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Block-Level Interference Exploitation Precoding for MU-MISO: An ADMM Approach

IEEE TRANSACTIONS ON COMMUNICATIONS 2025年第5期73卷 3482-3496页

作者： Wang, Yiran Wen, Yunsi Li, Ang Hu, Xiaoyan Masouros, Christos Xi An Jiao Tong Univ Fac Elect & Informat Engn Sch Informat & Commun Engn Xian 710049 Shaanxi Peoples R China Southeast Univ Natl Mobile Commun Res Lab Nanjing 211189 Peoples R China UCL Dept Elect & Elect Engn London WC1E 7JE England

We study constructive interference based block-level precoding (CI-BLP) in the downlink of multi-user multiple-input single-output (MU-MISO) systems. Specifically, our aim is to extend the analysis on CI-BLP to the case when the number of symbol slots in a given transmission block is smaller than the number of users. To this end, we mathematically prove the feasibility of using the pseudo-inverse to obtain a closed-form structure of the optimal CI-BLP precoding matrix. Similar to the case when the number of symbol slots in a given transmission block is not smaller than the number of users, we show that a quadratic programming (QP) optimization on simplex can be constructed. We also design a low-complexity algorithm based on the alternating direction method of multipliers (ADMM) framework, which can achieve a flexible trade-off between communication performance and execution time by modifying the maximum number of iterations. We further analyze the convergence and complexity of the proposed algorithm. Numerical results validate our analysis and the optimality of the QP optimization, and further show that the proposed ADMM algorithm can provide satisfactory results in dozens of iterations, which motivates the use of CI-BLP in practical wireless systems.

关键词： Precoding Symbols Optimization Interference Measurement signal to noise ratio signal processing algorithms Wireless communication Quadrature amplitude modulation Modulation MIMO constructive interference (CI) block-level precoding (BLP) quadratic programming (QP) optimization alternating direction method of multipliers (ADMM)

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An Eigenvalue-Based Generalized MVDR Method for DOA Estimation of Underwater Targets Without Prior Knowledge of Source Number

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2025年 74卷

作者： Wang, Bo Chen, Feng Mo, Shiqi Harbin Engn Univ Natl Key Lab Underwater Acoust Technol Harbin 150001 Peoples R China Harbin Engn Univ Minist Ind & Informat Technol Key Lab Marine Informat Acquisit & Secur Harbin 150001 Peoples R China Harbin Engn Univ Coll Underwater Acoust Engn Harbin 150001 Peoples R China

The actual underwater acoustic field environment is subject to various interferences, resulting in high background noise, thereby complicating underwater target detection. Some traditional subspace direction-of-arrival (DOA) estimation algorithms often require prior knowledge of the number of sources, leading to performance degradation if the number of sources is estimated inaccurately. With advancements in sensor technology, scholars have developed acoustic vector sensors (AVSs). However, some traditional algorithms applied directly to AVS result in degraded performance of the algorithm. To address these challenges, we propose a DOA estimation algorithm that is independent of the number of sources and is applicable to AVS. This is achieved by constructing the generalized minimum variance distortionless response (G-MVDR) model based on AVS and exploring the eigenvalue ordering principle under the G-MVDR framework. It provides high-resolution DOA results independent of the number of sources and can be flexibly applied to AVS arrays. The proposed algorithm is analyzed with respect to eigenvalue ranking, and the optimal threshold is determined. Finally, the accuracy and effectiveness of the proposed algorithm are validated through simulations and experiments.

关键词： signal processing algorithms Estimation Direction-of-arrival estimation Vectors Noise Mathematical models Partitioning algorithms Eigenvalues and eigenfunctions Underwater acoustics Covariance matrices Acoustic vector sensors direction of arrival (DOA) source number underwater acoustic field

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ICASSP 2024 Speech signal Improvement Challenge

IEEE OPEN JOURNAL OF SIGNAL PROCESSING

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IEEE OPEN JOURNAL OF signal processing 2025年 6卷 238-246页

作者： Ristea, Nicolae-Catalin Naderi, Babak Saabas, Ando Cutler, Ross Braun, Sebastian Branets, Solomiya Microsoft Corp Redmond WA 98073 USA

The ICASSP 2024 Speech signal Improvement Challenge aims to advance research in enhancing speech signal quality within communication systems. The speech signal quality can be assessed using the SIG metric from ITU-T P.835 and still remains a top issue in audio communication and conferencing systems. For example, in the ICASSP 2023 Deep Noise Suppression Challenge, the improvement in the background and overall quality is impressive, while the speech signal enhancement was not statistically significant. To improve the speech signal the following speech impairment areas must be addressed: coloration, discontinuity, loudness, reverberation, and noise. To this end, we organized ICASSP 2024 Speech signal Improvement Challenge, which marks the second signal-focused challenge, built upon the success of the previous ICASSP 2023 Speech signal Improvement Challenge. A training and test set was provided for the challenge, and the winners were determined using an extended crowdsourced implementation of ITU-T P.804's listening phase and the word accuracy (WAcc) rate. The results show that significant improvement was made across all measured dimensions of speech quality.

关键词： Speech enhancement Reverberation Noise Measurement Distortion Quality assessment Noise reduction Background noise signal processing algorithms Correlation deep learning subjective testing speech quality assessment

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Uplink Performance of Stacked Intelligent Metasurface-Enhanced Cell-Free Massive MIMO Systems

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2025年第5期24卷 3731-3746页

作者： Shi, Enyu Zhang, Jiayi Zhu, Yiyang An, Jiancheng Yuen, Chau Ai, Bo Beijing Jiaotong Univ State Key Lab Adv Rail Autonomous Operat Beijing 100044 Peoples R China Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing 100044 Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

In this paper, we explore the integration of low-power, low-cost stacked intelligent metasurfaces (SIM) into cell-free (CF) massive multiple-input multiple-output (mMIMO) systems to enhance access point (AP) capabilities and address high power consumption and cost challenges. Specifically, we investigate the uplink performance of a SIM-enhanced CF mMIMO system and propose a novel system framework. First, the closed-form expressions of the spectral efficiency (SE) are obtained using the unique two-layer signal processing framework of CF mMIMO systems. Second, to mitigate inter-user interference, an interference-based greedy algorithm for pilot allocation is introduced. Third, a wave-based beamforming algorithm for SIM is proposed, based only on statistical channel state information, which effectively reduces the fronthaul costs. Finally, two different power control algorithms are proposed to improve the performance of UE with inferior channel conditions. The results indicate that increasing the number of SIM layers and meta-atoms leads to significant performance improvements and allows for a reduction in the number of APs and AP antennas, thus lowering the costs. In particular, the best SE performance is achieved with the deployment of 20 APs plus 1200 SIM meta-atoms. Finally, the proposed wave-based beamforming algorithm can enhance the SE performance of SIM-enhanced CF-mMIMO systems by 57%, significantly outperforming traditional CF mMIMO systems.

关键词： Metasurfaces Array signal processing Antennas signal processing algorithms Uplink Reconfigurable intelligent surfaces Power control Costs Central processing Unit System performance Stacked intelligent metasurface cell-free massive MIMO wave-based beamforming power control spectral efficiency

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A Resource-Efficient Time-Domain-Based Algorithm to Estimate Respiration Rate From Single-Lead ECG signal

IEEE OPEN JOURNAL OF INSTRUMENTATION AND MEASUREMENT

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IEEE OPEN JOURNAL OF INSTRUMENTATION AND MEASUREMENT 2025年 4卷

作者： Krishnapriya, G. B. Ponnalagu, R. N. Goel, Sanket Birla Inst Technol & Sci Pilani Dept Elect & Elect Engn MEMS Microfluid & Nano Elect Lab Hyderabad Campus Hyderabad 500078 India Birla Inst Technol & Sci Pilani Dept Elect & Elect Engn Hyderabad Campus Hyderabad 500078 India

This study introduces a novel, computationally efficient time-domain (TD) algorithm for accurate breath rate (BR) estimation from single-lead ECG signals, designed for wearable devices. The proposed algorithm uses statistical TD parameters-mean, prominence, and distance (MPD)-to detect valid respiratory peaks in ECG-derived respiration (EDR) signals. The performance of the MPD algorithm was evaluated using two datasets: 1) a benchmark database containing ECG acquired during dynamic activities and 2) a real-time dataset comprising ECG signals from five subjects performing dynamic activities, including standing, jogging, and recovery. Comparative analysis against state-of-the-art TD methods, such as count-orig, zero-crossing detection, peak detection, and adaptive threshold techniques, demonstrates the superiority of MPD in both accuracy and computational efficiency. On the benchmark dataset, MPD achieved a mean absolute error (MAE) of 3.66 bpm and mean absolute percentage error (MAPE) of 23.69%, outperforming the Count-Orig method (MAE = 5.09 bpm, MAPE = 32.76%). For real-time data, MPD further demonstrated robust performance with an MAE of 1.53 bpm and MAPE of 7.25%. The algorithm's design simplicity, combined with its ability to handle spurious peaks and varying signal conditions, makes it particularly suitable for resource-constrained wearable applications. Its high accuracy, low computational demands, and adaptability across activity conditions underscore its potential for continuous, real-time respiratory monitoring in diverse scenarios.

关键词： Electrocardiography Accuracy Heuristic algorithms Estimation Monitoring Real-time systems Wearable devices signal processing algorithms Performance evaluation Biomedical monitoring Bio medical signal processing denoising ECG-derived respiration (EDR) rate ECG signal processing signal processing wearable devices

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Mixed Grover: A Hybrid Version to Improve Grover's Algorithm for Unstructured Database Search

IEEE TRANSACTIONS ON QUANTUM ENGINEERING

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IEEE TRANSACTIONS ON QUANTUM ENGINEERING 2025年第1期6卷 1-13页

作者： Piron, Romain Habibie, Muhammad Idham Goursaud, Claire Univ Lyon INSA Lyon Inria CITI EA 3720 F-69007 Lyon France

In this article, we propose a new strategy to exploit Grover's algorithm for unstructured search problems. We first show that running Grover's routine with a reduced number of iterations but allowing several trials presents a complexity advantage while keeping the same success probability. Then, by a theoretical analysis of the performance, we provide a generic procedure to parameterize the number of iterations k within one shot of Grover's algorithm and the maximum number of trials T, given a targeted success pand the size of the database N. At the end, we highlight that this new approach permits to reduce the computational time by at least 10% for p >= 0.999 independently of the size of the database.

关键词： signal processing algorithms Databases Search problems Registers Flyback transformers Costs Approximation algorithms Qubit Optimization Complexity theory Complexity grover's algorithm hybrid quantum computing unstructured search

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An Enhanced Augmented Coprime Array with Low Mutual Coupling and High DOFs

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IEEE Transactions on Vehicular Technology 2025年第5期74卷 7676-7687页

作者： Han, Liang Zhao, Yijiu Mei, Sitao Zhao, Xinyi Wang, Houjun Zhang, Bo University of Electronic Science and Technology of China Shenzhen Institute for Advanced Study Shenzhen518110 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China University of Electronic Science and Technology of China School of Optoelectronic Science and Engineering Chengdu611731 China

Coprime array (CA) has gained significant attention due to its high degrees of freedom (DOFs) and large array aperture. Previous researches have focused on improving coprime arrays, but few studies have successfully combined a large array aperture, low mutual coupling, and high DOFs with the number of array elements. In this paper, we propose a novel semi-symmetrical augmented coprime array (SSACA) that strategically positions sensors by arranging M-subarrays and symmetric N-subarrays. This design reduces redundancy lags, and increases DOFs, continuous DOFs, and array aperture, thereby mitigating mutual coupling effects and improving angular resolution for the direction of arrival (DOA) estimation. We derive closed-form expressions for the DOFs, continuous DOFs, and array aperture of SSACA. Simulation results demonstrate that the proposed SSACA outperforms the existing studies regarding higher DOFs, reduced mutual coupling effects, and lower root mean square error (RMSE) in similar application scenarios, particularly in strong mutual coupling scenarios. © 1967-2012 IEEE.

关键词： Sensor arrays Sensors Mutual coupling Array signal processing Direction-of-arrival estimation Estimation Vectors Apertures Couplings signal processing algorithms

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Small-Leak Identification Method Based on Infrasound and VMD-HMM for Pipelines

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IEEE SENSORS JOURNAL 2025年第10期25卷 17413-17421页

作者： Liu, Zheyuan Shen, Shichen Yan, Jimin Chu, Jiawei Lv, Xin Liu, Yu Xu, Dianqiang Univ Shanghai Sci & Technol Sch Energy & Power Engn Shanghai 200093 Peoples R China Dalian Univ Technol Ningbo Inst Ningbo 315016 Peoples R China Ningbo Water Meter Grp Co Ltd Ningbo 315000 Peoples R China Ningbo Univ Sch Civil & Environm Engn & Geog Sci Ningbo 315211 Zhejiang Peoples R China

Pipeline leaks cause not only significant wastage of resources but also economic losses and major safety accidents. The detection of pipeline leaks and the identification of their magnitudes have attracted significant research attention. A promising method for leak detection involves the use of infrasound sensors to detect infrasound waves from leaks. However, the detection of leakage infrasound is highly challenging due to strong environmental disturbances, such as external vibrations and noise, which often obscure weak leak signals. To address these challenges, this study proposes an innovative variational mode decomposition-hidden Markov model (VMD-HMM) method for processing infrasound sensor outputs in noisy environments. The method combines an optimized VMD algorithm with the HMM, leveraging the VMD algorithm's ability to handle non-stationary signals and the HMM's superior classification performance for time-series data. The optimization of the VMD algorithm significantly improves noise reduction, while the integration with HMM enhances the accuracy of leak identification. Subsequently, a comprehensive pipeline experimental platform was constructed to validate the proposed method under varying leakage calibers and noise conditions. The experimental results demonstrated that the accuracies of traditional methods, including the HMM, BP neural network, and support vector machine (SVM), did not exceed 80%. In contrast, the proposed VMD-HMM method achieved a remarkable accuracy of 94%, significantly outperforming existing approaches and providing a robust solution for identifying small leaks in pipelines.

关键词： Pipelines Hidden Markov models Accuracy signal processing algorithms Noise Sensors Training Noise reduction Acoustics signal resolution Hidden Markov model (HMM) infrasound waves pipeline leak detection variational mode decomposition

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Cascaded Lagrangian Power Allocation to Optimize D-MIMO OWC Systems

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IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS 2025年第5期43卷 1676-1690页

作者： Cunha, Thiago E. B. Linnartz, Jean-Paul M. G. Eindhoven Univ Technol Dept Elect Engn NL-5600 MB Eindhoven Netherlands

Light mainly propagates along a line-of-sight without the rich multipath scattering that can be exploited in radio frequency (RF) multiple-input multiple-output (MIMO) systems. To ensure outage-free communication MIMO can nonetheless be used, provided that multiple ceiling nodes are spatially distributed. Angular-selective client nodes can to some extent, but not perfectly, separate spatial streams coming from different ceiling points. In addition, many optical wireless communication (OWC) links have a low-pass frequency response. Because of these properties, indoor distributed (D)-MIMO OWC differs in many aspects from RF links. This paper explores how OWC D-MIMO systems can best be operated. The optimization of how to spread power over spatial streams and frequencies comes to different settings than typically seen for radio. We evaluate algorithms by an analytical foundation and by simulation based on a commonly accepted channel model. We derive a simple criterion to select the number of spatial streams which can be used. This also can serve as a selector for switching between spatial diversity and spatial multiplexing transmission modes. Moreover, we derive a simple formula for how to best spread power among spatial streams. Besides theoretically optimum solutions, we propose a very-near-optimum algorithm that is highly efficient for practical systems in rapidly varying channels.

关键词： OFDM Streams Loading Optimization Bandwidth Throughput Resource management Wireless communication signal processing algorithms Light emitting diodes Power-loading algorithm low-pass channel optical wireless communication (OWC) distributed multiple-input multiple-output (D-MIMO) orthogonal frequency division multiplexing (OFDM)

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High-Resolution Imaging Method for Vehicle-Mounted FMCW Shallow Ice Radar

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2025年 18卷 11512-11524页

作者： Li, Binbin Zhao, Bo Yuan, Xuyi Guo, Jingxue Liu, Xiaojun Chinese Acad Sci Key Lab Electromagnet Radiat & Sensing Technol Beijing 100094 Peoples R China Chinese Acad Sci AIRCAS Aerosp Informat Res Inst Beijing 100094 Peoples R China Univ Chinese Acad Sci Sch Elect Elect & Commun Engn Beijing 100049 Peoples R China Polar Res Inst China Shanghai 200136 Peoples R China

The accumulation rate is a key parameter for calculating the surface mass balance of ice sheets and estimating sea level rise. Frequency-modulated continuous wave ice-sounding radar (FMCW-ISR) can be used to detect internal layers of ice sheets, and data of these layers are crucial for calculating the accumulation rate. However, during FMCW-ISR scanning, the same ice layer target may appear multiple times in the data matrix, leading to defocusing in the azimuth direction. In addition, FMCW-ISR systems are typically ultra-wideband, making it difficult to maintain absolute signal linearity throughout the entire sweep period. This nonlinear modulation results in high sidelobe levels, complicating the interpretation of ice layer structures. To address these problems, this article proposes a high-resolution FMCW shallow ice radar imaging method that combines the range migration algorithm (RMA) with nonlinear phase estimation and correction techniques. The proposed method effectively improves azimuth focusing accuracy and reduces sidelobe levels in the range direction, thereby better preserving the clear structure of the internal layers of the ice sheets. Validation using both simulated and measured data demonstrates that the proposed method significantly improves imaging quality, thereby making the layered structure of the shallow ice sheet more distinct.

关键词： Radar Ice Radar imaging Radar antennas Ice sheets Imaging signal processing algorithms Frequency modulation Accuracy Azimuth Frequency-modulated continuous wave (FMCW) ice-sounding radar (ISR) nonlinear phase correction range migration algorithm (RMA)

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