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Temporal feature-based memory neural network for probabilistic-shaping polarization-division multiplexed ultrahigh-order QAM coherent optical transmission

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Chinese Optics Letters 2025年第05期 28-32页

作者：黄雪晶高明义范佳敏戈懿凡由骁迪沈纲祥 Jiangsu Engineering Research Center of Novel Optical Fiber Technology and Communication Network Suzhou Key Laboratory of Advanced Optical Communication Network TechnologySchool of Electronic and Information EngineeringSoochow University

High-speed single-carrier transmission can be achieved by increasing the modulation format cardinality for higher spectral ***,ultrahigh-order QAM signals are usually more susceptible to various ***,we propose a temporal feature-based memory (TFM) neural network (NN) equalizer to effectively mitigate signals'impairments in ultrahigh-order *** temporal convolutional network is utilized as a feature extraction layer to significantly improve the performance of the bidirectional long short-term memory *** TFM-NN equalizer was experimentally validated in a probabilistically shaped polarization-division multiplexed 1024/4096-QAM coherent optical transmission system,and raw spectral efficiencies of 16.190 and 21.188 bit/s/Hz have been achieved at normalized generalized mutual information thresholds.

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Measurement and Analysis of Radar-Cross-Section of UAV at 21-26 GHz Frequency Band

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ZTE communications 2025年第1期23卷 107-114页

作者： AN Hao LIU Ting HE Danping MA Yihua DOU Jianwu State Key Laboratory of Advanced Rail Autonomous Operation Bei-jing Jiaotong UniversityBeijing 100044China State Key Laboratory of Mobile Network and Mobile Multimedia Technology ZTE CorporationShenzhen 518057China

With the emergence of the 6G technology,integrated sensing and communication(ISAC)has become a hot-spot vertical *** low-altitude scenario is considered to be a significant use case of the ***,the existing channel model is hard to meet the demands of the sensing *** radar-cross-section(RCS)is a critical feature for the sensing part,while accurate RCS data for the typical frequency band of ISAC are still ***,this paper conducts measurements and analysis of the RCS data of the unmanned aerial vehicles(UAVs)under multiple poses and angles in real flying *** echo from a UAV is acquired in an anechoic chamber,and the RCS values are *** results of different flying attitudes are analyzed,providing RCS features for the ISAC applications.

关键词： unmanned aerial vehicle radar-cross-section integrated sensing and communication anechoic chamber measurement

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Polarimetric Imaging LiDAR Based on FMCW and Mueller Matrix for Target Classification

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Journal of Lightwave technology 2025年第9期43卷 4063-4075页

作者： Zhang, Longkun Sun, Jianfeng Cong, Haisheng Xu, Qian Lu, Zhiyong Chen, Weibiao University of Science and Technology of China Department of Optics and Optical Engineering Hefei230026 China Chinese Academy of Sciences Key Laboratory of Space Laser Communication and Detection Technology Shanghai Institute of Optics and Fine Mechanics Shanghai201800 China Shanghai Key Laboratory of Satellite Network Shanghai200120 China

We present a three-dimensional (3D) polarimetric imaging light detection and ranging (LiDAR) based on frequency modulated continuous wave (FMCW) coherent detection and Mueller matrix polarimetry techniques for target classification. The proposed 3D polarimetric imaging LiDAR can accurately determine which point clouds (or pixels) are on target without ambiguity, which is generally challenging for conventional imaging LiDAR. To reduce artifacts caused by time-sharing polarization imaging, the spatial parallelism and beam synchronization methods are designed to simultaneously obtain multi-polarization point clouds by using Risley-prism multi-beam scanning. After acquiring the point clouds of the polarized reflection intensity, the long-range target recognition and classification can be preliminarily achieved. After calculating the Mueller matrix, the polarization characteristics of the target can be further characterized, thereby achieving more precise target recognition and classification. It is experimentally validated that the architectural materials and structural details with different polarization characteristics can be effectively distinguished and classified by using different polarization parameters, significantly improving the accuracy of target recognition. This study may open new opportunities for 3D perception of urban architecture. © 1983-2012 IEEE.

关键词： Polarimeters

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HAPG-SAQAM: Human Auditory Perception Guided Spatial Audio Quality Assessment Metric

HAPG-SAQAM: Human Auditory Perception Guided Spatial Audio Q...

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

作者： Zheng, Yuanming Yao, Jiaxuan Deng, Xiangyu Yang, Yuhong Liao, Ruiqi Tu, Weiping Lin, Cedar National Engineering Research Center for Multimedia Software School of Computer Science Wuhan University Wuhan China Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan China Guangdong OPPO Mobile Telecommunications Corp. Guangdong China

ISBN: (纸本)9798350368741

Spatial audio quality evaluation is essential for applications like virtual and augmented reality, where accurate sound reproduction enhances user immersion. While subjective listening tests are the gold standard, they are costly and time-consuming. To address this, we propose HAPG-SAQAM, an objective metric for assessing timbre quality, spatial quality, and overall quality of binaural audio, guided by human auditory perception. Our contributions include: (1) the Multi-scale Auditory Guided Feature Extraction (MAGFE) module, incorporating gammatone frequency cepstral coefficients for better alignment with human perception;(2) Perceptual Weighted Loss (PWL), optimizing the weighting of timbre quality (TQ) and spatial quality (SQ) loss based on subjective test data;and (3) data augmentation techniques to enhance robustness by amplifying perceptual distortions. Experimental results show HAPG-SAQAM improves correlation with subjective scores by 10%, with ablation studies confirming the contributions of its components to enhanced spatial and overall audio quality. © 2025 IEEE.

关键词： auditory perception spatial audio Speech and audio quality assessment subjective experiment timbre quality

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Improving Speech Enhancement by Cross- and Sub-band Processing with State Space Model

Improving Speech Enhancement by Cross- and Sub-band Processi...

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

作者： Li, Jizhen Tu, Weiping Yang, Yuhong Xu, Xinmeng Zhang, Yiqun Ren, Yanzhen NERCMS School of Computer Science Hubei Luojia Laboratory Wuhan University China Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan University China School of Cyber Science and Engineering Wuhan University China

ISBN: (纸本)9798350368741

Recently, the state space model (SSM) represented by Mamba has shown remarkable performance in long-term sequence modeling tasks, including speech enhancement. However, due to substantial differences in sub-band features, applying the same SSM to all sub-bands limits its inference capability. Additionally, when processing each time frame of the time-frequency representation, the SSM may forget certain high-frequency information of low energy, making the restoration of structure in the high-frequency bands challenging. For this reason, we propose Cross- and Sub-band Mamba (CSMamba). To assist the SSM in handling different sub-band features flexibly, we propose a band split block that splits the full-band into four sub-bands with different widths based on their information similarity. We then allocate independent weights to each subband, thereby reducing the inference burden on the SSM. Furthermore, to mitigate the forgetting of low-energy information in the high-frequency bands by the SSM, we introduce a spectrum restoration block that enhances the representation of the cross-band features from multiple perspectives. Experimental results on the DNS Challenge 2021 dataset demonstrate that CSMamba outperforms several state-of-the-art (SOTA) speech enhancement methods in three objective evaluation metrics with fewer parameters. © 2025 IEEE.

关键词： band split spectrum restoration speech enhancement state space model

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Differentially Private Federated Stochastic Primal-Dual Learning for Internet of Vehicles

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IEEE Internet of Things Journal 2025年第11期12卷 17034-17050页

作者： Li, Yiwei Wang, Shuai Chang, Tsung-Hui Xiamen University of Technology Fujian Key Laboratory of Communication Network and Information Processing Xiamen361024 China University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China The Chinese University of Hong Kong Shenzhen School of Science and Engineering Shenzhen Research Institute of Big Data Shenzhen518172 China

Federated learning (FL) has the potential to empower Internet-of-Vehicles (IoV) networks by enabling smart vehicles (SVs) to participate in the learning process under the orchestration of a vehicular service provider while keeping data locally. In this paper, we propose a novel federated stochastic primal-dual algorithm with differential privacy (FedSPD-DP) to ensure robust privacy protection for FL based IoV (FL-IoV) systems. The FedSPD-DP algorithm leverages multiple steps of local stochastic gradient descent (SGD) and partial client participation (PCP) to improve communication efficiency while incorporating differential privacy (DP) to ensure privacy protection. Our theoretical analysis explores the impact of these strategies on learning performance. Specifically, we demonstrate that the data sampling strategy and PCP enhance data privacy, while a larger number of local SGD steps may increase privacy leakage, revealing a non-trivial tradeoff between communication efficiency and privacy protection. Extensive experiments on real-world data validate the effectiveness of the proposed algorithm, showing superior performance compared to state-of-the-art FL algorithms, and confirming the analytical results and properties. © 2014 IEEE.

关键词： Federated learning

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Joint phase-frequency modulation with binary amplitudes for optical camera communication

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Optics Letters 2025年第10期50卷 3217-3220页

作者： Dong, Ke Su, Weiqiang Wang, Mingjun Chen, Dan School of Automation and Information Engineering Xi’an University of Technology Shaanxi Xi’an710048 China Xi’an Key Laboratory of Wireless Optical Communication and Network Research Shaanxi Xi’an710049 China

Constrained by the imaging mechanisms of cameras, the data transmission rate in optical camera communication (OCC) is considerably lower than that in traditional visible light communication (VLC). This Letter introduces a new, to the best of our knowledge, binary modulation scheme designed to increase OCC transmission rates, with the transmitter performing high-order modulation across frequency and phase dimensions and the receiver employing a frequency-domain demodulation approach. This proposed scheme exhibits better scalability and lower implementation complexity than existing schemes. Additionally, the influence of exposure time and readout time parameters of rolling shutter cameras on communication performance has been dissected and confirmed through numerical simulations and experimental validation, laying a theoretical foundation for the design and optimization of the OCC system. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Signaling

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Iterative Bounded Distance Decoding With Random Flipping for Product-Like Codes

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IEEE Transactions on communications 2025年第5期73卷 2864-2875页

作者： Li, Guorong Wang, Shiguo Zhao, Shancheng Jinan University National and Local Joint Research Center of Network Security Detection and Protection Technology College of Information Science and Technology Guangzhou510632 China Guangdong Key Laboratory of Data Security and Privacy Preserving Guangzhou Key Laboratory of Data Security and Privacy Preserving Guangzhou510632 China Changsha University of Science and Technology Computer and Communication Engineering Institute Changsha410114 China

Product-like codes are widely used in high-speed communication systems since they can be decoded with low-complexity hard decision decoders (HDDs). To meet the growing demand of data rates, enhanced HDDs are required. In this paper, we propose a novel soft-aided HDD (SA-HDD), termed iterative bounded distance decoding with random flipping (iBDD-RF), for product-like codes. In iBDD-RF, the soft reliability of a bit is a weighted sum of the output of bounded distance decoder (BDD) and the channel log-likelihood ratio (LLR). When the amplitude of the soft reliability of a bit is less than a given threshold, it is flipped with a given probability. This random flipping may make the decoder escape from the local optimum. To optimize the threshold and the flipping probability, we derive the density evolution (DE) equations of iBDD-RF for product codes (PCs) and staircase codes (SCs). Our extensive numerical results show that iBDD-RF outperforms iBDD with scaled reliability (iBDD-SR) over the binary-input additive white Gaussian noise (Bi-AWGN) channel. Particularly, for a PC with (255,239,2) Bose-Chaudhuri-Hocquenghem (BCH) code and an SC with (254,230,3) BCH code, iBDD-RF performs about 0.25 dB and 0.28 dB better than iBDD-SR, respectively. © 1972-2012 IEEE.

关键词： Optical fiber communication

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FSMM: An Efficient Matrix Multiplication Accelerator Supporting Flexible Sparsity 24

FSMM: An Efficient Matrix Multiplication Accelerator Support...

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43rd International Conference on Computer-Aided Design, ICCAD 2024

作者： Qiao, Yuxuan Yang, Fan Zhang, Yecheng Xiong, Xiankui Yao, Xiao Yao, Haidong State Key Laboratory of Integrated Chips and Systems Fudan University Shanghai China School of Microelectronics Fudan University Shanghai China State Key Laboratory of Mobile Network and Mobile Multimedia Technology ZTE Corporation Shenzhen China

ISBN: (纸本)9798400710773

Sparse matrix multiplication is a critical operation in deep learning. However, matrix sparsity leads to irregular data flow, which would degrade the efficiency of matrix multiplication. Traditional accelerators, equipped with additional hardware units to address this issue, often experience the issue of low hardware utilization. Furthermore, N : M structured sparsity and corresponding hardware architectures face challenges such as accuracy degradation, limited flexibility, and restricted applicability. In this paper, we propose a Flexible Sparse Matrix Multiplication Accelerator (FSMM), which can improve the efficiency of sparse matrix multiplication through both algorithmic-level and hardware-level optimizations. At the algorithmic level, we propose the matrix-matrix multiplication with block-level outer production and fine-grained matrix reordering algorithm. The algorithm balances the sparsity of each column of a matrix block, which improves matrix compression, balances the load, and speeds up computation. This algorithm reduces storage by 8.2% ~ 85.9%. At the hardware-level, we introduce a flexible architecture for matrix multiplication. It selects the most suitable data path to complete matrix multiplication based on the sparsity of the reordered matrix. FSMM achieves a speedup of 1.90× ~ 16.18× over Systolic Array and 1.70× ~ 2.87× over the existing TSTC approach. © 2024 Copyright is held by the owner/author(s).

关键词： Fast response computer systems

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An Efficient Coherent Integration Method for Highly Maneuvering Target Detection by Exploiting Range-Azimuth Coupling Relationships Between Subsegments

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IEEE Sensors Journal 2025年第9期25卷 15456-15476页

作者： Wan, Jun Jiang, Xinyu Liu, Chengyuan Li, Dong Xie, Xiaoran Sang, Qinglin Chen, Zhanye Chongqing University School of Microelectronics and Communication Engineering Chongqing Key Laboratory of Space Information Network and Intelligent Information Fusion Chongqing400044 China China Academy of Electronics and Information Technology Beijing100041 China State Key Laboratory of Millimeter Waves Institute of Electromagnetic Space Southeast University Nanjing210096 China

Arbitrary-order range migrations (RMs) and Doppler frequency migrations (DFMs) caused by complicated motions of highly maneuvering targets (HMTs) pose challenges for coherent integration (CI) in radar remote sensing and detection applications. Complicated Doppler frequency ambiguity improves the challenges of CI for HMTs. The optimal generalized Radon-Fourier transform (GRFT) suffers from a large computational cost, and nonlinear transform-based methods are affected by severe performance loss. To tackle these difficulties, an efficient segmented CI method for HMT detection via the range-azimuth coupling relationship between subsegments is proposed. First, inspired by the advantage of subaperture processing, a segmentation operation is introduced to remove intrasegment RMs and DFMs. Second, a high-order compensation function is presented to remove the high-order intersegment RMs and DFMs. Third, by exploiting the range-azimuth coupling relationship between subsegments, a residual migration compensation function is used to correct the residual intersegment RM. Thus, a well result of HMT's CI is achieved. The proposed method handles arbitrary-order RMs and DFMs, complex Doppler ambiguity, and ambiguous speed sidelobes (BSSLs) in low signal-to-noise ratio (SNR) circumstances and multitarget cases due to its linear transform property. In comparison to the optimal GRFT, the proposed approach substantially lowers computational cost while showing similar performance. Then, the presented approach can be implemented by parallel processing. It is advantageous to enhance real-time processing efficiency. Several real radar data are analyzed to confirm the effectiveness of the developed method. © 2001-2012 IEEE.

关键词： Signal to noise ratio

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