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low-complexity Decentralized Output-Feedback Fault-Tolerant Control of General Unknown Interconnected Nonlinear Systems

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2025年 22卷 5852-5862页

作者： Yang, Jin-Zi Zhang, Jin-Xi Chai, Tianyou Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang 110819 Peoples R China

This paper is concentrated on the problem of decentralized output-feedback control of interconnected strict-feedback systems with actuator failures. It is focused on the cases where the virtual control coefficients of the plant are unknown;the global boundedness, matching conditions or global Lipschitz conditions of the interconnections are not assumed;the control algorithm is as simple as possible. They render the existing decentralized output-feedback fault-tolerant control designs infeasible. To address the problem, a low-complexity decentralized robust prescribed performance control approach based on a linear state transformation and an input-driven filter is put forward in this paper. It achieves the system outputs to track the corresponding references with the preassigned speed and accuracy. It is also inherently robust against the unknown system dynamics, the actuator failures, and the disturbances, thus without parameter estimation, function approximation, derivative computation, command filtering, fault detection, fault isolation or fault estimation. Finally, a comparative simulation on two inverted pendulums linked by a spring is conducted to demonstrate the developed control design.

关键词： Actuators Interconnected systems Nonlinear systems Estimation Fault tolerant systems Fault tolerance Fault detection Actuator failures decentralized output-feedback control general interconnected systems low-complexity model uncertainties

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low-complexity channel estimation for wideband mmWave massive MIMO systems with uniform planar arrays

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The Journal of China Universities of Posts and Telecommunications 2025年第1期32卷 1-10页

作者： Wang Haotian Liu Lizhou Qiu Ling Zhang Lei School of Electronic and Information Engineering University of Science and Technology of ChinaHefei 230022China

Millimeter-wave(mmWave) and massive multiple-input multiple-output(MIMO) are broadly recognized as key enabling technologies for the fifth generation(5G) communication systems. In this paper, a low-complexity angle-delay parameters estimation(ADPE) algorithm was put forward for wideband mmWave systems with uniform planar arrays(UPAs). In particular, the ADPE algorithm effectively decouples the angle-delay parameters and converts the angle-delay estimation problem into three independent subproblems. Accordingly, the ability to devise an off-grid method based on discrete Fourier transform(DFT) with a closed-form solution for angle-delay estimation and potential path number acquisition can be realized. In actuality, only a limited number of potential paths are close to the true paths influenced by noise. Consequently, the removal of noise paths to acquire the corresponding true path gains through a sparsity adaptive path gains estimation(APGE) algorithm is postulated. Finally, the simulation results substantiate the effectiveness of ADPE and APGE algorithms.

关键词： wideband millimeter-wave(mmWave) massive multiple-input multiple-out(MIMO) low-complexity uniform planar array(UPA) channel estimation

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low-complexity Near-Optimal Demodulation for Spatial Modulation Based on M-Algorithm

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IEEE WIRELESS COMMUNICATIONS LETTERS 2025年第3期14卷 571-575页

作者： Zheng, Jian Sun, Yutai Zhou, Huayi Zhang, Chuan Southeast Univ Natl Mobile Commun Res Lab LEADS Nanjing 211189 Peoples R China Southeast Univ Frontiers Sci Ctr Mobile Informat Commun & Secur Nanjing 211189 Peoples R China Purple Mt Labs Nanjing 211100 Peoples R China

Spatial modulation (SM), renowned for its high energy efficiency, stands as a pivotal massive MIMO transmission technique. Leveraging the parallel processing capability and superior error rate performance, the M-algorithm to maximum likelihood (MML) algorithm has emerged as a competitive demodulation method for SM systems. In MML, judicious configuration of layer widths can effectively diminish complexity. Nevertheless, existing literature, to the best of our knowledge, relies on empirical settings for layer widths, lacking a formal optimization strategy. In this letter, we propose a layer width optimization algorithm based on mathematical analysis and Monte Carlo simulations. Numerical results have demonstrated that the MML algorithm coupled with our proposed layer width configuration method yields the symbol vector error rate (SVER) comparable to the state-of-the-art optimal demodulation, while achieving a noteworthy complexity reduction.

关键词： Demodulation Modulation Symbols Transmitting antennas Vectors Monte Carlo methods Measurement complexity theory Receiving antennas Optimization Spatial modulation (SM) M-algorithm near-optimal demodulation low-complexity

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Noise Suppression Method With low-complexity Noise Estimation Model and Heuristic Noise-Masking Algorithm for Real-Time Processing of Robot Vacuum Cleaners

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IEEE ACCESS 2025年 13卷 789-801页

作者： Shin, Seunghyeon Kim, Minhan Jeon, Inkoo Song, Ju-Man Park, Yongjin Son, Jungkwan Lee, Seokjin Kyungpook Natl Univ Sch Elect & Elect Engn Daegu 41566 South Korea LG Elect Adv Robot Lab Seoul 07336 South Korea Kyungpook Natl Univ Sch Elect Engn Daegu 41566 South Korea

Noise suppression in a high-level noise environment using a low-complexity method is challenging. This study proposes a low-complexity noise suppression algorithm for robot vacuum cleaner processors. We collected working noise from a robot vacuum cleaner along with speech signals and developed a method to extract the desired speech signal while estimating the noise. Our approach estimates the noise in the existing signal and converts it into the desired signal. In addition, we designed a low-complexity neural network capable of operating on mobile processors. The evaluation results demonstrate that our method achieves a performance comparable to that of highly computational methods. Notably, our method maintains superior performance when the intensity of the desired signal is low, and its performance is less degraded than that of other methods. It exhibits less degradation than existing methods, and in contrast to other neural networks, it avoids generating incorrect signals. Furthermore, we simplified the neural network architecture reducing its size by approximately 25% with minimal performance loss.

关键词： Noise Robots Noise reduction Neural networks complexity theory Collision avoidance Acoustics Signal to noise ratio Program processors Spectrogram Source separation low-complexity low-SNR machine learning mask estimation mono channel neural network noise suppression robot vacuum cleaner

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A low-complexity Chinese Remainder Theorem Based Multi-Carrier Delay Estimation Approach

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2025年 73卷 1643-1657页

作者： Zhang, Yuxiao Wang, Shuai Yang, Xuanhe Zhang, Jiahao Pan, Gaofeng An, Jianping Niyato, Dusit Beijing Inst Technol Sch Cyberspace Sci & Technol Beijing 100081 Peoples R China Nanyang Technol Univ Coll Comp & Data Sci Singapore 639798 Singapore

With the rapid development of cluster systems, such as unmanned aerial vehicle (UAV) networks and satellite constellations, multi-node collaboration has emerged as a critical requirement. Accurate time synchronization, a cornerstone of such collaborative systems, heavily relies on high-precision delay estimation. Traditional multi-carrier delay estimation methods face an inherent trade-off between estimation accuracy and unambiguous range. While the Chinese Remainder Theorem (CRT)-based approach resolves this dilemma by enabling high-precision estimation without sacrificing range, its computational complexity remains prohibitively high for practical implementations. To address this challenge, we propose a novel low-complexity CRT algorithm based on remainder reconstruction (RR-CRT). By introducing an auxiliary phase to reconstruct erroneous remainders, our method reduces the computational complexity from O(K-2) to O(K), where K denotes the number of subcarriers. Crucially, this reduction in complexity only marginally impacts the algorithm's performance, including the phase error tolerance range, the probability of correctly solving phase ambiguity, and the root mean square error (RMSE) of delay estimation. Numerical simulations validate the effectiveness and robustness of the proposed algorithm, demonstrating its superiority in balancing computational efficiency and estimation performance.

关键词： Estimation Delay estimation Symbols Accuracy Computational complexity Signal processing algorithms Frequency estimation Synchronization Frequency modulation Bandwidth Chinese remainder theorem multi-carrier low-complexity

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low-complexity Own Voice Reconstruction for Hearables with an In-Ear Microphone

Low-Complexity Own Voice Reconstruction for Hearables with a...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Ohlenbusch, Mattes Rollwage, Christian Doclo, Simon Fraunhofer Institute for Digital Media Technology IDMT Oldenburg Branch for Hearing Speech and Audio Technology HSA Germany Dept. of Medical Physics and Acoustics Cluster of Excellence Hearing4all Carl von Ossietzky Universität Oldenburg Germany

ISBN: (纸本)9798350368741

Hearable devices, equipped with one or more microphones, are commonly used for speech communication. Here, we consider the scenario where a hearable is used to capture the user's own voice in a noisy environment. In this scenario, own voice reconstruction (OVR) is essential for enhancing the quality and intelligibility of the recorded noisy own voice signals for telephony applications. In previous work, we developed a deep learning-based OVR system, aiming to reduce the amount of device-specific recorded signals for training by using data augmentation with phoneme-dependent models of own voice transfer characteristics. Given the limited computational resources available on hearables, in this paper we propose low-complexity variants of an OVR system based on the frequency and time joint non-linear filter (FT-JNF) architecture and investigate the required amount of device-specific recorded signals for effective data augmentation and fine-tuning. Simulation results show that the proposed OVR system considerably improves speech quality, even under constraints of low complexity and a limited amount of device-specific recorded signals. © 2025 IEEE.

关键词： data augmentation hearables low-complexity own voice reconstruction speech enhancement

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low-complexity Patch-Based No-Reference Point Cloud Quality Metric Exploiting Weighted Structure and Texture Features

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IEEE TRANSACTIONS ON BROADCASTING 2025年

作者： Neri, Michael Battisti, Federica Tampere Univ Fac Informat Technol & Commun Sci Tampere 33720 Finland Univ Padua Dept Informat Engn I-35131 Padua Italy

During the compression, transmission, and rendering of point clouds, various artifacts are introduced, affecting the quality perceived by the end user. However, evaluating the impact of these distortions on the overall quality is a challenging task. This study introduces PST-PCQA, a no-reference point cloud quality metric based on a low-complexity, learning-based framework. It evaluates point cloud quality by analyzing individual patches, integrating local and global features to predict the Mean Opinion Score. In summary, the process involves extracting features from patches, combining them, and using correlation weights to predict the overall quality. This approach allows us to assess point cloud quality without relying on a reference point cloud, making it particularly useful in scenarios where reference data is unavailable. Experimental tests on three state-of-the-art datasets show good prediction capabilities of PST-PCQA, through the analysis of different feature pooling strategies and its ability to generalize across different datasets. The ablation study confirms the benefits of evaluating quality on a patch-by-patch basis. Additionally, PST-PCQA's light-weight structure, with a small number of parameters to learn, makes it well-suited for real-time applications and devices with limited computational capacity. For reproducibility purposes, we made code, model, and pretrained weights available at https://***/michaelneri/PST-PCQA.

关键词： No-reference point cloud deep learning deep learning low-complexity low-complexity quality assessment quality assessment quality assessment

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low-complexity Control for Uncertain Time-Varying SbW Systems With Input Nonlinearity and Dual-Channel Event-Triggering Communication

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2025年

作者： Du, Kaige Ma, Bingxin Li, Jiwu Wang, Yongfu Yanshan Univ Sch Vehicle & Energy Qinhuangdao 066004 Peoples R China Hebei Key Lab Special Carrier Equipment Qinhuangdao 066004 Peoples R China Northeastern Univ Sch Mech Engn & Automat Shenyang 110819 Peoples R China

This paper addresses the low-complexity prescribed performance control problem for steer-by-wire (SbW) systems with input nonlinearity, model uncertainty, full-state constraints, and dual-channel (i.e., the controller-to-actuator and sensor-to-controller channels) event-triggering communication. Firstly, considering the coupling of longitudinal and lateral dynamics, the nonlinearity of tire force, the time-varying characteristics of longitudinal velocity and road adhesion coefficient, the time-varying nonlinear models of the 8-DOF vehicle dynamics system and SbW system are established. Secondly, a dual-channel event-triggering mechanism and low-complexity prescribed performance control method is proposed, in which the communication resources of sensor-to-controller and controller-to-actuator channels and the computing resources of the controller can be saved, also, the model uncertainty and measurement error can be against by the inherent robustness of the proposed methods. Thirdly, theoretical analysis is presented to show that the full-state and tracking errors of the SbW systems can be constrained to the prescribed ranges, and all signals of the closed-loop system are globally uniformly bounded. Finally, simulations and experiments are given to verify the validity of developed methods.

关键词： Tires Wheels Vehicle dynamics Uncertainty Motors Control systems Torque Nonlinear systems Friction Adaptation models Steer-by-wire (SbW) system time-varying nonlinearity dual-channel event-triggering mechanism prescribed performance control low-complexity

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A low complexity Linear Precoding Method for Extremely Large-Scale MIMO Systems

IEEE OPEN JOURNAL OF VEHICULAR TECHNOLOGY

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IEEE OPEN JOURNAL OF VEHICULAR TECHNOLOGY 2025年 6卷 240-255页

作者： Berra, Salah Benchabane, Abderrazak Chakraborty, Sourav Maruta, Kazuki Dinis, Rui Beko, Marko Kasdi Merbah Ouargla Univ Dept Elect & Telecommun Lab LAGE Ouargla 30000 Algeria Univ Lusofona COPELABS P-1749024 Lisbon Portugal Cooch Behar Govt Engn Coll Dept Elect & Commun Engn Cooch Behar 736170 India Tokyo Univ Sci Fac Engn Dept Elect Engn Tokyo 1628601 Japan FCT UNL Inst Telecomunicacoes P-2825515 Caparica Portugal Univ Lisbon Inst Super Tecn P-1649004 Lisbon Portugal

Massive multiple-input multiple-output (MIMO) systems are critical technologies for the next generation of networks. In this field of research, new forms of deployment are emerging, such as extremely large-scale MIMO (XL-MIMO), in which the antenna array at the base station (BS) is of extreme dimensions. As a result, spatial non-stationary features emerge as users view just a section of the antenna array, known as the visibility regions (VRs). The XL-MIMO systems can achieve higher spectral efficiency, improve cell coverage, and provide significantly higher data rates than standard MIMO systems. It is a promising technology for future sixth-generation (6G) networks. However, due to the large number of antennas, linear precoding algorithms such as Zero-Forcing (ZF) and regularized Zero-Forcing (RZF) methods suffer from unacceptable computational complexity, primarily due to the required matrix inversion. This work aims to develop low-complexity precoding techniques for the downlink XL-MIMO system. These low-complexity linear precoding methods are based on Gauss-Seidel (GS) and Successive Over-Relaxation (SOR) techniques, which avoid calculating the complex matrix inversion and lead to stable linear precoding performance. To further enhance linear precoding performance, we incorporate the Chebyshev acceleration method with the SOR and GS methods, referred to as the Cheby-SOR and Cheby-GS methods. As these proposed methods require optimizing parameters, we create a deep unfolded network (DUN) to optimize the algorithm parameters. Our performance results demonstrate that the proposed method significantly reduces computational complexity from to O(K-2), where $K$ represents the number of users. Moreover, our approach outperforms the original algorithms, requiring only a few iterations to achieve the RZF bit error rate (BER) performance.

关键词： Precoding Massive MIMO Downlink Iterative methods Computational complexity Signal processing algorithms Chebyshev approximation Interference Vehicular and wireless technologies Artificial neural networks XL-MIMO non-stationary linear precoding Chebychev acceleration low-complexity iterative method deep unfolding

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low-complexity signal detection for massive MIMO systems via trace iterative method

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Journal of Systems Engineering and Electronics 2024年第3期35卷 549-557页

作者： IMRAN A.Khoso ZHANG Xiaofei ABDUL Hayee Shaikh IHSAN A.Khoso ZAHEER Ahmed Dayo College of Electronic and Information Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China School of Electrical Engineering Korea UniversitySeoul 02841Korea School of Mathematics South China University of TechnologyGuangzhou 510641China Department of Computer Science Huanggang Normal UniversityHuanggang 438000China

Linear minimum mean square error(MMSE)detection has been shown to achieve near-optimal performance for massive multiple-input multiple-output(MIMO)systems but inevitably involves complicated matrix inversion,which entails high *** avoid the exact matrix inversion,a considerable number of implicit and explicit approximate matrix inversion based detection methods is *** combining the advantages of both the explicit and the implicit matrix inversion,this paper introduces a new low-complexity signal detection ***,the relationship between implicit and explicit techniques is ***,an enhanced Newton iteration method is introduced to realize an approximate MMSE detection for massive MIMO uplink *** proposed improved Newton iteration significantly reduces the complexity of conventional Newton ***,its complexity is still high for higher ***,it is applied only for first two *** subsequent iterations,we propose a novel trace iterative method(TIM)based low-complexity algorithm,which has significantly lower complexity than higher Newton *** guarantees of the proposed detector are also *** simulations verify that the proposed detector exhibits significant performance enhancement over recently reported iterative detectors and achieves close-to-MMSE performance while retaining the low-complexity advantage for systems with hundreds of antennas.

关键词： signal detection low-complexity linear minimum mean square error(MMSE) massive multiple-input multiple-output(MIMO) trace iterative method(TIM)

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