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Practical Implementation Challenges in MIMO Beamforming and Its Applications

IEEE MICROWAVE MAGAZINE 2025年第4期26卷 59-75页

作者： Dusari, Nageswara Rao Rawat, Meenakshi Indian Inst Technol Roorkee Dept Elect & Commun Engn Roorkee 247667 India

Adaptive beamforming is a crucial signal processing technique used in 5G and beyond to mitigate path losses and improve energy and spectral efficiency by transmitting and receiving signals directionally. The MIMO beamforming systems contain multiple power amplifiers (PAs), which consume substantial power and require efficient linearization to enhance energy efficiency and reduce nonlinear distortions. However, implementing beamforming and PA linearization in real time introduces significant challenges, including calibration, synchronization, and hardware constraints. This article presents the practical challenges of implementing beamforming and digital predistortion (DPD) algorithms in hardware platforms and measurement processes. This article also discusses advanced techniques for linearizing PAs and overcoming measurement-related issues in beamforming systems.

关键词： Array signal processing Transmitters 5G mobile communication Spectral efficiency signal processing algorithms Hardware Real-time systems Calibration Synchronization Distortion measurement

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Power-Enhanced GNSS Interference Mitigation With Sensed Equivalent Bandwidth Based on ASF Algorithm

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IEEE SENSORS JOURNAL 2025年第2期25卷 2886-2896页

作者： Song, Jie Lu, Zukun Xiao, Wei Li, Chenglong Wang, Yuqing Sun, Guangfu Natl Univ Def Technol Coll Elect Sci & Technol Changsha 410073 Peoples R China Key Lab Satellite Nav Technol Changsha 410073 Peoples R China Hunan Inst Adv Technol Yueyang 414015 Peoples R China

Power-enhancement is a primary focus in the global navigation satellite system (GNSS) to improve its anti-interference capabilities. However, interference issues cannot be fully resolved due to the limited increase in signal power. Additionally, traditional interference mitigation methods often misclassify signals as interference and suppress them, leading to significant GNSS signal loss. This article proposes an adaptive sparse filtering (ASF) method based on sensed equivalent bandwidth, enabling interference mitigation for GNSS power-enhancement without additional signal loss. By analyzing the spectral relationship between interference and signal bandwidth, the equivalent bandwidth that ignores the strong signal recognition is derived, and the sparse sampling model is developed to reconstruct the interference mitigation filter. Simulations and practical tests verify the effectiveness of this interference mitigation method, which is broadly applicable to both conventional and power-enhanced GNSS signals. It improves anti-interference performance by 3-5 dB without introducing additional computational complexity associated with spectral awareness. This improvement in signal quality also results in the 19% increase in positioning accuracy.

关键词： Interference Global navigation satellite system Filtering algorithms Prevention and mitigation signal processing algorithms Receivers Filtering theory Satellites Information filters Vectors Adaptive sparse filtering (ASF) global navigation satellite system (GNSS) power-enhancement high anti-interference performance interference mitigation low-cost sensed equivalent bandwidth

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Modified Time-Domain Backprojection Algorithm for SAR Frequency-Domain Autofocus

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2025年 63卷

作者： Liu, Yanqi Fan, Jixia Tao, Manyi Shi, Tianyue Mao, Xinhua Nanjing Univ Aeronaut & Astronaut Key Lab Radar Imaging & Microwave Photon Minist Educ Nanjing 211106 Peoples R China Shanghai Acad Spaceflight Technol Shanghai 201109 Peoples R China Shanghai Inst Satellite Engn Shanghai 201109 Peoples R China Nanjing Univ Aeronaut & Astronaut Shenzhen Res Inst Shenzhen 518063 Peoples R China

The backprojection (BP) algorithm is a precise time-domain technique in synthetic aperture radar (SAR) imaging, known for its robustness in scenarios where frequency-domain algorithms struggle, such as nonlinear flight paths, high-resolution demands, or large imaging swaths. However, the unknown spectral structures of BP images pose significant challenges for frequency-domain autofocus algorithms, including phase gradient autofocus (PGA). This article introduces a novel interpretation of the BP algorithm, and then compares the image spectra between BP and the polar format algorithm (PFA). Our findings indicate that BP image's spectrum suffers from severe range ambiguity and spectral misalignment, which is the key reason why BP images cannot be directly applied to PGA. To address these issues, we first improve the postprocessing method, and then propose a modified BP algorithm. Both the approaches reconstruct the signal spectrum, thereby facilitating the direct application of PGA. Compared with the postprocessing method, the proposed algorithm is more efficient. Simulation and real data experiments validate the feasibility and efficacy of the proposed method, demonstrating the proposed algorithm's suitability for autofocusing in the frequency domain.

关键词： Radar imaging Electronics packaging Frequency-domain analysis Imaging History signal processing algorithms Fourier transforms Radar polarimetry Azimuth Synthetic aperture radar Backprojection (BP) frequency-domain autofocus spectrum analysis synthetic aperture radar (SAR)

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A Digital LLRF System Based on Intrapulse Phase Feedback for LINAC in Hefei Advanced Light Facility

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IEEE TRANSACTIONS ON NUCLEAR SCIENCE 2025年第3期72卷 483-490页

作者： Li, Zhenyan Qin, Jiajun Zhao, Lei Hou, Kexi Du, Baiting Ma, Yuelei Univ Sci & Technol China State Key Lab Particle Detect & Elect Hefei 230026 Peoples R China Univ Sci & Technol China Dept Modern Phys Hefei 230026 Peoples R China Univ Sci & Technol China Natl Synchrotron Radiat Lab Hefei 230026 Peoples R China

The linear accelerator system (LINAC) in Hefei advanced light facility (HALF) under construction will accelerate the beam to 2.2 GeV to reach the required luminosity. To achieve stable amplitude and phase control of the radio frequency (RF) field inside the acceleration tubes, low-level RF (LLRF) systems should be adopted. As the solid-state amplifier (SSA) and klystron operate in the saturated state, the system requires amplitude open-loop control and stable phase close-loop control during large amplitude disturbance, proposing a demand for the online phase stability to be better than 0.2 degrees rms with a klystron. In this article, we introduce a digital LLRF system designed for the LINAC of HALF. The LLRF system aims to achieve a fast intrapulse phase feedback control independent of the amplitude control, which is conducive to high phase-control stability. The system obtains digital phase data directly from a phase discriminator (PD) and an analog-to-digital converter (ADC). Besides, the independent output phase control is achieved through an analog time delay chip (ATD). As a result, the digital signal processing (DSP) algorithm is simplified, which is beneficial for achieving low closed-loop latency. Finally, we present the preliminary test results of the LLRF system, proving that the system could achieve fast and independent phase feedback control in one pulse duration.

关键词： Radio frequency Linear particle accelerator Phase control signal processing algorithms Phase modulation Phase detection Klystrons Hefei advanced light facility (HALF) intrapulse phase feedback linear accelerator system (LINAC) low-level radio frequency (LLRF) system

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A Robust Timing Recovery Algorithm With Enhanced DPLL Performance for Nyquist Digital Multi-Band Optical Systems

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JOURNAL OF LIGHTWAVE TECHNOLOGY 2025年第1期43卷 29-41页

作者： Zhang, Ziheng Guo, Wanzhen Luo, Jiating Zheng, Bofang Zhao, Jian South China Univ Technol Sch Elect & Informat Engn Guangzhou 510640 Peoples R China Huawei Technol Co Ltd Shenzhen 518129 Peoples R China

We propose a novel timing recovery algorithm (TRA) for Nyquist digital multi-band optical coherent systems. The proposed TRA employs two complementary metrics to cover all states of polarization (SOP) and differential group delays (DGD), and the extracted timing error is also robust to residual chromatic dispersion (rCD), phase noise and residual frequency offset (RFO). 1.12-Tbit/s simulations and 320-Gbit/s experiments are conducted to verify the proposed theory. It is shown that compared to the conventional Gardner, Godard and sGardner algorithms, the proposed TRA eliminates the singularity problem when the DGD is equal to odd times of half symbol period and the susceptibility to the signal spectral roll-off factor. This method also enhances the performance of the digital phase-lock loop with higher tolerance to clock frequency offset and loop delay than the conventional TRAs and our recently proposed TRA.

关键词： Delays Phase noise signal processing algorithms Symbols Receivers Clocks Transmitters Differential group delay digital multi-band system digital phase-lock loop time recovery

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A NTRU-Based Data Deduplication Scheme for Underwater Acoustic Sensor Networks

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IEEE SENSORS JOURNAL 2025年第7期25卷 12210-12221页

作者： Xu, Ming Guo, Tongtong Shanghai Maritime Univ Coll Informat Engn Shanghai 201306 Peoples R China

Data security and storage capacity have become more important as a result of the extensive use of underwater acoustic sensor networks (UWSNs) in fields including military applications, national defense, and marine resource research. To maintain data security while cutting costs associated with transmission and storage, we propose a number theory research unit (NTRU)-based data deduplication strategy for UWSNs, coined as NTRU-based data deduplication scheme for underwater acoustic sensor networks (NTDP). The NTDP scheme is novel in three aspects. First, a novel encryption scheme is proposed to ensure data security and privacy by utilizing primitive vectors, combined with NTRU multi-key fully homomorphic encryption and certificateless signatures in an underwater resource-constrained environment. Second, we propose a dynamic partitioning algorithm, which can identify repetitions within preprocessed data blocks so as to effectively achieve data deduplication. Third but not least, the NTDP scheme embeds a secure proof of ownership (PoW) protocol to ensure semantic security, enabling surface relay devices to claim data ownership without disclosing the actual data content, thus improving the level of data privacy protection. Extensive experimental results show that the NTDP scheme effectively enhances data transmission security and improves data storage efficiency in UWSNs.

关键词： Sensors Relays Sea surface Noise Underwater acoustics Heuristic algorithms Data models Unified modeling language Surface treatment signal processing algorithms Dynamic partition number theory research unit (NTRU) proof of ownership (PoW) underwater acoustic sensor networks (UWSNs)

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Weighted Average Consensus algorithms in Distributed and Federated Learning

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2025年第2期12卷 1369-1382页

作者： Tedeschini, Bernardo Camajori Savazzi, Stefano Nicoli, Monica Politecn Milan I-20133 Milan Italy Consiglio Nazl Ric CNR I-20133 Milan Italy

The exponential growth of the Internet of Things (IoT) has created an essential demand for Distributed Machine Learning (DML) systems. In this context, Federated Learning (FL) allows IoT devices to collaboratively train models while maintaining data ownership and privacy. Despite the evident advantages, FL faces practical challenges such as client selection and adaptation to heterogeneous data distributions. Recently, consensus-driven algorithms have been proposed to enable efficient and scalable FL without a central coordinating entity. Weighted Average Consensus (WAC) tools, primarily used in distributed signal processing, fail to address FL-specific challenges. The paper proposes a new family of server-less FL algorithms optimized to exploit WAC techniques. In particular, we propose an evolution of the centralized Federated Adaptive Weighting (FedAdp) method and present three distinct WAC schemes specifically designed for non-Independent and Identical Distributed (IID) data. Each scheme has a unique aggregation part that optimizes the weights of the clients' local models. The performances are evaluated in a real-world IoT system, analyzing their convergence properties in the context of heterogeneous client populations. Results show that the proposed algorithms outperform vanilla consensus FL up to 56% of accuracy and they are resilient to both label and sample data skewness.

关键词： Data models Heuristic algorithms Internet of Things Adaptation models Convergence signal processing algorithms Vehicle dynamics Optimization Distributed databases Training FL over networks weighted average consensus non-independent and identical distributed edge computing

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Physics-Informed Scattering Transform Network for Modulation Recognition in 5G Industrial Cognitive Communications Considering Nonlinear Impairments in Active Phased Arrays

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2025年第1期21卷 425-434页

作者： An, Zeliang Xu, Yuqing Tahir, Abdullah Wang, Jun Ma, Baoze Pedersen, Gert Frolund Shen, Ming Anhui Polytech Univ Sch Comp & Informat Wuhu 241000 Peoples R China Aalborg Univ Dept Elect Syst DK-9220 Aalborg Denmark Univ Engn & Technol Dept Mechatron Engn Faisalabad Campus Lahore 38000 Pakistan Chongqing Univ Posts & Telecommun Sch Optoelect Engn Chongqing 400065 Peoples R China

Modulation recognition (MR) plays a pivotal role due to its application in the spectrum sensing of 5G industrial cognitive communications and radio interference detection at the physical layer of the Internet of Things (IoT). Previous works have mainly focused on simulated fourth-generation (4G) multicarrier systems and ideal radio frequency (RF) scenarios. To bridge the gap between practice and theory, we propose a viable MR algorithm on all-physical testbeds, with nonlinear impairments of 28 GHz active phased arrays (APA). Specifically, our testbed is built on the Rohde&Schwarz (R&S) vector signal generation R&S-SMBV100B and spectrum analyzer R&S-FSW 67 GHz. To extract salient modulation patterns, we develop a physical-informed scattering transform (SCT) MR network (SCTMR-Net). With SCT modules, SCTMR-Net produces the translation-invariant and deformation-stable representations of 5-G signals by wavelet convolution, nonlinear modulus and low-pass filters. Extensive experiments on real-world measurement verify the viability of SCTMR-Net for high robustness to APA impairments.

关键词： OFDM Convolution Radio frequency Internet of Things Feature extraction Wavelet transforms signal processing algorithms 5-G new radio (NR) industrial cognitive communications deep learning (DL) modulation recognition nonlinear active phased arrays (APA) impairments scattering transform modulation recognition-network (SCTMR-Net)

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A Module to Enhance the Generalization Ability of End-to-End Deep Learning Systems in Optical Fiber Communications

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JOURNAL OF LIGHTWAVE TECHNOLOGY 2025年第2期43卷 596-601页

作者： Liu, Zheng Liu, Tiegen Zhao, Jian Uduagbomen, Joshua Wang, Yulin Popov, Sergei Xu, Tianhua Tianjin Univ Sch Precis Instruments & Optoelect Engn Tianjin 300072 Peoples R China Univ Warwick Sch Engn Coventry CV4 7AL England KTH Royal Inst Technol S-16440 Stockholm Sweden Tianjin Univ Tianjin 300072 Peoples R China UCL Dept Elect & Elect Engn London WC1E 7JE England

AnAdapter module is developed to increase the generalization capability of the end-to-end learning system for optical fiber communication systems. The Adapter has an interpretable structure and can be inserted and used without changing the original signal processing structure. The Adapter module can improve the system generalization capability and achieve the correct demapping within the transmission distance fluctuation range of $\pm$100 km and the power fluctuation range of $\pm$0.5 dBm. In addition, using an Adapter can improve the performance of optical communication by modifying the equalization algorithm without altering the structure of the existing transmission system.

关键词： Vectors Deep learning Optical fiber dispersion signal processing algorithms Optical fiber networks Constellation diagram Transceivers End-to-end deep learning fiber nonlinearity generalization geometric shaping optical communication

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Distributed Cascaded Spline-Based Adaptive Graph Filters for Nonlinear Systems: Design and Performance Analysis

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IEEE TRANSACTIONS ON signal AND INFORMATION processing OVER NETWORKS 2025年 11卷 274-288页

作者： Cai, Peng Lin, Dongyuan Qian, Junhui Zheng, Yunfei Guo, Zhongyuan Wang, Shiyuan Southwest Univ Coll Elect & Informat Engn Chongqing 400715 Peoples R China Chongqing Univ Sch Microelect & Commun Engn Chongqing 400044 Peoples R China Chongqing Univ Chongqing Key Lab Biopercept & Intelligent Informa Chongqing 400044 Peoples R China

The distributed nonlinear adaptive graph filter (DNAGF) is developed with the single nonlinear graph filter model (NGFM) to handle streaming datasets. However, the current DNAGFs tend to underperform when predicting unknown nonlinear dynamic systems. This suboptimal performance is due to their reliance on a single NGFM and the network's limited computational burden. To address these issues, two novel cascaded DNAGFs considering the spline interpolation method, i.e. a distributed Wiener spline adaptive graph filter (DWSAGF) and distributed Hammerstein spline adaptive graph filter (DHSAGF), are proposed to improve the capacity for nonlineaprediction in this paper. By utilizing piecewise low-order nonlinear spline functions, the proposed DWSAGF and DHSAGF can adapt locally to improve the fitting of the predicted nonlinear system to the unknown one. In DWSAGF and DHSAGF, the cascaded architectures containing linear and nonlinear subsystems are employed, which are more flexible than the single NGFM. Particularly, since DHSAGF has a memory through the constructed matrix U(t)(m)(r), it generates higher performance than DWSAGF for complex or time-varying nonlinear systems. In addition, the detailed performance analyses regarding DWSAGF and DHSAGF in the mean and mean-square senses are presented. Simulations are exhibited to validate the theoretical analysis and to show the performance superiorities of DWSAGF and DHSAGF.

关键词： Splines (mathematics) Adaptation models Interpolation Autoregressive processes Vectors Polynomials Nonlinear systems Finite impulse response filters signal processing algorithms Information processing Cascaded models distributed estimation graph signal processing nonlinear graph filter spline adaptive filter

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