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An Efficient Direct Downlink Sensing Method Using 5G NR SSB Signals in Perceptive Mobile networks

IEEE Internet of Things Journal 2025年第11期12卷 15360-15369页

作者： Li, Hang Xiang, Yang Guo, Qinghua Liu, Lizhe Huang, Xiaojing Cheng, Zhiqun Pang, Yashan Hangzhou Dianzi University School of Electronics and Information Hangzhou310018 China Academy of Network and Communications of CETC National Key Laboratory of Advanced Communication Networks Hebei Shijiazhuang050081 China University of Wollongong School of Electrical Computer and Telecommunications Engineering WollongongNSW2522 Australia University of Technology Sydney Global Big Data Technologies Centre UltimoNSW2007 Australia

In perceptive mobile networks (PMNs), using 5G New Radio (NR) signals for direct sensing poses a significant challenge to practical implementation due to the high computational complexity involved in estimating sensing parameters. In this paper, an efficient sensing method is proposed to incorporate both downlink active sensing and passive sensing to estimate multiple sensing parameters, including delays, angle of arrival (AoA), angle of departure (AoD) and Doppler. In particular, it exploits the synchronization signal blocks (SSBs) to facilitate sensing with multiple remote radio units (RRUs). To reduce the computational complexity of direct sensing, a sparse model is developed to decouple multiple sensing parameter estimation, enabling efficient sensing method design. Then, leveraging unitary approximate message passing (UAMP) and sparse Bayesian learning (SBL), we propose an efficient method to achieve parameter estimation and association with corresponding RRUs. This method is further extended to general scenarios involving multiple path components with the same delay. Extensive simulations demonstrate the effectiveness of the proposed method, showing that it outperforms existing ones in terms of sensing accuracy and complexity. © 2014 IEEE.

关键词： 5G mobile communication systems

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Color Correction Meets Cross-Spectral Refinement: A Distribution-Aware Diffusion for Underwater Image Restoration

arXiv

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arXiv 2025年

作者： Chang, Laibin Wang, Yunke Du, Bo Xu, Chang The School of Computer Science Institute of Artificial Intelligence National Engineering Research Center for Multimedia Software Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan University China The School of Computer Science The University of Sydney Australia

Underwater imaging often suffers from significant visual degradation, which limits its suitability for subsequent applications. While recent underwater image enhancement (UIE) methods rely on the current advances in deep neural network architecture designs, there is still considerable room for improvement in terms of cross-scene robustness and computational efficiency. Diffusion models have shown great success in image generation, prompting us to consider their application to UIE tasks. However, directly applying them to UIE tasks will pose two challenges, i.e., high computational budget and color unbalanced perturbations. To tackle these issues, we propose DiffColor, a distribution-aware diffusion and cross-spectral refinement model for efficient UIE. Instead of diffusing in the raw pixel space, we transfer the image into the wavelet domain to obtain such low-frequency and high-frequency spectra, it inherently reduces the image spatial dimensions by half after each transformation. Unlike single-noise image restoration tasks, underwater imaging exhibits unbalanced channel distributions due to the selective absorption of light by water. To address this, we design the Global Color Correction (GCC) module to handle the diverse color shifts, thereby avoiding potential global degradation disturbances during the denoising process. For the sacrificed image details caused by underwater scattering, we further present the Cross-Spectral Detail Refinement (CSDR) to enhance the high-frequency details, which are integrated with the low-frequency signal as input conditions for guiding the diffusion. This way not only ensures the high-fidelity of sampled content but also compensates for the sacrificed details. Comprehensive experiments demonstrate the superior performance of DiffColor over state-of-the-art methods in both quantitative and qualitative evaluations. © 2025, CC BY.

关键词： Budget control

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An Enhancing Stability Control Strategy of VSG-Based Power Source Under PWM Rectifier Load

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IEEE Transactions on Consumer Electronics 2025年

作者： Li, Gaoxiang Liu, Bowen Song, Wenhao Jining, Chen Liu, Xiao Guangxi University Guangxi Key Laboratory of Power System Optimization and Energy Technology School of Electrical Engineering Nanning530004 China Guangxi Zhuang Autonomous Region Information Center Guangxi Key Laboratory of Digital Infrastructure Nanning530200 China Guangxi University Guangxi Key Laboratory of Multimedia Communications and Network Technology Guangxi Colleges and Universities Key Laboratory of Multimedia Communications and Information Processing School of Computer Electronics and Information Nanning530004 China

Under PWM rectifier load, the power source based on virtual synchronous generator (VSG) is prone to cause mid-frequency oscillation. Firstly, the system oscillation mechanism and characteristic of the VSG-based power source are analyzed based on impedance method. Due to the negative resistance and capacitive characteristic in the middle frequency range, the PWM rectifier load is prone to interact with the VSG-based power source, which can lead to impedance resonance. Secondly, to improve the stability of the VSG-based power source under the PWM rectifier load, a voltage differentiation feedforward control is proposed. In addition, since the mid-frequency impedance magnitude decrease obviously, the improved VSG-based power source is closer to the ideal voltage source, which can automatically suppress the middle harmonics induced by uncontrollable rectifier load. Finally, the proposed control and the corresponding theoretical analysis are verified by simulations and experiments. © 1975-2011 IEEE.

关键词： Synchronous generators

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SMDPG: Identifying Metabolite-Disease Associations via Optimized Negative Sampling and Sparse Graph Convolutional network

IEEE Transactions on Computational Biology and Bioinformatic...

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IEEE Transactions on Computational Biology and Bioinformatics 2025年第2期22卷 672-683页

作者： Yiran Huang Qiulong Pu Wei Lan Cuiyu Huang Cheng Zhong School of Computer Electronics and Information Guangxi University Nanning China Guangxi Universities Key Laboratory of Parallel and Distributed Computing and Guangxi Key Laboratory of Multimedia Communications and Network Technology Guangxi University Nanning China College of Chemistry Nankai University Tianjin China

Identifying disease-associated metabolites could provide critical clues for the diagnosis and treatment of diseases. Although computational approaches have been proposed to predict disease-associated metabolites by training models using positive and negative samples, few efforts have paid attention to optimize the reliability of negative samples, which could possibly improve the prediction accuracy of model. In this work, we propose a novel method called SMDPG to leverage optimized negative sampling and sparse graph convolutional network to predict metabolite-disease associations. In SMDPG, we first build a metabolite-disease bipartite graph based on less similar metabolites and diseases and propose a negative sampling method to select reliable negative metabolite-disease samples from the bipartite graph to reduce the effect of noisy samples. Then a homogeneous metabolite-disease pair graph is constructed based on the selected negative samples and known metabolite-disease associations. Further, an edge sparseness operation is designed to simplify the connection of the homogeneous graph. Finally, the simplified homogeneous graph is fed into the graph convolutional network to predict metabolite-disease associations. Experimental results show that SMDPG can more accurately predicts metabolite-disease associations as compared to the existing methods. Moreover, the study case demonstrates that SMDPG is an effective framework for identifying potential metabolite-disease associations.

关键词： Diseases Feature extraction Semantics Databases Reliability Graph convolutional networks Training Sparse matrices Predictive models Bipartite graph

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Extremely Large-scale Array Systems: Near-Field Codebook Design and Performance Analysis

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IEEE Transactions on communications 2025年

作者： Zheng, Feng Yu, Hongkang Wang, Chenchen Sun, Luyang Wu, Qingqing Chen, Yijian Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing100876 China State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen518055 China Shanghai Jiao Tong University Department of Electronic Engineering Shanghai200240 China

Extremely Large-scale Array (ELAA) promises to deliver ultra-high data rates with increased antenna elements. However, increasing antenna elements leads to a wider realm of near-field, which challenges the traditional design of codebooks. In this paper, we propose novel near-field codebook schemes based on the fitting formula of codewords' quantization performance. First, we analyze the quantization performance properties of uniform linear array (ULA) and uniform planar array (UPA) codewords. Our findings reveal an intriguing property: the correlation formula for ULA codewords can be represented by the elliptic formula, while the correlation formula for UPA codewords can be approximated using the ellipsoid formula. Building on this insight, we propose a ULA uniform codebook that maximizes the minimum correlation based on the derived formula. Moreover, we introduce a ULA dislocation codebook to further reduce quantization overhead. Continuing our exploration, we propose UPA uniform and dislocation codebook schemes. Our investigation demonstrates that oversampling in the angular domain offers distinct advantages, achieving heightened accuracy while minimizing overhead in quantifying near-field channels. Numerical results demonstrate the appealing advantages of the proposed codebook over existing methods in decreasing quantization overhead and increasing quantization accuracy. © 1972-2012 IEEE.

关键词： communication channels (information theory)

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Channel Estimation for High-speed Mobile MIMO-OFDM Systems Using Deep Learning 25

Channel Estimation for High-speed Mobile MIMO-OFDM Systems U...

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Proceedings of the 2025 3rd International Conference on communication networks and Machine Learning

作者： Xingxing Ai Ao Deng Zeng Li Shaochuan Wu State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen Guangdong China School of Electronics and Information Engineering Harbin Institute of Technology Harbin Heilongjiang China

ISBN: (纸本)9798400713231

In high-speed mobile channel environment characterized by fast time-varying and Doppler frequency shifts, interference between subcarriers becomes increasingly prominent. In this case, channel estimation in multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system faces significant challenges, including low time correlation, high interpolation errors, and Doppler frequency shifts. To address these issues, we propose a channel estimation framework that integrates attention mechanisms with an enhanced Super-Resolution Convolutional Neural network (SRCNN). The whole network adopts the network structure of the autoencoder, embeds the channel attention module with powerful channel dynamic feature extraction ability at the encoder end, and reweights the channel features of the least squares (LS) estimation input with the learned attention map in turn, which can fully extract the features of the original data. Subsequently, the improved SRCNN reconstructs and refines the features of the dimensionally reduced data, exploiting its strong reconstruction and denoising capabilities to recover high-resolution characteristics. Finally, the decoder outputs the fully estimated channel matrix. Simulation results demonstrate that the proposed channel estimation method significantly outperforms the traditional least squares algorithm while exhibiting computational complexity slightly higher than LS but lower than the linear minimum mean square error (LMMSE) algorithm. Notably, as the number of user-transmitted symbols and subcarriers increases, the deep learning-based method shows greater advantages over the LMMSE algorithm, greatly reducing practical computational costs.

关键词： Channel estimation

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A Dual-Polarized Fixed-Frequency Beam-Scanning Leaky-Wave Antenna for 5G Millimeter-Wave Applications

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IEEE Transactions on Antennas and Propagation 2025年

作者： Wei, Bang Li, Zheng Xiong, Zhe Zhao, Yi Chen, Meie Wang, Junhong Beijing Jiaotong University Key Laboratory of All Optical Network and Advanced Telecommunication Network Ministry of Education Institute of Lightwave Technology Beijing100044 China WuHan Maritime Communication Research Institute China

In this paper, a dual-polarized (DP) fixed-frequency beam-scanning leaky-wave antenna (LWA) is presented. Operating from 24.5 to 27.5 GHz, the LWA consists of a vertically polarized (VP) patch array, a horizontally polarized (HP) printed dipole array, and a dual-channel gap waveguide (GW) that provides traveling-wave excitation. The VP patch array, located at the center of the antenna aperture, contains 80 slot-excited patches. The HP dipole array is divided into two subarrays distributed on both sides of the antenna aperture and is excited by slot-coupled microstrip lines. The VP and HP arrays are independent, enabling simultaneous control of both polarization beams. Due to the low profile of the printed dipole, the radiation aperture of the antenna can be fully utilized, providing the ability to expand in two dimensions. To achieve fixed-frequency beam scanning, each antenna unit has a 1-bit amplitude modulation capability, realized by electrically controlling the PIN diode. A dual-channel GW capable of transmitting both TE01 and TE10 modes is designed, and the stacked architecture makes it suitable for a compact DP antenna. Holographic method is employed to realize the beam scanning. Simulated and measured results verify that the proposed antenna can achieve fixed-frequency, wide-angle, and quasi-continuous beam scanning. © 1963-2012 IEEE.

关键词： Scanning antennas

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HAPG-SAQAM: Human Auditory Perception Guided Spatial Audio Quality Assessment Metric

HAPG-SAQAM: Human Auditory Perception Guided Spatial Audio Q...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Yuanming Zheng Jiaxuan Yao Xiangyu Deng Yuhong Yang Ruiqi Liao Weiping Tu Cedar Lin National Engineering Research Center for Multimedia Software School of Computer Science Wuhan University Wuhan China Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan China Guangdong OPPO Mobile Telecommunications Corp. China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Spatial audio quality evaluation is essential for applications like virtual and augmented reality, where accurate sound reproduction enhances user immersion. While subjective listening tests are the gold standard, they are costly and time-consuming. To address this, we propose HAPG-SAQAM, an objective metric for assessing timbre quality, spatial quality, and overall quality of binaural audio, guided by human auditory perception. Our contributions include: (1) the Multi-scale Auditory Guided Feature Extraction (MAGFE) module, incorporating gammatone frequency cepstral coefficients for better alignment with human perception; (2) Perceptual Weighted Loss (PWL), optimizing the weighting of timbre quality (TQ) and spatial quality (SQ) loss based on subjective test data; and (3) data augmentation techniques to enhance robustness by amplifying perceptual distortions. Experimental results show HAPG-SAQAM improves correlation with subjective scores by 10%, with ablation studies confirming the contributions of its components to enhanced spatial and overall audio quality.

关键词： Measurement Accuracy Spatial audio Performance gain Feature extraction Robustness Quality assessment Timbre Speech processing Optimization

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A base station microgrid traffic prediction method based on IOOA-CNN-BiLSTM 3

A base station microgrid traffic prediction method based on ...

引用

3rd International Conference on Smart Energy and Electrical Engineering, SEEE 2024

作者： Yan, Ming Guo, Wenhao Xian, Shixuan Qin, Tuanfa School of Electrical Engineering Guangxi University Nanning530004 China School of Computer Electronics and Information Guangxi University Nanning530004 China Guangxi Key Laboratory of Multimedia Communications and Network Technology Guangxi University Nanning530004 China

The rapid advancement of 5G technology has raised significant concerns regarding the energy consumption of base stations for mobile network operators. Integrating traditional base station power supply systems with microgrids to maximize the utilization of renewable energy has demonstrated considerable potential in addressing the energy consumption challenges faced by base stations. However, the inherent randomness of communication traffic loads adversely affects the reliable operation of base station microgrids. To tackle this issue, we propose a traffic prediction model for base station microgrids based on deep learning methods. Initially, a reference scenario for the base station microgrid is established, followed by the employment of an Improved Osprey Optimization Algorithm (IOOA) to enhance convergence speed and mitigate the risk of local optima. Ultimately, the key parameters of the CNN-BiLSTM model are optimized using the IOOA. Experimental results from real datasets corroborate the superiority of the proposed model concerning MAPE and R2 indicators, as well as perform effectively in energy savings. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Energy utilization

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A Harmonic Current Self-Compensation Control Strategy of DC Active Power Filter

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IEEE Journal of Emerging and Selected Topics in Power Electronics 2025年

作者： Li, Gaoxiang Wu, Huanchao Chen, Jining Liu, Xiao Guangxi University Guangxi Key Laboratory of Power System Optimization and Energy Technology School of Electrical En-gineering Nanning530004 China Guangxi Zhuang Autonomous Region Information Center Guangxi Key Laboratory of Digital Infrastructure Nanning530200 China Guangxi Key Laboratory of Multimedia Communications and Network Technology Guangxi Colleges and Universities Key Laboratory of Multimedia Communications and Information Processing School of Computer Electronics and Information Guangxi Uni-versity Nanning530004 China

Due to the diversity of nonlinear loads, the harmonic frequency of the DC microgrid is unpredictable, which poses a challenge to traditional DC active power filters (DC-APF). Firstly, the harmonic compensation mechanism and characteristics of the DC-APF with classical control strategy are analyzed. For the classical DC-APF, the voltage control and harmonic extraction are independent of each other, which may lead to their conflict and reduce the harmonic compensation performance. To address this issue, a harmonic current self-compensation control strategy of DC-APF is proposed, which uses a first-order inertia controller in the voltage loop and can simultaneously achieve voltage control and harmonic extraction. Then, the mechanism, characteristics, and parametric design method of the proposed harmonic current self-compensation control are introduced in detail. Compared with the classical DC-APF, the proposed DC-APF does not require any harmonic extraction filter and has better harmonic current compensation performance. Finally, the proposed control strategy and theoretical analysis are verified by simulation and experiment. © 2025 IEEE. All rights reserved.

关键词： Active filters

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