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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2025年第3期43卷 659-673页

作者： Cui, Mingyao Zeng, Qunsong Huang, Kaibin Univ Hong Kong Dept Elect & Elect Engn Hong Kong Peoples R China

The advancement of Rydberg atoms in quantum information technology is driving a paradigm shift from classical radio-frequency (RF) receivers to Rydberg atomic receivers. Capitalizing on the extreme sensitivity of Rydberg atoms to external electromagnetic fields, Rydberg atomic receivers are capable of realizing more precise radio-wave measurements than RF receivers to support high-performance wireless communication and sensing. Although the atomic receiver is developing rapidly in quantum-physics domain, its integration with wireless communications is at a nascent stage. In particular, systematic methods to enhance communication performance through this integration are yet to be discovered. Motivated by this observation, we propose in this paper to incorporate Rydberg atomic receivers into multiple-input-multiple-output (MIMO) communication, a prominent 5G technology, as the first attempt on implementing atomic MIMO receivers. To begin with, we provide a comprehensive introduction on the principles of Rydberg atomic receivers and build on them to design the atomic MIMO receivers. Our findings reveal that signal detection of atomic MIMO receivers corresponds to a non-linear biased phase retrieval (PR) problem, as opposed to the linear Gaussian model adopted in classical MIMO systems. Then, to recover signals from this non-linear model, we modify the Gerchberg-Saxton (GS) algorithm, a typical PR solver, into a biased GS algorithm to solve the biased PR problem. Moreover, we propose a novel Expectation-Maximization GS (EM-GS) algorithm to cope with the unique Rician distribution of the biased PR model. Our EM-GS algorithm introduces a high-pass filter constructed by the ratio of Bessel functions into the iteration procedure of GS, thereby improving the detection accuracy without sacrificing the computational efficiency. Finally, the effectiveness of the devised algorithms and the feasibility of atomic MIMO receivers are demonstrated by theoretical analysis and numerica

关键词： Receivers Atomic measurements Rydberg atoms Radio frequency Sensors Electromagnetic fields Quantum sensing Energy states Symbols signal processing algorithms Rydberg atomic receivers multiple-input-multiple-output (MIMO) quantum sensing signal detection

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Hybrid DoATDoA Method for Impact Localization on Thin-Walled Structures Using Sensor Clusters

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IEEE SENSORS JOURNAL 2025年第4期25卷 6659-6672页

作者： Zeng, Xu Deng, Deshuang Yang, Hongjuan Yang, Zhengyan Yang, Lei Wu, Zhanjun Dalian Univ Technol Sch Mech & Aerosp Engn Dalian 116024 Peoples R China Jiangnan Univ Sch Fiber Engn & Equipment Technol Wuxi 214122 Peoples R China Dalian Univ Technol Sch Mat Sci & Engn Dalian 116024 Peoples R China

Impact monitoring technology plays a critical role in ensuring the structural integrity and safety of thin-walled engineering structures in service. This article presents a novel hybrid direction of arrival (DoA)-time difference of arrival (TDoA) method for impact localization on thin-walled engineering structures using sensor clusters. The methodology involves placing two sensor clusters on the structure to capture impact signals. Subsequently, narrowband Lamb wave signals at a specific frequency are extracted from impact signals using continuous wavelet transform (CWT). The normalized variance sequence (NVS) approach is then used to determine the TDoA, and phase differences are calculated to estimate the DoA. The DoA-based spatial beamforming focusing (SBF) technique and TDoA-based hyperbolic locus imaging algorithm are used for impact imaging. An imaging fusion step is introduced to combine the results of the two imaging techniques, accurately determining the impact location. Experimental validation of the proposed method is conducted through impact tests on three distinct structures: a large-scale plate, a complex riveted stiffened plate, and a 3-D thin-walled cylindrical structure. A comparative analysis with two existing methods demonstrates the superior imaging resolution and localization accuracy of the proposed approach, which remains effective even in the presence of measurement noise. In addition, the effects of sensor type, shape, and configuration on the localization results are discussed. This research contributes to the advancement of impact localization technology for thin-walled structures, with potential applications in structural health monitoring and safety assessment.

关键词： Sensors Location awareness Sensor arrays Imaging Array signal processing Direction-of-arrival estimation signal processing algorithms Monitoring Narrowband Estimation Direction of arrival (DoA) impact localization sensor cluster time difference of arrival (TDoA)

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Motion Principle of New Parallel Mechanisms With Fewer Active Inputs Than the DOFs and Its Pose Adjustment Optimization

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IEEE-ASME TRANSACTIONS ON MECHATRONICS 2025年

作者： Wang, Yu Qiu, Can Wu, Jiabin Xu, Yundou Zhao, Yongsheng Yanshan Univ Parallel Robot & Mechatron Syst Lab Hebei Prov Qinhuangdao 066004 Peoples R China Yanshan Univ Key Lab Adv Forging & Stamping Technol & Sci Minist Educ China Qinhuangdao 066004 Peoples R China Yanshan Univ Hebei Prov Key Lab Def Sci & Technol Qinhuangdao 066004 Peoples R China

The proposed parallel mechanisms (PMs) differ from conventional PMs in that they can achieve the same mobility with fewer active joints. The general motion principle of the proposed new mechanism has been proposed. Based on the Newton iterative method and neural network approaches, a method is put forward to obtain the continuous forward solution for the new PMs. Since the posture adjustment of the moving platform is realized through the active branch adjusting the passive branches one by one in sequence, the adjustment sequence of passive branches and step size of the passive branch in each adjustment for any end posture of the new PM is optimized, with the workspace as the constraint and minimizing the number of adjustment times as the goal. The structure of the 7SPS is designed and prototype experiments are conducted. Experiment results have shown that the proposed PM can achieve the original mobility while significantly reducing the number of actuators.

关键词： Kinematics Vectors Optimization Mechatronics Biological neural networks Iterative methods Accuracy signal processing algorithms End effectors Training Adjustment sequence motion principle neural network parallel mechanism (PM)

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Optimal Driving signal Extraction for Maximum Efficiency of Dual-Input High Power Amplifiers

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IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES 2025年第1期73卷 180-194页

作者： Barradas, Filipe M. Nunes, Luis C. Pedro, Jose C. Erdmann, Christophe Univ Aveiro Inst Telecomunicacoes & DETI P-3810193 Aveiro Portugal Univ Aveiro Portugal Inst Telecomunicacoes & DETI P-3810193 Aveiro Portugal AMD Ireland Dublin D24 T683 Ireland

Dual-input single-output (DISO) radio frequency (RF) power amplifiers (PAs) have gathered significant interest for highly efficient amplification of modulated signals. DISO PAs provide advantages over their single-input single-output (SISO) counterparts, both for design and operation. However, contrary to SISO, driving DISO PAs requires an extraction of the optimum driving signals to maximize the power-added efficiency (PAE), and some input conditions can easily make the PA operate in a nonsafe region. This article presents algorithms to safely derive these optimal input signals. Two types of algorithms are proposed, which are dubbed "exploration" and "extraction";the exploration algorithm finds a safe operation region of the DISO PA from minimal a priori information on the device under test;the extraction algorithm finds the optimal input drive from the exploration algorithm data. These algorithms are tested and validated in simulation and measurement for different DISO PA architectures.

关键词： Radio frequency Costs Power generation Transistors Bandwidth signal processing algorithms Microwave transistors Data mining Probability density function Microwave theory and techniques Doherty dual-input power amplifiers (PAs) load modulation outphasing PAs shaping function

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Atomic Norm Regularized Tensor Completion for Angle Estimation in Bistatic MIMO Radar With Sensor Failures

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IEEE SENSORS JOURNAL 2025年第2期25卷 2934-2948页

作者： Chen, Jinli Song, Yang Zhang, Jincan Yao, Changhua Nanjing Univ Informat Sci & Technol Sch Elect & Informat Engn Nanjing 210044 Peoples R China

Faulty array sensors pose a significant challenge in accurately determining the target angles in bistatic multiple-input multiple-output (MIMO) radar systems. To remedy this, we propose a novel method utilizing atomic norm regularized tensor completion for joint estimates of the direction of departure (DOD) and direction of arrival (DOA). We first develop a third-order covariance tensor model for the sensor array data in bistatic MIMO radar and cast the reconstruction of missing entries caused by faulty array sensors as a low-rank tensor completion (LRTC) problem with structurally missing entries. By leveraging the Vandermonde structure inherent in the factor matrices from the CANDECOMP/PARAFAC (CP) decomposition of the covariance tensor, we impose atomic norm constraints on the factor vectors to formulate an atomic norm regularized tensor completion model. Then, an efficient optimization algorithm based on the alternating direction method of multipliers (ADMM) is developed to solve the proposed model. Moreover, to enforce the Vandermonde structure of the factor matrices, we integrate difference coarray processing to rectify the factor matrices during iterations. Finally, joint estimates of DOD and DOA are obtained by applying the estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm to the Toeplitz matrices derived from the optimized vectors. Extensive simulations demonstrate that the proposed algorithm achieves superior angle estimation accuracy and computational efficiency compared to state-of-the-art algorithms when handling array sensor failures.

关键词： Tensors Sensors Sensor arrays MIMO radar Covariance matrices Estimation Vectors Matrix decomposition Array signal processing signal processing algorithms Angle estimation atomic norm differential coarray multiple-input multiple-output (MIMO) radar sensor failures tensor completion

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Deep-Unfolded Massive Grant-Free Transmission in Cell-Free Wireless Communication Systems

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IEEE TRANSACTIONS ON signal processing 2025年 73卷 1094-1109页

作者： Sun, Gangle Cao, Mengyao Wang, Wenjin Xu, Wei Studer, Christoph Southeast Univ Natl Mobile Commun Res Lab Nanjing 210096 Peoples R China Purple Mt Labs Nanjing 211100 Peoples R China Swiss Fed Inst Technol Dept Informat Technol & Elect Engn CH-8092 Zurich Switzerland

Grant-free transmission and cell-free communication are vital in improving coverage and quality-of-service for massive machine-type communication. This paper proposes a novel framework of joint active user detection, channel estimation, and data detection (JACD) for massive grant-free transmission in cell-free wireless communication systems. We formulate JACD as an optimization problem and solve it approximately using forward-backward splitting. To deal with the discrete symbol constraint, we relax the discrete constellation to its convex hull and propose two approaches that promote solutions from the constellation set. To reduce complexity, we replace costly computations with approximate shrinkage operations and approximate posterior mean estimator computations. To improve active user detection (AUD) performance, we introduce a soft-output AUD module that considers both the data estimates and channel conditions. To jointly optimize all algorithm hyper-parameters and to improve JACD performance, we further deploy deep unfolding together with a momentum strategy, resulting in two algorithms called DU-ABC and DU-POEM. Finally, we demonstrate the efficacy of the proposed JACD algorithms via extensive system simulations.

关键词： signal processing algorithms Channel estimation Wireless communication Approximation algorithms Vectors Optimization Machine learning algorithms Training Sparse matrices Decoding Active user detection cell-free communication channel estimation data detection deep unfolding grant-free transmission massive machine-type communication

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DOA Estimation for Underwater Acoustic Array in Impulsive Noise Based on Adaptive Kernel Width Mixture Correntropy

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2025年 63卷

作者： Dai, Zehua Wu, Jinqiu Yin, Jingwei Zhang, Wenbo Qi, Xiaofei Qiao, Gang Peng Cheng Lab Dept Strateg & Adv Interdisciplinary Res Shenzhen 518055 Peoples R China Harbin Engn Univ Coll Underwater Acoust Engn Harbin 150001 Peoples R China

This article investigates a direction-of-arrival (DOA) estimation method for underwater acoustic arrays in non-Gaussian impulsive noise environments. Traditional DOA estimation methods for underwater acoustic arrays typically presume that underwater environmental noise follows a Gaussian distribution. This assumption can lead to a significant degradation in estimation accuracy, or even failure, in underwater environments where non-Gaussian impulsive noise is predominant, thereby limiting the detection capabilities of underwater acoustic arrays. To address this issue, this study employs a method based on mixture correntropy, which maximizes the mixture correntropy of the residual fitting error matrix for subspace decomposition of the received data matrix, effectively filtering out impulsive noise. Considering the signal processing performance of correntropy and mixture correntropy depends on the selection of the kernel width, this article introduces a novel adaptive method for updating the kernel width. This method updates the kernel width in each iteration based on the residual fitting error value, setting the square of the kernel width to the sum of the squares of a preset kernel width and the residual fitting error modulus. This approach retains the simplicity and robustness of the maximum mixture correntropy criterion (MMCC) algorithm while enhancing the convergence rate and achieving a lower steady-state excess mean square error. Furthermore, this study applies the classical multiple signal classification (MUSIC) algorithm for DOA estimation. Finally, simulations and sea trials have substantiated the correctness and effectiveness of the method proposed in this article.

关键词： Noise Estimation Direction-of-arrival estimation Kernel Underwater acoustics Filtering signal processing algorithms Multiple signal classification Acoustic arrays Array signal processing Adaptive kernel width direction-of-arrival (DOA) estimation mixture correntropy non-Gaussian impulsive noise underwater acoustic arrays

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Theoretical Bounds in Decentralized Hypothesis Testing

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IEEE TRANSACTIONS ON signal processing 2025年 73卷 1110-1121页

作者： Guel, Goekhan Johannes Gutenberg Univ Mainz Univ Med Ctr Mainz Dept Cardiol Prevent Cardiol & Prevent Med D-55131 Mainz Germany Johannes Gutenberg Univ Mainz Univ Med Ctr Mainz Ctr Thrombosis & Hemostasis Clin Epidemiol & Syst Med D-55131 Mainz Germany

Three fundamental problems are addressed for distributed detection networks regarding the maximum of performance/detection loss. The losses obtained are, first, due to the choice of decision rule in parallel sensor networks (general-case vs identical decisions), second, due to the choice of network architecture (serial vs parallel), and third, due to the choice of quantization rule (centralized vs decentralized). Previous results, if available, for all these three problems are restricted to the statement that the loss is "small" over some specific examples. The key principles underlying this study are delineated as follows. First, there is a surjection from all simple hypothesis tests to the receiver operating characteristic (ROC) curve. Second, the ROC can be well modeled with linear splines. Third, considering splines with only a finite number of line segments, in fact, on the order of the total number of sensors, is sufficient to determine the maximum loss. Leveraging these principles, infinite-dimensional optimization problems are reduced to their finite-dimensional equivalent forms. The equivalent problems are then numerically solved to obtain the theoretical bounds.

关键词： Quantization (signal) Splines (mathematics) Receivers Network topology Cost function Topology Accuracy Vectors signal processing algorithms Power demand Distributed detection data fusion sensor networks

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A High-Resolution TOA Estimation Algorithm Based on Coherent Subspace for Dual-Band signals

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2025年第3期24卷 2559-2573页

作者： Fan, Jiancun Gao, Jiawei Li, Renjie Xi An Jiao Tong Univ Sch Informat & Commun Engn Xian 710049 Peoples R China

The high-resolution TOA estimation of multipath channel is essential for many areas while the resolution of conventional algorithms is constrained by the system bandwidth. With the advancement of communication technology, more applications demand higher positioning accuracy, yet single-band systems are restricted by their limited bandwidth. To address this, we consider utilizing decentralized multi-band signals to obtain a larger available bandwidth for high-resolution TOA estimation. Taking dual-band signals as an example, we exploit the dual-band coherent subspace and propose a novel subspace-based high-resolution TOA estimation algorithm. The proposed algorithm does not require parameter matching with high complexity and is suitable for the existing dual-band communication systems. We also derive the Cram & eacute;r-Rao Bound (CRB) for the dual-band signal model. Simulation results show that the performance of the proposed algorithm is better than existing subspace-based algorithms available for dual-band signals and converges to the derived CRB.

关键词： Time of arrival estimation Dual band Estimation OFDM Delay effects Accuracy signal processing algorithms Diversity reception Transceivers Simulation Time-of-arrival (TOA) estimation subspace high-resolution dual-band CRB

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Simplified Fast List PAC Decoder for Broadcasting Services in 6G: Algorithm and Implementation

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IEEE TRANSACTIONS ON BROADCASTING 2025年

作者： Dai, Jingxin Yin, Hang Lv, Yansong Wang, Yuhuan Xu, Yin Lv, Rui Commun Univ China State Key Lab Media Convergence & Commun Beijing 100024 Peoples R China Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Cooperat Medianet Innovat Ctr Shanghai 200240 Peoples R China

In the 6G network, integrating broadcasting and mobile networks will significantly improve the transmission capability. Considering the excellent error-correction performance, polarized-adjusted convolutional (PAC) codes are promising for ensuring reliable data transmission in 6G broadcasting services. However, the inherent high decoding latency of PAC codes poses challenges for seamless switching between broadcasting and mobile services. In this paper, we propose a simplified fast list (SFL) PAC decoder, which jointly exploits the node thresholds and adaptive path-pruning technology to reduce the decoding latency while maintaining high reliability. Firstly, we present a novel path expansion rule based on the node thresholds to avoid unnecessary computations. Secondly, the introduction of the adaptive path-pruning technology efficiently reduces the number of sorting operations. Moreover, we implement the proposed decoder on general purpose processors (GPPs) by software. Simulation results show that the proposed SFL decoding algorithm significantly reduces the decoding latency by up to 75.18% compared to the state-of-the-art (SOTA) work with no noticeable degradation in error-correction performance. Software implementation of the proposed decoder achieves an 18.80% improvement in throughput performance over the SOTA PAC software decoder.

关键词： Decoding Picture archiving and communication systems Software Codes 6G mobile communication Broadcasting Software algorithms Throughput Polar codes signal processing algorithms PAC codes broadcasting decoding latency threshold decoder software

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