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Random Staircase Generator Matrix Codes: Coding Theorem, Performance Analysis, and Code Design

IEEE Transactions on information Theory 2025年第5期71卷 3497-3509页

作者： Wang, Qianfan Wang, Yiwen Wang, Yixin Liang, Jifan Ma, Xiao Sun Yat-sen University School of Computer Science Engineering and Guangdong Key Laboratory of Information Security Technology Guangzhou510006 China Sun Yat-sen University School of Systems Science and Engineering Guangzhou510006 China

In this paper, we present a class of codes, referred to as random staircase generator matrix codes (SGMCs), which have staircase-like generator matrices. In the infinite-length region, we prove that the random SGMC is capacity-achieving over binary-input output-symmetric (BIOS) channels. In the finite-length region, we propose the generalized representative ordered statistics decoding with local constraints (LC-ROSD) algorithm for the SGMCs. The most distinguished feature of the SGMCs with LC-ROSD is that the staircase-like matrices enable parallel implementation of the Gaussian elimination (GE), avoiding the serial GE of conventional OSD and supporting a potential low decoding latency, as implied from simulations. To analyze the performance of random SGMCs in the finite-length region, we derive the ensemble weight spectrum and invoke the conventional union bound. We also derive a partially random coding union (RCU) bound, which is tighter than the conventional one and is used as a criterion to design the SGMCs. Staircase-like generator matrices allow us to derive a series of (tighter and tighter) lower bounds based on the second-order Bonferroni inequality with the incremental number of codewords. The numerical results show that the decoding performance can match well with the proposed partially RCU bound for different code rates and different profiles. The numerical results also show that the tailored SGMCs with the LC-ROSD algorithm can approach the finite-length performance bound, outperforming the 5G low-density parity-check (LDPC) codes, 5G polar codes, and Reed-Muller (RM) codes. © 1963-2012 IEEE.

关键词： Decoding

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An overview on IRS-enabled sensing and communications for 6G: architectures, fundamental limits, and joint beamforming designs

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science China(information sciences) 2025年第5期68卷 170-193页

作者： Xianxin SONG Yuan FANG Feng WANG Zixiang REN Xianghao YU Ye ZHANG Fan LIU Jie XU Derrick Wing Kwan NG Rui ZHANG Shuguang CUI School of Science and Engineering (SSE) Shenzhen Future Network of Intelligence Institute (FNii-Shenzhen)and Guangdong Provincial Key Laboratory of Future Networks of Intelligence The Chinese University of Hong Kong Department of Electrical Engineering City University of Hong Kong School of Information Engineering Guangdong University of Technology Key Laboratory of Wireless-Optical Communications Chinese Academy of Sciences School of Information Science and Technology University of Science and Technology of China Computer School Beijing Information Science and Technology University National Mobile Communications Research Laboratory School of Information Science and Engineering Southeast University School of Electrical Engineering and Telecommunications University of New South Wales School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Department of Electrical and Computer Engineering National University of Singapore

This study presents an overview on intelligent reflecting surface(IRS)-enabled sensing and communication for the forthcoming sixth-generation(6G) wireless networks, in which IRSs are strategically deployed to proactively reconfigure wireless environments to improve both sensing and communication(S&C) performance. First, we exploit a single IRS to enable wireless sensing in the base station's(BS's) non-line-of-sight(NLoS) area. In particular, we present three IRS-enabled NLoS target sensing architectures with fully-passive, semi-passive, and active IRSs, respectively. We compare their pros and cons by analyzing the fundamental sensing performance limits for target detection and parameter estimation. Next, we consider a single IRS to facilitate integrated sensing and communication(ISAC), in which the transmit signals at the BS are used for achieving both S&C functionalities, aided by the IRS through reflective beamforming. We present joint transmit signal and receiver processing designs for realizing efficient ISAC, and jointly optimize the transmit beamforming at the BS and reflective beamforming at the IRS to balance the fundamental performance tradeoff between S&C. Furthermore, we discuss multi-IRS networked ISAC, by particularly focusing on multi-IRS-enabled multi-link ISAC, multi-region ISAC, and ISAC signal routing, respectively. Finally, we highlight various promising research topics in this area to motivate future work.

关键词： integrated sensing and communication (ISAC) intelligent reflecting surface (IRS) non-line-of-sight (NLoS) sensing sensing and communication tradeoff

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Multifrequency measurement system with no frequency ambiguity based on two frequency-space mappings

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Optical engineering 2025年第3期64卷

作者： Zhang, Jiahong Ma, Di Li, Peiqi Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming China Kunming University of Science and Technology Yunnan Key Laboratory of Computer Technology Applications Kunming China

Multifrequency measurement system with no frequency ambiguity based on two frequency-space mappings has been designed and investigated. By simultaneously mapping the unknown frequencies with a certain frequency shift onto non-flat optical frequency combs (OFCs) and obtaining two beat frequency signals using two balanced photodetectors (BPD), the channel where the measured signal is located can be determined, achieving instantaneous measurement of multifrequencies while effectively addressing five possible types of frequency ambiguity. Simulation results indicate that when the comb line spacing of the OFC is designed as 2 GHz, the measurement range of the system is 0.1 to 30 GHz, with a measurement error within ±1 MHz and a measurement resolution of 2.7 MHz. Furthermore, by adjusting the comb line spacing of the OFC to 4 GHz, the frequency measurement range can be extended to 60 GHz. © 2025 Society of Photo-Optical Instrumentation Engineers (SPIE)

关键词： Electric frequency measurement

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Global Navigation Satellite System Reflectometry specular point positioning method based on reflection geometric model: Suitable for land and ocean applications

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Journal of Applied Remote Sensing 2025年第1期19卷

作者： Li, Shuaishuai He, Shanbao Cheng, Xing Wang, Feng Xie, Heng Pang, Jingjing Cai, Min Beijing Information Science and Technology University Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing China Beihang University School of Electronic and Information Engineering Beijing China Beijing Information Science and Technology University School of Information and Communication Engineering Beijing China

The accurate positioning of the specular point of the spaceborne global navigation satellite system reflectometry (GNSS-R) receiver is a key step in using GNSS-R technology for geophysical parameter retrieval. As GNSS-R applications expand across diverse environments ranging from land and oceans to glaciers, traditional geometric positioning accuracy is no longer sufficient to meet the demands of these varied applications. Specifically, positioning algorithms must not only facilitate real-time spaceborne processing but also adapt to fluctuating surface conditions, all while sustaining high levels of accuracy and efficiency. In response to these demands, we propose a positioning algorithm tailored for spaceborne GNSS-R specular points across various surface environments. The proposed algorithm integrates actual surface height data by leveraging surface models for localized terrain fitting. It employs a regional grid traversal method, guided by geographic positioning criteria, to accurately search for specular points that satisfy specific conditions. Considering the impact of initial position accuracy on traversal speed, we developed an ellipsoidal reflection geometric model based on the unique properties of the ellipsoid. This model facilitates the swift, non-iterative determination of a high-precision initial position for specular points. Experimental data indicate that our proposed approach reduces the Euclidean distance error of the initial position by ~87.5% and enhances grid traversal efficiency by a factor of more than eight times. To verify the robustness of the proposed method, this paper conducted multiple experiments in both ocean and land scenarios, including case studies in the Qinghai-Tibet Plateau region. The findings highlight that the normal vector angle analysis criterion offers superior reliability in complex terrains, positioning it as the optimal criterion for the positioning of specular points. © 2025 Society of Photo-Optical Instrumentation Engi

关键词： Global positioning system

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Diffusion Models Meet Network Management: Improving Traffic Matrix Analysis with Diffusion-Based Approach

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IEEE Transactions on Network and Service Management 2025年第2期22卷 1259-1275页

作者： Yuan, Xinyu Qiao, Yan Wei, Zhenchun Zhang, Zeyu Li, Minyue Zhao, Pei Hu, Rongyao Li, Wenjing Hefei University of Technology School of Computer Science and Information Engineering China Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology China Macau University of Science and Technology Faculty of Information Technology China

Due to network operation and maintenance relying heavily on network traffic monitoring, traffic matrix analysis has been one of the most crucial issues for network management related tasks. However, it is challenging to reliably obtain the precise measurement in computer networks because of the high measurement cost, and the unavoidable transmission loss. Although some methods proposed in recent years allowed estimating network traffic from partial flow-level or link-level measurements, they often perform poorly for traffic matrix estimation nowadays. Despite strong assumptions like low-rank structure and the prior distribution, existing techniques are usually task-specific and tend to be significantly worse as modern network communication is extremely complicated and dynamic. To address the dilemma, this paper proposed a diffusion-based traffic matrix analysis framework named Diffusion-TM, which leverages problem-agnostic diffusion to notably elevate the estimation performance in both traffic distribution and accuracy. The novel framework not only takes advantage of the powerful generative ability of diffusion models to produce realistic network traffic, but also leverages the denoising process to unbiasedly estimate all end-to-end traffic in a plug-and-play manner under theoretical guarantee. Moreover, taking into account that compiling an intact traffic dataset is usually infeasible, we also propose a two-stage training scheme to make our framework be insensitive to missing values in the dataset. With extensive experiments with real-world datasets, we illustrate the effectiveness of Diffusion-TM on several tasks. Moreover, the results also demonstrate that our method can obtain promising results even with 5% known values left in the datasets. © 2004-2012 IEEE.

关键词： Level measurement

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An optical carbon nanotube fibre probe for measurement of nano structures with large aspect ratio

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Nano Research 2025年第3期18卷 436-443页

作者： Weihao Tao Shuhao Zhao Hanjin Dong Ze Zhang Peirui Ji Shenghan Qin Wenbo Hu Jinlong Zhu Renjie Zhou Shuming Yang State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong UniversityXi’an 710049China State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Department of Biomedical Engineering The Chinese University of Hong KongHong KongChina

With the development of imaging and measurement technologies,scanning near-field optical microscopy(SNOM)has achieved high signal-to-noise *** resolution of a fibre probe-based SNOM system is capable of reaching 10 ***,SNOM applications are presently constrained to the measurement of near-field optical information to relatively straightforward structures,including quantum dots,carbon nanotubes,graphene,and so *** geometry of conventional fibre probes,with tips at an angle of 30°-60°,presents a challenge for accurately imaging complex surface *** paper proposes a carbon nanotube composite fibre probe(CNT-FP)with a large aspect *** key point is that a carbon nanotube bundle is composited at the tip of conventional surface plasmon polaritons fibre probes(SPPs-FP),which are the fibre probes coated with gold film to excite the *** coupling,propagation,and focusing effects of SPPs on the carbon nanotube bundle are ***-FPs have been fabricated and applied to measure a grating with the depth of 400 nm and the width of 400 *** experimental results show that the measurement accuracy and imaging quality of CNT-FP are nearly one order of magnitude higher than that of conventional SPPs-FP,as evidenced by evaluation criteria such as line roughness and volatility ***,it achieves an optical resolution of 72.1 nm in the measurements of a nano structure with large aspect *** provides an effective solution of measuring structures with larger aspect ratios.

关键词： carbon nanotubes fibre optic probes surface plasmon polaritons nano-focusing large aspect ratio

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Hypoxia-triggered photothermal/drug combination therapy of tumors using a perylene diimide molecular capsule

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science China Chemistry 2025年第3期68卷 1009-1017页

作者： Fei Yang Guo Wang Kecheng Huang Yanqing Xu Xiao Feng Weizhi Wang Wei Wei Key Laboratory of Medical Molecule Science and Pharmaceutics Engineering Ministry of Industry and Information TechnologySchool of Chemistry and Chemical EngineeringBeijing Institute of TechnologyBeijing 100081China Beijing Key Laboratory for Optical Materials and Photonic Devices Department of ChemistryCapital Normal UniversityBeijing 100048China

Hypoxia is a common characteristic of tumors and associated with poor outcome in most cancer types,thus hypoxia-triggered combined therapeutic systems with well-defined structure hold significant promise for achieving specific and effective tumor ***,a water-soluble perylene diimide(PDI)cyclophane“Gemini Box”(GBox-1^(4+))is demonstrated as both a hypoxia-responsive photothermal agent and a drug capsule for tumor-specific combination ***,owing to the covalent enclosure of PDI chromophore by double-sided molecular straps,GBox-1^(4+)can significantly stabilize labile PDI radical anions generated through bioreduction at the lesion site of hypoxic tumors,leading to high-efficiency near-infrared photothermal ablation of ***,GBox-1^(4+)can act as a molecular capsule to bind water-insoluble antitumor drugs camptothecin and hydroxycamptothecin in 1:1 host-guest stoichiometry with high affinities,greatly enhancing the water solubility of ***,such drug-loading cyclophane system as a hypoxia-activated photothermal/drug combined therapeutic platform exhibits more effective inhibition of tumor growth than the single treatment under identical *** study significantly extends the application range of host-guest cyclophane systems and opens a promising avenue to structurally uniform combined therapeutic agents against hypoxic tumors with improved specificity.

关键词： hypoxia-responsive photothermal agent cyclophanes host-guest system near-infrared combination therapy

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FDCPNet:feature discrimination and context propagation network for 3D shape representation

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虚拟现实与智能硬件(中英文) 2025年第1期7卷 83-94页

作者： Weimin SHI Yuan XIONG Qianwen WANG Han JIANG Zhong ZHOU State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China

Background Three-dimensional(3D)shape representation using mesh data is essential in various applications,such as virtual reality and simulation *** methods for extracting features from mesh edges or faces struggle with complex 3D models because edge-based approaches miss global contexts and face-based methods overlook variations in adjacent areas,which affects the overall *** address these issues,we propose the Feature Discrimination and Context Propagation Network(FDCPNet),which is a novel approach that synergistically integrates local and global features in mesh *** FDCPNet is composed of two modules:(1)the Feature Discrimination Module,which employs an attention mechanism to enhance the identification of key local features,and(2)the Context Propagation Module,which enriches key local features by integrating global contextual information,thereby facilitating a more detailed and comprehensive representation of crucial areas within the mesh *** Experiments on popular datasets validated the effectiveness of FDCPNet,showing an improvement in the classification accuracy over the baseline ***,even with reduced mesh face numbers and limited training data,FDCPNet achieved promising results,demonstrating its robustness in scenarios of variable complexity.

关键词： 3D shape representation Mesh model MeshNet Feature discrimination Context propagation

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Power Allocation Based on Federated Multiagent Deep Reinforcement Learning for NOMA Maritime Networks

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IEEE Internet of Things Journal 2025年第9期12卷 12869-12884页

作者： He, Jiayi Liu, Zhiyong Zhang, Yakai Jin, Zihao Zhang, Qinyu School of Information Science and Engineering Shandong Weihai264209 China Shandong Provincial Key Laboratory of Marine Electronic Information and Intelligent Unmanned Systems Key Laboratory of Cross-Domain Synergy and Comprehensive Support for Unmanned Marine Systems of the Ministry of Industry and Information Technology Shandong Weihai264209 China Communication Engineering Research Center Guangdong Shenzhen518055 China Peng Cheng Laboratory Shenzhen518055 China

The absence of established communication infrastructures at sea presents a significant hurdle for the development of the Internet of Things (IoT) in maritime environments. In this article, we propose a novel solution: a nonorthogonal multiple access (NOMA) maritime network employing power allocation facilitated by federated multiagent deep reinforcement learning (DRL). Conventional single-agent DRL algorithms encounter challenges, such as dimensionality explosion in real-world scenarios. We address this issue by extending these algorithms to incorporate multiple agents. Furthermore, to mitigate risks associated with centralized training, such as data leakage and network attacks, we adopt a federated learning (FL) framework for distributed training across multiple agents. By uploading only select parameters during training and keeping data locally, FL not only enhances algorithm convergence speed but also bolsters data privacy. Specifically, we introduce the federated multiagent deep Q-network (FLMADQN) algorithm tailored for power allocation in NOMA maritime networks. Our algorithm aims to maximize system throughput, optimize data transfer rates, and expedite convergence. Through extensive computer simulations, we validate the efficacy of our proposed approach. Results demonstrate that the FLMADQN algorithm significantly outperforms the traditional DRL algorithm, DQN, in NOMA maritime environments, improving average system throughput by 20.12%, peak system throughput by 45.10%, and system spectral efficiency by 48.33%. Moreover, FLMADQN exhibits a twofold increase in convergence speed compared to MADQN without FL and is 2.5 times faster than DQN. Our findings underscore the potential of federated multiagent DRL in advancing communication systems for maritime IoT applications. © 2014 IEEE.

关键词： Federated learning

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Listen With Seeing: Cross-Modal Contrastive Learning for Audio-Visual Event Localization

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IEEE Transactions on Multimedia 2025年 27卷 2650-2665页

作者： Sun, Chao Chen, Min Zhu, Chuanbo Zhang, Sheng Lu, Ping Chen, Jincai Huazhong University of Science and Technology Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Engineering Research Center of Data Storage Systems and Technology Ministry of Education of China School of Computer Science and Technology Wuhan430074 China South China University of Technology School of Computer Science and Engineering Guangzhou510640 China Pazhou Laboratory Guangzhou510640 China

In real-world physiological and psychological scenarios, there often exists a robust complementary correlation between audio and visual signals. Audio-Visual Event Localization (AVEL) aims to identify segments with Audio-Visual Events (AVEs) that contain both audio and visual tracks in unconstrained videos. Prior studies have predominantly focused on audio-visual cross-modal fusion methods, overlooking the fine-grained exploration of the cross-modal information fusion mechanism. Moreover, due to the inherent heterogeneity of multi-modal data, inevitable new noise is introduced during the audio-visual fusion process. To address these challenges, we propose a novel Cross-modal Contrastive Learning Network (CCLN) for AVEL, comprising a backbone network and a branch network. In the backbone network, drawing inspiration from physiological theories of sensory integration, we elucidate the process of audio-visual information fusion, interaction, and integration from an information-flow perspective. Notably, the Self-constrained Bi-modal Interaction (SBI) module is a bi-modal attention structure integrated with audio-visual fusion information, and through gated processing of the audio-visual correlation matrix, it effectively captures inter-modal correlation. The Foreground Event Enhancement (FEE) module emphasizes the significance of event-level boundaries by elongating the distance between scene events during training through adaptive weights. Furthermore, we introduce weak video-level labels to constrain the cross-modal semantic alignment of audio-visual events and design a weakly supervised cross-modal contrastive learning loss (WCCL Loss) function, which enhances the quality of fusion representation in the dual-branch contrastive learning framework. Extensive experiments conducted on the AVE dataset for both fully supervised and weakly supervised event localization, as well as Cross-Modal Localization (CML) tasks, demonstrate the superior performance of our model compa

关键词： information fusion

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