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A General Constrained Adaptive Filtering Algorithm for SISO Channel Estimation and Beamforming

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2025年第2期74卷 2770-2782页

作者： Li, Yingsong Sun, Dazhi Li, Liping Zakharov, Yuriy Miao, Yongchun Huang, Zhixiang Anhui Univ Key Lab Intelligent Comp & Signal Proc Minist Educ Hefei 230093 Peoples R China Univ York Sch Phys Engn & Technol York YO10 5DD England

In wireless communications and vehicle communications, it is useful to use adaptive filtering techniques for channel estimation, beamforming and echo cancellation. In this paper, we propose a general constrained adaptive filtering (GCAF) algorithm for single channel estimation and beamforming, which is obtained by integrating a general and adaptive loss function into the constrained adaptive filtering (CAF) framework. By selecting the parameter in the GCAF, it can approximate to several popular CAF algorithms. Then, the convergence, stability boundary and the stability analysis of the mean squared-deviation have been analyzed and presented in detail. Additionally, The complexity of the GCAF is presented and compared with the existing algorithms. The proposed GCAF is used for single-input and single-output (SISO) channel estimation and beamforming under different noises, and the tracking performance of the GCAF is also analyzed. The simulation results demonstrate that the GCAF algorithm outperforms the typically adaptive filtering algorithms and can effectively approxiamte the similar algorithms under heavy-tailed noises, which makes the proposed GCAF more robust and general.

关键词： Approximation algorithms Channel estimation signal processing algorithms Array signal processing Vectors Convergence Complexity theory Adaptive filtering beamforming channel estimation general constrained adaptive filtering algorithm

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signal processing in GPR Applications for Cave-in Prediction in Road Assessment: A Review

Signal Processing in GPR Applications for Cave-in Prediction...

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Digital signal processing and its Applications (DSPA), International Conference on

作者： Vladimir Shlykov Daniil Spitsyn Sergey Guzhov Vadim Tutubalin Sergey Vityazev Stepan Andreev Rui Fan Alexandr Dvorkovich Moscow Institute of Physics and Technology Dolgoprudny Moscow Region Russian Federation Ryazan state radio engineering university named after V.F.Utkin Ryazan Russian Federation Tongji University Shanghai P. R. China National Research University “Moscow Power Engineering Institute” Moscow Russian Federation

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

The article focuses on the problem of searching for voids under the road surface using ground penetrating radar (GPR). Early detection of such voids allows for the prediction of road collapses and prevents the occurrence of hazards. The main emphasis is on a review of signal processing algorithms used for this purpose. First, basic signal processing steps common to all GPR applications are considered. Then some advanced GPR signal processing methods are discussed. Next, the techniques used specifically for cave-in prediction are highlighted. Finally, an experimental study is described. The article is a review and introduces an important area of research and development.

关键词： Three-dimensional displays Reviews Roads signal processing algorithms Radar imaging Media Search problems Recording Surface treatment Research and development

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Optimizing Neural Prosthetic Control Systems Using Genetic Algorithm for Adaptive signal processing

Optimizing Neural Prosthetic Control Systems Using Genetic A...

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Multi-Agent Systems for Collaborative Intelligence (ICMSCI), International Conference on

作者： S. Purnima A. Sathiya P. Poonkuzhali Minu Balakrishnan Saravanan M M. Saravanan Dept. of BME Jerusalem College of Engineering Chennai Department of ECE M. Kumarasamy College of Engineering (Autonomous) Karur Department of ECE R.M.D. Engineering College Chennai Department of Information Technology Sri Eshwar College of Engineering Coimbatore Department of ECE Sri Eshwar college of engineering Coimbatore Department of ECE Faculty of Engineering & Technology Annamalai University Chidambaram

ISBN: (数字)9798331509828

ISBN: (纸本)9798331509835

Neural prosthetic systems provide promising solutions for restoring motor functions in individuals with disabilities. However, optimizing the control systems that decode neural signals remains a key challenge due to the dynamic nature of neural activity. This paper proposes a novel approach using a Genetic Algorithm (GA) to optimize the parameters of adaptive signal processing algorithms in neural prosthetic systems. The GA enables continuous calibration and adjustment, improving the accuracy of neural signal decoding and control over time. Simulation results show significant improvements in the efficiency of signal decoding from EEG/EMG data, leading to smoother control of prosthetic devices. The proposed methodology offers an adaptive and user-specific solution, contributing to enhanced prosthetic functionality and user experience.

关键词： Accuracy signal processing algorithms Control systems Adaptive signal processing User experience Decoding Time factors Prosthetics Genetic algorithms Testing

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Optimized algorithms for FPGA Implementation of PDCCH Chain for 5G-NR Base Station

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2025年

作者： Rudramuniyappa, Harsha Soujanya, Samudrala Singh, Prem Sharma, Ekant IIIT Bangalore ECE Dept Bengaluru 560100 India IIT Roorkee ECE Dept Roorkee 247667 India

The physical layer in a cellular network base station typically runs on a field programmable gate array (FPGA) to enable reconfigurability and adaptability to meet future demands of the network with sufficient computational power. This work proposes a novel architecture and algorithms for the FPGA implementation of the fifth-generation (5G) new radio (NR) physical downlink control channel (PDCCH) using the 3GPP procedures for downlink control information (DCI) processing, including sub-block interleaver, bit selection, scrambling, golden sequence generation, and modulation. The proposed algorithms are optimized to meet 5G-NR frame timings for DCI processing with minimum power consumption and hardware resource utilization. We perform rigorous testing including all corner cases to benchmark our designs in i) standalone mode, and ii) integrated fashion for the end-to-end PDCCH processing. The PDCCH implementation, with maximum DCI payload, using the proposed architecture and algorithms achieves 1.5 mu s latency, 1.98% hardware resource utilization, 1.2$ Gbps throughput and 10 Gbps/W power efficiency. With a subcarrier spacing Delta f=30 KHz, it can multiplex DCI to schedule up to 20 and 40 users for one orthogonal frequency division multiplexing (OFDM) and two OFDM symbols long PDCCH respectively.

关键词： Field programmable gate arrays Hardware Physical layer OFDM 3GPP signal processing algorithms Encoding 1/f noise Throughput Symbols 5G-NR hardware implementation DCI PDCCH FPGA AXI-stream

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Research and Design of AIS Reception signal processing System Based on GNU Radio

Research and Design of AIS Reception Signal Processing Syste...

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International Conference on Advanced Communication Technology (ICACT)

作者： Zijiao Zhou Peng Gong Bin Tang Piao He Xiuming Peng Guangwei Zhang National Key Laboratory of Mechatronic Engineering and Control School of Mechatronical Engineering Beijing Institute of Technology Beijing China

ISBN: (数字)9791188428137

ISBN: (纸本)9798331507602

The Automatic Identification System (AIS), as a standard communication and navigation device for ships, plays a significant role in ensuring the safety and efficiency of maritime traffic. The accuracy of the AIS receiver’s signal processing directly affects the bit error rate (BER) and packet error rate (PER) of the AIS system, drawing considerable attention to AIS signal reception and processing technologies. Current research on AIS reception signals mainly focuses on custom implementations using hardware platforms like FPGAs; however, the high cost of hardware implementation has become a limiting factor in the development of AIS signal processing technologies. Therefore, this paper designs an AIS reception signal processing system based on GNU Radio, developing demodulation algorithm and NRZI decoding modules, and testing them with typical demodulation algorithms. Experimental results demonstrate the feasibility and effectiveness of the designed reception signal processing system.

关键词： Costs Software algorithms Bit error rate signal processing algorithms signal processing Hardware Decoding Artificial intelligence Standards Demodulation

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Blind Deconvolution of Graph signals: Robustness to Graph Perturbations

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IEEE signal processing LETTERS 2025年 32卷 1381-1385页

作者： Ye, Chang Mateos, Gonzalo Univ Rochester Dept ECE Rochester NY 14627 USA

We study blind deconvolution of signals defined on the nodes of an undirected graph. Although observations are bilinear functions of both unknowns, namely the forward convolutional filter coefficients and the graph signal input, a filter invertibility requirement along with input sparsity allow for an efficient linear programming reformulation. Unlike prior art that relied on perfect knowledge of the graph eigenbasis, here we derive stable recovery conditions in the presence of small graph perturbations. We also contribute a provably convergent robust algorithm, which alternates between blind deconvolution of graph signals and eigenbasis denoising in the Stiefel manifold. Reproducible numerical tests showcase the algorithm's robustness under several graph eigenbasis perturbation models.

关键词： Perturbation methods Deconvolution signal processing algorithms Upper bound Topology Robustness Noise reduction Vectors Temperature sensors Stability analysis Graph signal processing robust blind deconvolution graph perturbation eigenbasis denoising stable recovery

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A Noncontact Sleep Monitoring Method Based on Millimeter-Wave Radar

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2025年 74卷

作者： Duan, Xiang Li, Kunpeng Liu, Xuan Li, Yang Hou, Yuqing He, Xiaowei Tang, Sheng Northwest Univ Sch Informat Sci & Technol Xian 710127 Shaanxi Peoples R China

High-quality sleep is a fundamental guarantee for human physical health. Sleep monitoring is crucial for understanding sleep quality and structure, but traditional sleep monitoring methods often require specialized lab environments and uncomfortable sensors. This article proposes a noncontact sleep monitoring method based on millimeter-wave radar, which accurately measures breathing and heartbeat rates during sleep by preprocessing reflected signals and using variational mode extraction (VME) algorithm and simultaneously detects snoring events. In order to improve the accuracy of snoring detection, a sliding window algorithm based on data density and amplitude is introduced, effectively filtering out low-amplitude noise and accurately identifying snoring segments. Experimental results show that this method can detect snoring events with an average error of 0.10 s, and the accuracy of breathing rate and heart rate (HR) detection is approximately 0.72 and 2.56 bpm, respectively. This method demonstrates high real-time performance and reliability and is expected to find broad applications in the diagnosis of clinical sleep disorders and home health monitoring.

关键词： Monitoring Sleep apnea Radar Millimeter wave radar Biomedical monitoring Heart rate Sensors Chirp signal processing algorithms Heart beat Breath heartbeat millimeter-wave radar sleep monitoring snore

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A Method to Obtain Non-Power-of-Two FFT Flow Graphs Based on a New Prime Factor Algorithm

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IEEE TRANSACTIONS ON signal processing 2025年 73卷 1004-1017页

作者： Bautista, Victor Manuel Garrido, Mario Univ Politecn Madrid UPM ETSI Telecomun DEPT ELECT ENGN MADRID 28040 Spain

This paper presents a novel method to obtain non-power-of-two (NP2) fast Fourier transform (FFT) flow graphs based on a new prime factor algorithm (PFA). The FFT flow graph is crucial for designing FFT architectures but previous works only provide systematic approaches to build flow graphs for power-of-two sizes (P2). Thus, the derivation of NP2 flow graphs is an important step towards the design of efficient NP2 FFT architectures. The proposed approach consists of two independent parts. On the one hand, it obtains all the possible index mappings that lead to a flow graph with no rotations between butterflies. On the other hand, it determines the permutations between butterflies in the flow graph. By combining these two parts, the order of the inputs and outputs is derived. As a result, the entire flow graph is obtained systematically. Additionally, the proposed approach generates all the possible flow graphs for a given factorization of the FFT size. The reduction in operations for NP2 FFTs using the proposed approach leads to a significant reduction in area and power consumption concerning P2 FFTs with similar sizes after implementing the proposed flow graphs directly in hardware. Particularly, there is a significant improvement between the proposed 30-point and 60-point FFT and previous efficient P2 FFTs. This remarkable fact sets NP2 at the forefront of FFT research after being in second place behind P2 FFTs for decades.

关键词： Fast Fourier transforms Flow graphs Indexes signal processing algorithms Discrete Fourier transforms Systematics Standards Software algorithms Hardware Hands Fast Fourier transform (FFT) non-power-of-two (NP2) index mapping prime factor algorithm (PFA) butterfly

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Improved Low-Complexity Sparse Bayesian Learning With Embedded Bayesian Threshold

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IEEE signal processing LETTERS 2025年 32卷 1066-1070页

作者： Yang, Yifei Qi, Tengfei Wang, Qianli Zhu, Pengcheng Deng, Xiong Southeast Univ Natl Mobile Commun Res Lab Nanjing 211189 Peoples R China Southwest Jiaotong Univ Sch Info Sci & Tech Chengdu 611756 Peoples R China

Sparse Bayesian Learning (SBL) is recognized for its efficacy in sparse signal recovery, the computational demand escalates significantly with increasing data dimensionality due to the matrix inversion at each iteration. An Inverse-Free sparse Bayesian Learning (IF-SBL) approach has been introduced to mitigate computational complexity. However, IF-SBL converges easily to a sub-optimal solution with false peaks due to the neglect of the correlation between atoms. In this paper, we analyze causes of false peaks in IF-SBL. Subsequently, a novel dynamically updated embedded Bayesian threshold is designed to mitigate the interference caused by false peaks. This innovative approach retrieves the stability and reliability without significantly increasing signal recovery complexity compared with IF-SBL. Simulation experiments validate the results.

关键词： Bayes methods Sparse matrices Noise Iterative methods Vectors Covariance matrices Computational complexity Testing signal to noise ratio signal processing algorithms Bayesian threshold compressd sensing inverse-free sparse Bayesian learning relaxed evidence lower bound

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Meta-Heuristic Approaches to Parallel processing in signal Representation and Real-Time Analysis

Meta-Heuristic Approaches to Parallel Processing in Signal R...

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Automation and Computation (AUTOCOM), International Conference on

作者： Harisha Naik N T Sudhanshu Dev Aniket Shivam Neelesh Singh Shreenidhi H S Awakash Mishra Department of Computer Applications (DCA) Presidency College Bengaluru India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Computer Science and Engineering Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India Chitkara Centre for Research and Development Chitkara University Baddi Himachal Pradesh India School of Engineering and Technology Computer Science and Engineering JAIN (Deemed to be University) Bangalore Karnataka Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (数字)9798331542375

ISBN: (纸本)9798331542382

Meta-heuristic techniques have been popular in solving highly complex optimization problems. Parallel processing is very important in signal representation and real-time analysis, as it helps lower the time required for the data process so that algorithms can perform faster. The biggest challenge with the traditional parallel processing techniques is load balancing and higher communication overhead, which may need to scale up to a larger extent. Meta-heuristic techniques reduce the complexity of problems that are NP-complete or NP-hard by providing satisfactory solutions and approximate answers to difficult ones. This has helped in parallel processing for signal representation and real-time analysis. Parallel processing has also been useful in using meta-heuristic algorithms like genetic algorithms, ant colony optimization, and particle swarm optimization. Meta-heuristic algorithms produce flexible, adaptive mechanisms for solving complex problems.

关键词： Heuristic algorithms Metaheuristics signal processing algorithms Parallel processing signal processing Approximation algorithms Load management Real-time systems signal representation Particle swarm optimization

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