beliefs in Expectation Propagation
Zilu Zhao, Jichao Chen, Dirk Slock
Expectation Propagation (EP) is a widely used iterative message-passing algorithm that decomposes a global inference problem into multiple local ones. It approximates marginal dist…
Approximating Univariate Factored Distributions via Message-Passing Algorithms
Zilu Zhao, Dirk Slock
Gaussian Mixture Models (GMMs) commonly arise in communication systems, particularly in bilinear joint estimation and detection problems. Although the product of GMMs is still a GM…
Expectations in Expectation Propagation
Zilu Zhao, Fangqing Xiao, Dirk Slock
Expectation Propagation (EP) is a widely used message-passing algorithm that decomposes a global inference problem into multiple local ones. It approximates marginal distributions…
Distributed Iterative ML and Message Passing for Grant-Free Cell-Free Massive MIMO Systems
Zilu Zhao, Christian Forsch, Laura Cottatellucci +1
Cell-Free (CF) Massive Multiple-Input Multiple-Output (MaMIMO) is considered one of the leading candidates for enabling next-generation wireless communication. With the growing int…
Bayesian Learning for Pilot Decontamination in Cell-Free Massive MIMO
Christian Forsch, Zilu Zhao, Dirk Slock +1
Pilot contamination (PC) arises when the pilot sequences assigned to user equipments (UEs) are not mutually orthogonal, eventually due to their reuse. In this work, we propose a no…
Multipath Component Power Delay Profile Based Joint Range and Doppler Estimation for AFDM-ISAC Systems
Fangqing Xiao, Zunqi Li, Dirk Slock
Integrated Sensing and Communication (ISAC) systems combine sensing and communication functionalities within a unified framework, enhancing spectral efficiency and reducing costs b…
Decentralized Expectation Propagation for Semi-Blind Channel Estimation in Cell-Free Networks
Zilu Zhao, Dirk Slock
This paper serves as a correction to the conference version. In this work, we explore uplink communication in cell-free (CF) massive multiple-input multiple-output (MaMIMO) systems…