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GNN-Assisted BiG-AMP: Joint Channel Estimation and Data Detection for Massive MIMO Receiver

IEEE Transactions on Wireless Communications 2025年

作者： Liu, Zishen Wu, Nan He, Dongxuan Yuan, Weijie Li, Yonghui Quek, Tony Q. S. School of Information and Electronics Beijing Institute of Technology Beijing100081 China School of System Design and Intelligent Manufacturing Shenzhen Key Laboratory of Robotics and Computer Vision Southern University of Science and Technology Shenzhen518055 China School of Electrical and Information Engineering The University of Sydney SydneyNSW2008 Australia Singapore University of Technology and Design 487372 Singapore Department of Electronic Engineering Kyung Hee University Yongin17104 Korea Republic of

In this paper, we develop a graph neural network (GNN)-assisted bilinear inference approach to enhance the receiver performance of the MIMO system through message passing-based joint channel estimation and data detection (JCD). Specifically, based on the bilinear generalized approximate message passing (BiG-AMP) framework and conditional correlation of signal, we propose a GNN-assisted BiG-AMP (GNN-BiGAMP) approach, which integrates a GNN module into the data-detection-loop to compensate the inaccurate marginal likelihood approximation. By leveraging the coupling between the channel and received symbols, a bilinear GNN-assisted BiG-AMP (BiGNN-BiGAMP) JCD receiver is further proposed. This method incorporates two GNNs with similar graph representation into the bilinear posterior estimation loops, which not only compensates for approximation errors but also alleviates performance loss due to premature variance convergence, thereby enhancing the receiver performance significantly. To fully exploit the supervised information from channel estimation and data detection, we propose a multitask learning based training scheme, which coordinates GNNs with different tasks in two loops. Simulation results show that our proposed GNN-assisted JCD receivers significantly outperform other JCD counterparts in terms of both channel estimation and data detection. © 2025 IEEE. All rights reserved.

关键词： Graph neural networks

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BAN: A Universal Paradigm for Cross-Scene Classification Under Noisy Annotations From RGB and Hyperspectral Remote Sensing Images

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IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Chen, Wentang Wen, Yibin Zheng, Juepeng Huang, Jianxi Fu, Haohuan Sun Yat-sen University School of Artificial Intelligence Zhuhai519082 China Zhejiang University State Key Laboratory of Fluid Power and Mechatronic Systems Engineering Research Center for Design Engineering and Digital Twin of Zhejiang Province School of Mechanical Engineering Robotics Institute Hangzhou310027 China Southwest Jiaotong University Faculty of Geosciences and Engineering Chengdu610032 China China Agricultural University College of Land Science and Technology Beijing100107 China Ministry of Agriculture and Rural Affairs Key Laboratory of Remote Sensing for Agri-Hazards Beijing100125 China Tsinghua University Tsinghua Shenzhen International Graduate School Shenzhen518071 China Tsinghua University Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System Science Beijing100190 China National Supercomputer Center in Shenzhen Shenzhen518071 China

While domain adaptation (DA) methods have made significant strides in remote sensing community, most current works assume that the source domain labels are accurate. However, limited emphasis has been placed on the scenario where source data are mislabeled with noisy annotations, which is more common in real applications and referred to as noisy DA (NDA). This article formulates remote sensing cross-scene classification on NDA scenarios and proposes a novel network called bilateral adaptation network (BAN), which consists of two parts: 1) forward learning (FL), which utilizes a model learning from the noisy source domain and transfers knowledge to target domain;and 2) backward learning (BL), which utilizes a dual model to acquire knowledge from the target domain and transfer it to source domain. We conduct two parts alternately and adopt a symmetrical Kullback-Leibler (KL) loss to align predictions of the model and its dual model in the same domain. This interactive strategy is able to explore bilateral relationships between domains, implicitly reducing label noise in the source domain. In addition, BAN could serve as a universal paradigm to not only improve the existing NDA methods but also enhance recent DA approaches. Comprehensive evaluations on three publicly available RGB-band remote sensing datasets and two hyperspectral datasets validate the superior effectiveness of our proposed BAN. BAN improves the average accuracy by 6.70%-15.70% on RGB datasets and overall accuracy (OA) by 1.36%-3.14% on hyperspectral datasets with flip-20% noise compared to other state-of-the-art DA and NDA approaches. Promising results indicate the potential of our approach in tackling more general and practical problems with noisy source domain. © 2025 IEEE.

关键词： Contrastive Learning

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Stabilization of zinc anode by trace organic corrosion inhibitors for long lifespan

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Chinese Chemical Letters 2025年第3期36卷 538-543页

作者： Wenfeng Shao Chuanlin Li Chenggang Wang Guangsen Du Shunshun Zhao Guangmeng Qu Yupeng Xing Tianshuo Guo Hongfei Li Xijin Xu School of Physics and Technology University of JinanJi’nan 250022China State Key Laboratory of Chemical Resource Engineering Beijing University of Chemical TechnologyBeijing 100029China School of Chemistry and Chemical Engineering Shandong UniversityJi’nan 250100China School of System Design and Intelligent Manufacturing Southern University of Science and TechnologyShenzhen 518000China

Aqueous zinc-ion batteries are highly favored for their enhanced safety and reduced ***,there exist challenges including zinc dendrite,hydrogen evolution,and surface corrosion to be *** electrolyte additives is a highly convenient approach to solving zinc anode-related *** by industrial corrosion protection,a trace amount of the corrosion inhibitor urotropine(URT)is used as an electrolyte additive to protect the zinc *** calculation and experimental analysis confirm the adsorption of URT molecules onto the surface of Zn,which inhibits hydrogen *** adsorption further leads to the formation of an inorganic-organic bilayer solid electrolyte interface(SEI)on the surface of the zinc anode,effectively protecting the Zn anode from corrosion,hydrogen evolution and zinc *** presence of SEI enables symmetrical Zn//Zn cells to exhibit a long cycling performance of 1750 h at 1mA/cm^(2)and an average coulombic efficiency of 99.0%at 1mA/cm^(2)in Zn//Cu *** being coupled with polyaniline(PANI),the Zn//PANI full battery displays excellent cycle stability and specific capacity.

关键词： Solid electrolyte interface Aqueous zinc-ion battery Corrosion inhibitors Electrolyte additive Zinc anode

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Mobility-Aware User Association and Computation Offloading in Ultra-Dense Networks

IEEE Transactions on Green Communications and Networking

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IEEE Transactions on Green Communications and Networking 2025年

作者： Qiu, Bin Feng, Ke Li, Xian Xiao, Hailin Zhang, Zhongshan Guilin University of Technology School of Computer Science and Engineering Guilin541004 China Guilin University of Technology Guangxi Key Laboratory of Embedded Technology and Intelligent System Guilin541004 China Guangxi Modern Polytechnic College Hechi530700 China Shenzhen University College of Electronics and Information Engineering Shenzhen518060 China Hubei University School of Computer Science and Information Engineering Wuhan430062 China Wuhan430062 China School of Cyberspace Science and Technology Guangdong519088 China

The integration of mobile edge computing (MEC) into ultra-dense network (UDN) has emerged as a promising solution for providing uninterrupted task offloading services to computation-demanding mobile devices (MDs), leveraging densely deployed MEC servers. However, the mobility of MDs can significantly affect the computation offloading decision and system performance in UDN-MEC. To address this issue, we develop a joint optimization algorithm for mobility-aware user association and computation offloading to minimizize the total system cost, including delay and energy consumption in UDN-MEC. Specifically, a polynomial fitting algorithm based on an extended Kalman filter (PFA-EKF) is designed to predict the nonlinear moving trajectories of the MDs. Furthermore, we present a mobility-aware user-association rule based on a breadth-first search (UAR-BFS) that can realize balanced matching offloading in the overlapping coverage area of densely deployed small base stations. Accordingly, we propose an improved deep deterministic policy gradient-based greedy algorithm (IDDPG-GA) to address the joint optimization problem of multiuser dynamic offloading and resource allocation, in which an intelligently adjusted bias factor is proposed to enhance collaborative behavior among MDs. Extensive numerical results and comparisons demonstrate the promising performance improvements of the proposed scheme compared with existing benchmark schemes in various scenarios. © 2025 IEEE.

关键词： Computation offloading

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A Memetic Algorithm Based Feature Weighting for Metabolomics Data Classification

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Chinese Journal of Electronics 2014年第4期23卷 706-711页

作者： ZHOU Jiarui ZHU Zexuan JI Zhen College of Biomedical Engineering and Instrument Science Zhejiang University Shenzhen City Key Laboratory of Embedded System Design College of Computer Science and Software EngineeringShenzhen University

A metaheuristic chain based memetic algorithm namely MCMA is proposed for the classification of metabolomics data. MCMA regards both global evolution and local search as equivalent elemental metaheuristics,and searches with a chain of metaheuristics performed alternatively on the target problem. A hidden Markov model based scheduling mechanism is employed in MCMA for the selection of metaheuristics. By using MCMA for optimizing the linkage weight vector, a feature weighting algorithm for metabolomics data is formed to identify relevant metabolite features and reveal their exact relationships with the given physiological states. An extreme learning machine based classifier is utilized in predicting the physiological states according to the weighted metabolite features. Experimental results on real metabolomics data of clinical liver transplantation demonstrate that the proposed feature weighting and classification method obtains better performance than the other compared algorithms.

关键词： Metabolomics Feature weighting Memetic algorithm

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Computer-aided Optimization of a 5.8 GHz ETC Receiver Front-end design using Memetic Algorithm

Computer-aided Optimization of a 5.8 GHz ETC Receiver Front-...

引用

International Conference on Mechatronics and Applied Mechanics (ICMAM 2011)

作者： Lai, Jiang Hang, Yu Yan, Li Yan, Yin Zhan, Li College of Computer Science and Software Engineering Shenzhen University Shenzhen City Key Laboratory of Embedded System Design Shenzhen

ISBN: (纸本)9783037853801

systematic level design and optimization of a Radio Frequency (RF) receiver is a multidimensional problem and it is usually an arduous and experience-based work because of the trade-off between various system parameters. In the mean while, co-operated with Genetic Algorithm (GA) and local search, Memetic Algorithm (MA) gradually becomes popular to solve multidimensional optimization problems, and it can be an efficient method for computer-aided design of RF receivers. In this paper, the MA method was adopted to aid the design of a 5.8 GHz RF receiver front-end. The transfer function for the signal-to-noise ratio at the front-end output (SNRout) was first derived based on the gain, noise figure and inter-modulation product of each individual circuit component, and the transfer function was then used as the required fitness function for the MA method. The efficacy of the proposed method was validated by ADS simulations.

关键词： Computer-aided design RE front-end fitness function MA ADS simulation

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A Novel Wideband CPW-Fed 5.8GHz RFID Tag Antenna

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电子学报(英文版) 2012年第2期21卷 202-208页

作者： LI Huihui MOU Xuanqin JI Zhen YU Hang LI Yan Institute of Image Processing and Pattern Recognition Xi'an Jiaotong University Xi'an 710049 China College of Computer Science and Software Engineering Shenzhen University Shenzhen 518060 China Shenzhen Key Laboratory of Embedded System Design Shenzhen 518060 China

A novel wideband 5.8GHz CPW-fed an- tenna is presented for Radio frequency identification (RFID) tag. Four U-shaped and four L-shaped branches are used as additional resonators to achieve wideband operation. The proposed antenna was analyzed numeri- cally using the Method of moment (MOM) and the Fi- nite element method (FEM). With the antenna size lim- ited to 30 × 30mm2, the ?10dB bandwidth obtained by MOM is 3.235GHz (5.765～9GHz) and the ?9.5dB band- width obtained by FEM is 2.74GHz (5.32～8.06GHz), cor- responding to 55.7% and 47.2% of the center frequency 5.8GHz respectively. Moreover, the simulated results show that the proposed antenna has gain of more than 4.8dBi and the radiation pattern is nearly omnidirectional in the H-plane. The measured ?10dB bandwidth is 2.68GHz (5.63GHz～8.31GHz), 46.2% of the 5.8GHz frequency. Fur- thermore, there are three measured resonant frequencies at 1.34GHz, 3.23GHz and 5.8GHz with lower than ?10dB return loss respectively. The measurement result achieves a wideband RFID tag antenna performance and is in good agreement with the calculated results.

关键词： RFID标签天线尺寸共面波导宽带无线电频率识别有限元分析网络连接数值分析

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Memetic ant colony optimization for band selection of hyperspectral imagery classification

Memetic ant colony optimization for band selection of hypers...

引用

Chinese Conference on Pattern Recognition

作者： Zhu, Zexuan Ji, Zhen Jia, Sen Shenzhen City Key Laboratory of Embedded System Design College of Computer Science and Software Engineering Shenzhen University Shenzhen 518060 China

ISBN: (纸本)9781424472109

This paper proposes a novel memetic ant colony optimization (MACO) algorithm for band selection on hyperspectral imagery classification. The method incorporates filter method based local search and ant colony optimization (ACO) based global search to take advantage of both. Particularly, the local search fine-tunes the paths explored by the ants by adding the relevant bands and eliminating irrelevant/redundant ones. A comparison study to the filters methods (including Gain Ratio, ReliefF, AP based method, and FCBF) and the counterpart wrapper ACO feature selection on four hyperspectral imagery datasets demonstrates that MACO is capable of attaining competitive or better classification accuracy with fewer selected bands. The empirical results suggest that MACO is effective and efficient in identifying relevant bands while eliminating irrelevant/redundant ones. ©2010 IEEE.

关键词： Ant colony optimization

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An offset-free 10 MHz limiting amplifier designed for a 5.8 GHz ETC receiver

An offset-free 10 MHz limiting amplifier designed for a 5.8 ...

引用

6th International ICST Conference on Wireless Internet, WICON 2011

作者： Jiang, Lai Yu, Hang Wei, Rongchen Li, Yan Lin, Shengyue Ji, Zhen Shenzhen City Key Laboratory of Embedded System Design College of Computer Science and Software Engineering Shenzhen University 518060 Shenzhen China

ISBN: (纸本)9783642304927

Electronic tolling collection (ETC) system will be largely adopted in the next generation of Chinese highway network, and its operating frequency is specified to be 5.8 GHz. A limiting amplifier designed for the 5.8 GHz receiver of the ETC system is presented in this work. AC-coupled gain stage was realized to avoid additional offset cancellation mechanism. The trade-off between the small signal gain, number of stages, gain-bandwidth product, and power dissipation was studied by systematic analysis. Implemented using a standard CMOS 0.18 μm process, the simulation results show that the limiting amplifier achieves overall small signal gain of 81 dB, with 20 MHz bandwidth. © 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.

关键词： Bandwidth

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A low-IF 2.4 GHz integrated RF receiver for Bluetooth applications

A low-IF 2.4 GHz integrated RF receiver for Bluetooth applic...

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3rd International Conference on Intelligent Structure and Vibration Control, ISVC 2013

作者： Jiang, Lai Liu, Shao Hua Yu, Hang Li, Yan Shenzhen City Key Laboratory of Embedded System Design College of Computer Science and Software Engineering Shenzhen University Shenzhen Guangdong China

ISBN: (纸本)9783037857236

In this paper, a low-IF 2.4 GHz integrated RF receiver for Bluetooth is presented. designed in a 0.18 μm CMOS technology, the receiver consists of LNA, mixer, complex band-pass filter, and GFSK demodulator. A received signal strength indicator is also employed in the receiver to auto adjust the receiver gain. In this paper, the structures of the major modules were analyzed, and the simulation results are presented and discussed. © (2013) Trans Tech Publications, Switzerland.

关键词： Bluetooth

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