Search Results for author: Qinghua Guo

Found 10 papers, 1 papers with code

RIS-Assisted Joint Uplink Communication and Imaging: Phase Optimization and Bayesian Echo Decoupling

no code implementations10 Jan 2023 Shengyu Zhu, Zehua Yu, Qinghua Guo, Jinshan Ding, Qiang Cheng, Tie Jun Cui

Achieving integrated sensing and communication (ISAC) via uplink transmission is challenging due to the unknown waveform and the coupling of communication and sensing echoes.

Hyper-Parameter Auto-Tuning for Sparse Bayesian Learning

no code implementations9 Nov 2022 Dawei Gao, Qinghua Guo, Ming Jin, Guisheng Liao, Yonina C. Eldar

Choosing the values of hyper-parameters in sparse Bayesian learning (SBL) can significantly impact performance.

Variational Bayesian Inference Clustering Based Joint User Activity and Data Detection for Grant-Free Random Access in mMTC

no code implementations25 Oct 2022 Zhaoji Zhang, Qinghua Guo, Ying Li, Ming Jin, Chongwen Huang

Furthermore, in conjunction with the AMP algorithm, a variational Bayesian inference based clustering (VBIC) algorithm is developed to solve this clustering problem.

Bayesian Inference Scheduling

A Unitary Transform Based Generalized Approximate Message Passing

1 code implementation17 Oct 2022 Jiang Zhu, Xiangming Meng, Xupeng Lei, Qinghua Guo

We consider the problem of recovering an unknown signal ${\mathbf x}\in {\mathbb R}^n$ from general nonlinear measurements obtained through a generalized linear model (GLM), i. e., ${\mathbf y}= f\left({\mathbf A}{\mathbf x}+{\mathbf w}\right)$, where $f(\cdot)$ is a componentwise nonlinear function.

Signal Detection in MIMO Systems with Hardware Imperfections: Message Passing on Neural Networks

no code implementations8 Oct 2022 Dawei Gao, Qinghua Guo, Guisheng Liao, Yonina C. Eldar, Yonghui Li, Yanguang Yu, Branka Vucetic

Modelling the MIMO system with NN enables the design of NN architectures based on the signal flow of the MIMO system, minimizing the number of NN layers and parameters, which is crucial to achieving efficient training with limited pilot signals.

Bayesian Inference

Unitary Approximate Message Passing for Matrix Factorization

no code implementations31 Jul 2022 Zhengdao Yuan, Qinghua Guo, Yonina C. Eldar, Yonghui Li

We consider matrix factorization (MF) with certain constraints, which finds wide applications in various areas.

Compressive Sensing Dictionary Learning +1

Hformer: Hybrid CNN-Transformer for Fringe Order Prediction in Phase Unwrapping of Fringe Projection

no code implementations13 Dec 2021 Xinjun Zhu, Zhiqiang Han, Mengkai Yuan, Qinghua Guo, Hongyi Wang

Our work opens an alternative way to deep learning based phase unwrapping methods, which are dominated by CNN in fringe projection 3D measurement.

Unitary Approximate Message Passing for Sparse Bayesian Learning

no code implementations25 Jan 2021 Man Luo, Qinghua Guo, Ming Jin, Yonina C. Eldar, Defeng, Huang, Xiangming Meng

Sparse Bayesian learning (SBL) can be implemented with low complexity based on the approximate message passing (AMP) algorithm.

Variational Inference

Massive MIMO As an Extreme Learning Machine

no code implementations1 Jul 2020 Dawei Gao, Qinghua Guo, Yonina C. Eldar

This work shows that a massive multiple-input multiple-output (MIMO) system with low-resolution analog-to-digital converters (ADCs) forms a natural extreme learning machine (ELM).

Extreme Learning Machine-Based Receiver for MIMO LED Communications

no code implementations27 Feb 2019 Dawei Gao, Qinghua Guo

This work concerns receiver design for light-emitting diode (LED) multiple input multiple output (MIMO) communications where the LED nonlinearity can severely degrade the performance of communications.

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