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Linearized microwave downconversion link based on fast and intelligent impairment equalization for noncooperative systems

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Chinese Optics Letters 2023年第2期21卷 143-147页

作者：陈智宇钟欣蒋林徐嘉鑫刘静娴盘艳周涛 Key Laboratory of Science and Technology on Electronic Information Control Chengdu 610029China Center for Information Photonics&Communications School of Information Science&TechnologySouthwest Jiaotong UniversityChengdu 610031China Science and Technology on Communication Security Laboratory Institute of Southwestern CommunicationChengdu 610041China

We experimentally demonstrated the use of intelligent impairment equalization(IIE)for microwave downconversion link linearization in noncooperative *** an equalizer is realized based on an artificial neural network(ANN).Once the training process is completed,the inverse link transfer function can be *** the inverse transformation for the detected signal after transmission,the third-order intermodulation distortion components are suppressed significantly without requiring any prior information from an input RF ***,fast training speed is achieved,since the configuration of ANN-based equalizer is *** results show that the spurious-free dynamic range of the proposed link is improved to 106.5 dB·Hz^(2/3),which is 11.3 dB higher than that of a link without ***,the training epochs reduce to only five,which has the potential to meet the practical engineering requirement.

关键词： microwave photonics linearized downconversion link intelligent impairment equalization artificial neural network

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Review of data security within energy blockchain:A comprehensive analysis of storage,management,and utilization

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High-Confidence Computing 2024年第3期4卷 82-102页

作者： Yunhua He Zhihao Zhou Yan Pan Fahui Chong Bin Wu Ke Xiao Hong Li School of Information Science and Technology North China University of TechnologyBeijing 100144China China Industrial Control Systems Cyber Emergency Response Team Beijing 100040China Key Laboratory in Blockchain and Data Security by Ministry of Industry and Information Technology Beijing 100040China Institute of Information Engineering Chinese Academy of Sciences Beijing 100195China

Energy systems are currently undergoing a transformation towards new paradigms characterized by decarbonization,decentralization,democratization,and *** this evolving context,energy blockchain,aiming to enhance efficiency,transparency,and security,emerges as an integrated technological solution designed to address the diverse challenges in this *** security is essential for the reliable and efficient functioning of energy *** pressing need to address challenges related to secure data storage,effective data management,and efficient data utilization is increasingly *** paper offers a comprehensive survey of academic discourse on energy blockchain data security over the past five years,adopting an all-encompassing perspective that spans data storage,management,and *** work systematically evaluates and contrasts the strengths and weaknesses of various research ***,this paper proposes an integrated hierarchical on-chain and off-chain security energy blockchain architecture,specifically designed to meet the complex security requirements of multi-blockchain business ***,this paper identifies key directions for future research,particularly in advancing the integration of storage,management,and utilization of energy blockchain data security.

关键词： Energy blockchain Data security Storage Management Utilization

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Waveform Design for High-Order QAM Faster-Than-Nyquist Transmission in the Presence of Phase Noise

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IEEE Transactions on Wireless communications 2022年第1期21卷 2-17页

作者： Wen, Shan Liu, Guanghui Liu, Chengxiang Qu, Huiyang Tian, Miao Chen, Yan School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China School of Cyberspace Security University of Science and Technology of China Hefei China

The state-of-the-art radio-frequency (RF) devices limit the deployment of extremely high-order quadrature amplitude modulation (QAM) formats (e.g., 16384-QAM) to meet the high-capacity demand on microwave backhaul links. This paper turns to faster-than-Nyquist (FTN) transmission using lower-order constellations and lower-cost RF devices as a solution to the demand. To realize low-complexity interference cancellation, we pre-equalize the FTN-induced inter-symbol interference at the transmitter by using Tomlinson-Harashima precoding (THP), while at the receiver suppressing the phase noise (PHN) generated by the RF local oscillators with pilot symbol assisted approaches. However, the THP may distort the pilots, which degrades the performance of PHN compensation. To resolve this problem, we propose two pilot designs that are distortion-free to precisely estimate the PHN samples. Moreover, we derive a closed-form expression of the symbol detection signal-to-noise ratio (SNR), in terms of the THP-FTN waveform parameters. With the SNR expression, a waveform optimization procedure is developed to maximize the SNR and enhance the achievable FTN capacity. The proposed scheme is validated in the simulated platform of 4096-QAM microwave link. The results demonstrate that the FTN signaling achieves the system capacity equivalent to that of the 16384-QAM Nyquist signaling with an SNR gain of 5.8 dB. © 2002-2012 IEEE.

关键词： Phase noise

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Federated Deep Q-network: A Dynamic Task Allocation Strategy for UAV-Assisted Cell-Free Networks 4th

Federated Deep Q-network: A Dynamic Task Allocation Strategy...

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4th International Conference on Frontiers of Electronics, information and Computation Technologies, ICFEICT 2024

作者： He, Jian Pan, Chunyu Wang, Jincheng Lu, Cunbo Chen, Shuo The Key Laboratory of Information and Communication Systems Ministry of Information Industry and the Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100101 China Information Science Academy of China Electronics Technology Group Corporation Beijing China

ISBN: (纸本)9789819653133

A dynamic resource allocation problem for jointly optimizing access point selection and task offloading is proposed for a mobile edge computing system in an unmanned aerial vehicle (UAV)-assisted cell-free (CF) networks for the purpose of delay reduction in an urban scenario. On the one hand, given that various resources are coupled in the optimization problem, exhibiting non-convex traits and thus cannot be directly separated. On the other hand, to expedite algorithm convergence while ensuring user data security, we propose a method that combines the federated learning (FL) framework with deep reinforcement learning (DRL). Specifically, we introduce a federated deep Q network (F-DQN) algorithm to execute the dynamic resource allocation strategy for the proposed problem. Simulation results show that the proposed algorithm has better convergence performance than traditional Q-learning and deep Q network (DQN), and the proposed strategy has lower system delay with a maximum gain of 60.5% compared to other baseline strategies. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Deep reinforcement learning

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Optimization of the Internet of Remote Things Data Acquisition Based on Satellite UAV Integrated Network

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China communications 2023年第7期20卷 15-28页

作者： Yuanyuan Yao Dengyang Dong Sai Huang Chunyu Pan Shuo Chen Xuehua Li Key Laboratory of Information and Communication Systems Ministry of Information IndustryBeijing Information Science and Technology UniversityBeijing 100101China Key Laboratory of Modern Measurement&Control Technology Ministry of EducationBeijing Information Science and Technology UniversityBeijing 100101China Key Laboratory of Universal Wireless Communications Ministry of EducationBeijing University of Posts and TelecommunicationsBeijing 100876China

In order to achieve dependable and efficient data acquisition and transmission in the Internet of Remote Things(IoRT),we investigate the optimization scheme of IoRT data acquisition under the unmanned aerial vehicle(UAV)-low earth orbit(LEO)satellite integrated space-air-ground network,in which the UAV acquires data from massive Internet of Things(IoT)devices in special *** combine with the actual scenario,we consider two different data types,that is,delay-sensitive data and delay-tolerant data,the transmission mode is accordingly divided into two *** delay-sensitive data,the data will be transmitted via the LEO satellite relay to the data center(DC)in *** delay-tolerant data,the UAV will store and carry the data until the acquisition is completed,and then return to *** to nonconvexity and complexity of the formulated problem,a multi-dimensional optimization Rate Demand based Joint Optimization(RDJO)algorithm is *** algorithm first uses successive convex approximation(SCA)technology to solve the non-convexity,and then based on the block coordinate descent(BCD)method,the data acquisition efficiency is maximized by jointly optimizing UAV deployment,the bandwidth allocation of IoRT devices,and the transmission power of the ***,the proposed RDJO algorithm is compared with the conventional *** consequences demonstrate that the efficiency of IoRT data acquisition can be greatly improved by multi-parameter optimization of the bandwidth allocation,UAV deployment and the transmission power.

关键词： Internet of Remote Things dataacquisi-tion unmanned aerial vehicle LEO satellite

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Cognitive Jammer Time Resource Scheduling With Imperfect information via Fuzzy Q-Learning

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IEEE Transactions on Aerospace and Electronic Systems 2025年第3期61卷 7422-7434页

作者： Gan, Linchuan Xiong, Kui Liao, Maosen Yu, Xianxiang Cui, Guolong University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology Beijing100089 China UESTC Shenzhen Institute for Advanced Study Shenzhen518038 China

Effective strategy generation of the jammer with inaccurate or undetermined information for combating the radar system is a challenging problem, and the relevant research is scarce in existing work. This article aims at exploring this promising topic and proposing a transmitting time slot scheduling strategy generation method for the cognitive jammer with imperfect time-matching information based on fuzzy reinforcement learning. First, the interaction between the jammer and environment is modeled as a Markov decision process (MDP) with uncertain state and continuous action, in which the goal of the jammer in interaction is to maximize accumulated discount pulse transmitting time slot jamming probability. Then, the uncertain pulse repetition intervals (PRIs) of the radar signal are inferred using the fuzzy inference system (FIS), where the inferred reward is evaluated by the correntropy of the inferred radar PRI and the previously measured one, thus presenting the fuzzy Q-learning based time scheduling (TSFQL) algorithm. Finally, numerical simulations in typical scenarios are performed to illustrate the effectiveness and superiority of the TSFQL algorithm over conventional methods. © 1965-2011 IEEE.

关键词： Markov processes

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Ship Detection and Recognition Based on Improved YOLOv7

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Computers, Materials & Continua 2023年第7期76卷 489-498页

作者： Wei Wu Xiulai Li Zhuhua Hu Xiaozhang Liu School of Information and Communication Engineering Hainan UniversityHaikou570228China School of Cyberspace Security Hainan UniversityHaikou570228China School of Computer Science and Technology Hainan UniversityHaikou570228China

In this paper,an advanced YOLOv7 model is proposed to tackle the challenges associated with ship detection and recognition tasks,such as the irregular shapes and varying sizes of *** improved model replaces the fixed anchor boxes utilized in conventional YOLOv7 models with a set of more suitable anchor boxes specifically designed based on the size distribution of ships in the *** paper also introduces a novel multi-scale feature fusion module,which comprises Path Aggregation Network(PAN)modules,enabling the efficient capture of ship features across different ***,data preprocessing is enhanced through the application of data augmentation techniques,including random rotation,scaling,and cropping,which serve to bolster data diversity and *** distribution of positive and negative samples in the dataset is balanced using random sampling,ensuring a more accurate representation of real-world *** experimental results demonstrate that the proposed method significantly outperforms existing state-of-the-art approaches in terms of both detection accuracy and robustness,highlighting the potential of the improved YOLOv7 model for practical applications in the maritime domain.

关键词： Ship position prediction target detection YOLOv7 data augmentation techniques

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Energy leakage in OFDM sparse channel estimation:The drawback of OMP and the application of image deblurring

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Digital communications and Networks 2024年第5期10卷 1280-1288页

作者： Gang Qiao Xizhu Qiang Lei Wan Hanbo Jia Acoustic Science and Technology Laboratory Harbin Engineering UniversityHarbin 150001China Key Laboratory of Marine Information Acquisition and Security(Harbin Engineering University) Ministry of Industry and Information TechnologyHarbin 150001China College of Underwater Acoustic Engineering Harbin Engineering UniversityHarbin 150001China School of Informatics Xiamen UniversityXiamen 361005China Key Laboratory of Underwater Acoustic Communication and Marine Information Technology(Xiamen University) Ministry of EducationXiamen 361005China

In this paper,in order to reduce the energy leakage caused by the discretized representation in sparse channel estimation for Orthogonal Frequency Division Multiplexing(OFDM)systems,we systematically have analyzed the optimal locations of atoms with discrete delays for each path reconstruction from the perspective of linear fitting ***,we have investigated the adverse effects of the non-ideal inner product function on the iteration in one of the most widely used channel estimation method,Orthogonal Matching Pursuit(OMP).The study shows that the distance between the selected atoms for each path in OMP can be larger than the sampling interval,which prevents OMP-based methods from achieving better *** overcome this drawback,the image deblurring-based channel estimation method,in which the channel estimation problem is analogized to one-dimensional image deblurring,was proposed to improve the large compensation distance of traditional *** advantage of the proposed method was validated by the results of numerical simulation and sea trial data decoding.

关键词： Sparse channel estimation Orthogonal matching pursuit(OMP) Orthogonal frequency division multiplexing (OFDM) Linear fitting Image deblurring

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Precipitation Retrieval of FY-3D MWHTS and MWRI Data Based on Light Gradient Boosting Model

Precipitation Retrieval of FY-3D MWHTS and MWRI Data Based o...

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2024 Photonics and Electromagnetics Research Symposium, PIERS 2024

作者： Lv, Yanfang Zhang, Lanjie Zhang, Yifan Zhang, Biao Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University Beijing100101 China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100101 China

ISBN: (纸本)9798350375909

As an essential component of the earth system, precipitation plays a crucial role in the regional and global water cycle. This paper uses observations from the Fengyun-3D microwave humidity and temperature sounder and microwave radiation imager, as well as Integrated Multi-satellite Retrievals for GPM (IMERG), to establish a precipitation retrieval model based on the light gradient boosting model (LGBM). Using IMERG as the comparison data, the performance of precipitation identification with the LGBM-based precipitation retrieval model is as follows: accuracy is 0.9302, probability of detection is 0.7683, false alarm rate is 0.3529, and critical success index is 0.5414. The performance of precipitation estimation is also evaluated, with a correlation coefficient of 0.7536, a mean absolute error of 0.9119, and a mean squared error of 3.9506. In summary, this study achieves good performance in precipitation identification and estimation by the LGBM model. © 2024 IEEE.

关键词： Microwave acoustic devices

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information Freshness-Oriented Trajectory Planning and Resource Allocation for UAV-Assisted Vehicular Networks

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China communications 2023年第5期20卷 244-262页

作者： Hao Gai Haixia Zhang Shuaishuai Guo Dongfeng Yuan School of Control Science and Engineering Shandong UniversityJinan 250061China Shandong Key Laboratory of Wireless Communication Technologies Shandong UniversityJinan 250061China China Academy of Information and Communication Technology(CAICT) Beijing 100191China

In this paper,multi-UAV trajectory planning and resource allocation are jointly investigated to improve the information freshness for vehicular networks,where the vehicles collect time-critical traffic information by on-board sensors and upload to the UAVs through their allocated spectrum *** adopt the expected sum age of information(ESAoI)to measure the network-wide information *** is jointly affected by both the UAVs trajectory and the resource allocation,which are coupled with each other and make the analysis of ESAoI *** tackle this challenge,we introduce a joint trajectory planning and resource allocation procedure,where the UAVs firstly fly to their destinations and then hover to allocate resource blocks(RBs)during a *** on this procedure,we formulate a trajectory planning and resource allocation problem for ESAoI *** solve the mixed integer nonlinear programming(MINLP)problem with hybrid decision variables,we propose a TD3 trajectory planning and Round-robin resource allocation(TTPRRA).Specifically,we exploit the exploration and learning ability of the twin delayed deep deterministic policy gradient algorithm(TD3)for UAVs trajectory planning,and utilize Round Robin rule for the optimal resource *** TTP-RRA,the UAVs obtain their flight velocities by sensing the locations and the age of information(AoI)of the vehicles,then allocate the RBs to the vehicles in a descending order of AoI until the remaining RBs are not sufficient to support another successful *** results demonstrate that TTP-RRA outperforms the baseline approaches in terms of ESAoI and average AoI(AAoI).

关键词： information freshness for vehicular networks multi-UAV trajectory planning resource allocation deep reinforcement learning

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