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A Practical Approach for Missing Wireless Sensor Networks Data Recovery

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China communications 2024年第5期21卷 202-217页

作者： Song Xiaoxiang Guo Yan Li Ning Ren Bing The college of communications engineering Army Engineering University of PLANanjing 210007China The 63891 Unit of PLA Luoyang 471000China

In wireless sensor networks(WSNs),the performance of related applications is highly dependent on the quality of data collected.Unfortunately,missing data is almost inevitable in the process of data acquisition and transmission.Existing methods often rely on prior information such as low-rank characteristics or spatiotemporal correlation when recovering missing WSNs data.However,in realistic application scenarios,it is very difficult to obtain these prior information from incomplete data sets.Therefore,we aim to recover the missing WSNs data effectively while getting rid of the perplexity of prior information.By designing the corresponding measurement matrix that can capture the position of missing data and sparse representation matrix,a compressive sensing(CS)based missing data recovery model is established.Then,we design a comparison standard to select the best sparse representation basis and introduce average cross-correlation to examine the rationality of the established model.Furthermore,an improved fast matching pursuit algorithm is proposed to solve the model.Simulation results show that the proposed method can effectively recover the missing WSNs data.

关键词： average cross correlation matching pursuit missing data wireless sensor networks

Radiation build-up and dissipation in Raman random fiber laser

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Science China(Information Sciences) 2024年第1期67卷 254-260页

作者： Shengtao LIN Zinan WANG Jiaojiao ZHANG Pan WANG Han WU Yifei QI Key Laboratory of Optical Fiber Sensing and communications University of Electronic Science and Technology of China college of Electronics and Information engineering Sichuan University

Raman random fiber laser(RRFL) is a complex physical system that arises from the distributed Raman amplification and the intrinsic stochasticity of fiber scattering.The analysis of the underlying lightwave kinetics at steady state has been the focus of considerable interest.However,the transient state,such as the RRFL build-up and dissipation,is particularly important for revealing the lightwave interaction process.Here,we investigate for the first time the RRFL dynamics at the transient state and track the RRFL temporal and spectral evolution theoretically and experimentally.Particularly,with the contribution of random distributed feedback,RRFL build-up exhibits continuous Verhulst logistic growth curves without cavity-related features,which is significantly different from the step-like growth curve of conventional fiber lasers.Furthermore,the radiation build-up duration is inversely related to the pump power,and the spectral evolution of the RRFL undergoes two phases,i.e.,from spectral density increase to spectral broadening.From the steady state to the pump switch-off state,the RRFL output power dissipates immediately,and the remaining Stokes lightwave from the Rayleigh scattering will gradually disappear after one round trip.This work provides new insights into the transient dynamic features of the RRFL.

关键词： random fiber laser stimulated Raman scattering transient phenomenon nonlinear optics łinebreak biological growth dynamics

Dynamic Update Scheme of Spectrum Information Based on Spectrum Opportunity Incentive in the Database-Assisted Dynamic Spectrum Management

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China communications 2024年第3期21卷 75-90页

作者： Zhang Yu Chen Yong He Panfeng Cai Yueming Sixty-third Research Institute National University of Defense TechnologyNanjing 210007China college of communications engineering Army of Engineering UniversityNanjing 210007China

To solve the problem of delayed update of spectrum information(SI) in the database assisted dynamic spectrum management(DB-DSM), this paper studies a novel dynamic update scheme of SI in DB-DSM. Firstly, a dynamic update mechanism of SI based on spectrum opportunity incentive is established, in which spectrum users are encouraged to actively assist the database to update SI in real time. Secondly, the information update contribution(IUC) of spectrum opportunity is defined to describe the cost of accessing spectrum opportunity for heterogeneous spectrum users, and the profit of SI update obtained by the database from spectrum allocation. The process that the database determines the IUC of spectrum opportunity and spectrum user selects spectrum opportunity is mapped to a Hotelling model. Thirdly, the process of determining the IUC of spectrum opportunities is further modelled as a Stackelberg game by establishing multiple virtual spectrum resource providers(VSRPs) in the database. It is proved that there is a Nash Equilibrium in the game of determining the IUC of spectrum opportunities by VSRPs. Finally, an algorithm of determining the IUC based on a genetic algorithm is designed to achieve the optimal IUC. The-oretical analysis and simulation results show that the proposed method can quickly find the optimal solution of the IUC, and ensure that the spectrum resource provider can obtain the optimal profit of SI update.

关键词： database-assisted dynamic spectrum management Hotelling information updating contribution spectrum information updating Stackelberg

Distributed Matching Theory-Based Task Re-Allocating for Heterogeneous Multi-UAV Edge Computing

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China communications 2024年第1期21卷 260-278页

作者： Yangang Wang Xianglin Wei Hai Wang Yongyang Hu Kuang Zhao Jianhua Fan college of communications engineering Army Engineering University of PLANanjing 210007China The Sixty-Third Research Institute National University of Defense TechnologyNanjing 210007China

Many efforts have been devoted to efficient task scheduling in Multi-Unmanned Aerial Vehicle(UAV)edge computing.However,the heterogeneity of UAV computation resource,and the task re-allocating between UAVs have not been fully considered yet.Moreover,most existing works neglect the fact that a task can only be executed on the UAV equipped with its desired service function(SF).In this backdrop,this paper formulates the task scheduling problem as a multi-objective task scheduling problem,which aims at maximizing the task execution success ratio while minimizing the average weighted sum of all tasks’completion time and energy consumption.Optimizing three coupled goals in a realtime manner with the dynamic arrival of tasks hinders us from adopting existing methods,like machine learning-based solutions that require a long training time and tremendous pre-knowledge about the task arrival process,or heuristic-based ones that usually incur a long decision-making time.To tackle this problem in a distributed manner,we establish a matching theory framework,in which three conflicting goals are treated as the preferences of tasks,SFs and UAVs.Then,a Distributed Matching Theory-based Re-allocating(DiMaToRe)algorithm is put forward.We formally proved that a stable matching can be achieved by our proposal.Extensive simulation results show that Di Ma To Re algorithm outperforms benchmark algorithms under diverse parameter settings and has good robustness.

关键词： edge computing heterogeneity matching theory service function unmanned aerial vehicle

Identity-based searchable attribute signcryption in lattice for a blockchain-based medical system

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Frontiers of Information Technology & Electronic engineering 2024年第3期25卷 461-471页

作者： Huifang YU Xiaoping BAI School of Cyberspace Security Xi'an University of Posts&TelecommunicationsXi'an 710121China School of Information engineering Qinghai Communications Technical CollegeXining 810003China

Electronic healthcare systems can offer convenience but face the risk of data forgery and information leakage.To solve these issues,we propose an identity-based searchable attribute signcryption in lattice for a blockchain-based medical system(BCMS-LIDSASC).BCMS-LIDSASC achieves decentralization and anti-quantum security in the blockchain environment,and provides fine-grained access control and searchability.Furthermore,smart contracts are used to replace traditional trusted third parties,and the interplanetary file system(IPFS)is used for ciphertext storage to alleviate storage pressure on the blockchain.Compared to other schemes,BCMS-LIDSASC requires smaller key size and less storage,and has lower computation cost.It contributes to secure and efficient management of medical data and can protect patient privacy and ensure the integrity of electronic healthcare systems.

关键词： Blockchain Identity-based searchable attribute signcryption Distributed storage NTRU lattice

Learning background restoration and local sparse dictionary for infrared small target detection

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Optoelectronics Letters 2024年第7期20卷 437-448页

作者： HE Yue ZHANG Rui XI Chunmei ZHU Hu School of communications and Information engineering Nanjing University of Posts and Telecommunications

This paper proposes a method for learning background restoration for infrared small target detection, employing a local sparse dictionary alongside an equalized structural texture representation. The method is specifically designed for the detection of small infrared targets, accommodating various levels of brightness, spatial size, and intensity. Our proposed model intelligently combines global low-rankness and local sparsity to estimate the rank of the background tensor, leveraging spatial and structural information to overcome the limitations posed by insufficient detailed texture knowledge. Subsequently, a structural texture representation, combining local gradient maps and local intensity maps, is applied to emphasize small objects. By comparing our method with nine advanced and representative approaches and quantifying the comparison using various metrics, the experimental results indicate that our proposed method has achieved favorable outcomes in both quantitative assessments and visual results.

关键词： A

Deep learning for joint channel estimation and feedback in massive MIMO systems

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Digital communications and Networks 2024年第1期10卷 83-93页

作者： Jiajia Guo Tong Chen Shi Jin Geoffrey Ye Li Xin Wang Xiaolin Hou National Mobile communications Research Laboratory Southeast UniversityNanjing210096China Department of Electrical and Electronic engineering Imperial College LondonLondonSW72AZUK DOCOMO Beijing communications Laboratories Co. LtdBeijingChina

The great potentials of massive Multiple-Input Multiple-Output(MIMO)in Frequency Division Duplex(FDD)mode can be fully exploited when the downlink Channel State Information(CSI)is available at base stations.However,the accurate CsI is difficult to obtain due to the large amount of feedback overhead caused by massive antennas.In this paper,we propose a deep learning based joint channel estimation and feedback framework,which comprehensively realizes the estimation,compression,and reconstruction of downlink channels in FDD massive MIMO systems.Two networks are constructed to perform estimation and feedback explicitly and implicitly.The explicit network adopts a multi-Signal-to-Noise-Ratios(SNRs)technique to obtain a single trained channel estimation subnet that works well with different SNRs and employs a deep residual network to reconstruct the channels,while the implicit network directly compresses pilots and sends them back to reduce network parameters.Quantization module is also designed to generate data-bearing bitstreams.Simulation results show that the two proposed networks exhibit excellent performance of reconstruction and are robust to different environments and quantization errors.

关键词： Channel estimation CSI feedback Deep learning Massive MIMO FDD

New Antenna Array Beamforming Techniques Based on Hybrid Convolution/Genetic Algorithm for 5G and Beyond communications

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Computer Modeling in engineering & Sciences 2024年第3期138卷 2749-2767页

作者： Shimaa M.Amer Ashraf A.M.Khalaf Amr H.Hussein Salman A.Alqahtani Mostafa H.Dahshan Hossam M.Kassem Electronics and communications engineering Department Higher Institute of Engineering and TechnologyKafr ElsheikhEgypt Electronics and Electrical communications engineering Department Faculty of EngineeringMinia UniversityMiniaEgypt Electronics and Electrical communications engineering Department Faculty of EngineeringTanta UniversityTantaEgypt Electronics and Electrical communications engineering Department Faculty of EngineeringHorus University EgyptNew DamiettaEgypt Department of Computer engineering College of computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia School of Computing Mathematics and EngineeringCharles Sturt UniversityBathurstNSW2795Australia

Side lobe level reduction(SLL)of antenna arrays significantly enhances the signal-to-interference ratio and improves the quality of service(QOS)in recent and future wireless communication systems starting from 5G up to 7G.Furthermore,it improves the array gain and directivity,increasing the detection range and angular resolution of radar systems.This study proposes two highly efficient SLL reduction techniques.These techniques are based on the hybridization between either the single convolution or the double convolution algorithms and the genetic algorithm(GA)to develop the Conv/GA andDConv/GA,respectively.The convolution process determines the element’s excitations while the GA optimizes the element spacing.For M elements linear antenna array(LAA),the convolution of the excitation coefficients vector by itself provides a new vector of excitations of length N=(2M−1).This new vector is divided into three different sets of excitations including the odd excitations,even excitations,and middle excitations of lengths M,M−1,andM,respectively.When the same element spacing as the original LAA is used,it is noticed that the odd and even excitations provide a much lower SLL than that of the LAA but with amuch wider half-power beamwidth(HPBW).While the middle excitations give the same HPBWas the original LAA with a relatively higher SLL.Tomitigate the increased HPBWof the odd and even excitations,the element spacing is optimized using the GA.Thereby,the synthesized arrays have the same HPBW as the original LAA with a two-fold reduction in the SLL.Furthermore,for extreme SLL reduction,the DConv/GA is introduced.In this technique,the same procedure of the aforementioned Conv/GA technique is performed on the resultant even and odd excitation vectors.It provides a relatively wider HPBWthan the original LAA with about quad-fold reduction in the SLL.

关键词： Array synthesis convolution process genetic algorithm(GA) half power beamwidth(HPBW) linear antenna array(LAA) side lobe level(SLL) quality of service(QOS)

Actor-Critic-Based UAV-Assisted Data Collection in the Wireless Sensor Network

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China communications 2024年第4期21卷 163-177页

作者： Huang Xiaoge Wang Lingzhi He Yong Chen Qianbin School of communications and Information engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China

Wireless Sensor Network(WSN)is widely utilized in large-scale distributed unmanned detection scenarios due to its low cost and flexible installation.However,WSN data collection encounters challenges in scenarios lacking communication infrastructure.Unmanned aerial vehicle(UAV)offers a novel solution for WSN data collection,leveraging their high mobility.In this paper,we present an efficient UAV-assisted data collection algorithm aimed at minimizing the overall power consumption of the WSN.Firstly,a two-layer UAV-assisted data collection model is introduced,including the ground and aerial layers.The ground layer senses the environmental data by the cluster members(CMs),and the CMs transmit the data to the cluster heads(CHs),which forward the collected data to the UAVs.The aerial network layer consists of multiple UAVs that collect,store,and forward data from the CHs to the data center for analysis.Secondly,an improved clustering algorithm based on K-Means++is proposed to optimize the number and locations of CHs.Moreover,an Actor-Critic based algorithm is introduced to optimize the UAV deployment and the association with CHs.Finally,simulation results verify the effectiveness of the proposed algorithms.

关键词： actor critic data collection deep reinforcement learning unmanned aerial vehicle wireless sensor network