At this historic juncture of deepening technological revolution and industrial transformation,China's communication sector stands on the eve of another great leap forward.Reflecting on the development of communica...At this historic juncture of deepening technological revolution and industrial transformation,China's communication sector stands on the eve of another great leap forward.Reflecting on the development of communications over the past two decades,China has forged an innovative path from catching up to keeping pace and then to leading the way.Today,at the new starting point of 6G development and facing the paradigm shift brought about by“AI+communications,”China's scientific research community,with the courage to venture into uncharted territory,is advancing original theories such as the new communication paradigm based on a unified theoretical framework of information theory to the global forefront.展开更多
The modern world remains vulnerable to natural disasters,including floods,earthquakes,wildfires,and others.These events remain unpredictable and inevitable,and recovering quickly and effectively requires significant e...The modern world remains vulnerable to natural disasters,including floods,earthquakes,wildfires,and others.These events remain unpredictable and inevitable,and recovering quickly and effectively requires significant effort and expense.Monitoring is becoming more efficient thanks to technologies such as Unmanned Aerial Vehicles(UAVs),which can access hard-to-reach areas and provide real-time data.However,in disaster-affected areas,these monitoring systems may encounter many obstacles when communicating with servers or transmitting monitored data.This paper proposes an adaptive communication model to overcome the challenges faced in disaster-affected areas.A base station is responsible for collecting data(such as images and videos)captured by UAVs performing surveillance within its communication range.This station is typically a tower providing fixed cellular network service.However,in the absence of such a tower,a selected UAV may serve as the station,depending on the situation.If surveillance needs to be performed outside the coverage area,it can continue to communicate via nearby UAVs through cooperative communication.UAVs with internet support,known as the Internet of Flying Things(IoFT),will also be utilized to enhance communication capacity and efficiency.The proposed communication model is validated through experiments,showing superior data transmission performance and higher throughput.Analysis indicates it outperforms traditional systems,even in rural areas,with or without internet access.展开更多
Text semantic extraction has been envisioned as a promising solution to improve the data transmission efficiency with the limited radio resources for the autonomous interactions among machines and things in the future...Text semantic extraction has been envisioned as a promising solution to improve the data transmission efficiency with the limited radio resources for the autonomous interactions among machines and things in the future sixth-generation(6G)wireless networks.In this paper,we propose a Chinese text semantic extraction model,namely T-Pointer,to improve the quality of semantic extraction by integrating the Transformer with the pointer-generator network.The proposed T-Pointer model consists of a semantic encoder and a semantic decoder.In the encoding stage,we use the multi-head attention mechanism of the Transformer to extract semantic features from the input Chinese text.In the decoding stage,we first use the Transformer to extract multi-level global text features.Then,we introduce the pointer-generator network model to directly copy the keyword information from the source text.The simulation results demonstrate that the T-Pointer model can improve the bilingual evaluation understudy(BLEU)and recalloriented understudy for gisting evaluation(ROUGE)by 14.69%and 14.87%on average in comparison with the state-of-the-art models,respectively.Also,we implement the T-Pointer model on a semantic communication system based on the universal software radio peripheral(USRP)platform.The result shows that the packet delay of semantic transmission can be reduced by 52.05%on average,compared to traditional information transmission.展开更多
The smart meter communication system has substantial application value for the construction and upgrading of the entire power system.The deployment of the transmitter(Tx)of the smart meter system in the residential sc...The smart meter communication system has substantial application value for the construction and upgrading of the entire power system.The deployment of the transmitter(Tx)of the smart meter system in the residential scenarios is vexed by the need for more theoretical support.This paper mainly studies the communication channel between the Tx at semibasement and receiver(Rx)at outdoor.The design of an effective communication system relies on an accurate understanding of channel characteristics.Channel measurements and ray-tracing channel modeling are conducted to obtain channel data.The influence of different positions at same semi-basement is studied.Typical channel characteristics are analyzed,such as power delay profile(PDP),power angular profile(PAP),root-mean-square(RMS)delay spread(DS),channel capacity,received power,and path loss.The influence of different semi-basement placements and different floor heights is also compared.Besides,the channel measurements and simulation data fit well,which can illustrate the validity and reliability of the acquired channel data.This paper can provide theoretical support for the design and optimization of smart meter communication systems in semi-basement scenarios.展开更多
This study investigates how to pedagogically integrate ideological education with competency development in the Intercultural Communication course,a challenge arising from China’s dual reform contexts of the New Libe...This study investigates how to pedagogically integrate ideological education with competency development in the Intercultural Communication course,a challenge arising from China’s dual reform contexts of the New Liberal Arts initiative and the national curriculum ideology policy.As global interactions intensify,cultivating foreign language professionals who possess both firm cultural confidence and sophisticated intercultural competence have become a critical educational imperative.This exploratory study investigates how a three-dimensional“Value-Knowledge-Competency”framework can guide the redesign of course content,task design,and assessment to achieve organic fusion.Drawing on qualitative data from a case study,it analyzes specific implementation pathways,synthesizes teacher and student feedback,and discusses the resultant challenges and broader implications for foreign language curriculum reform.The findings suggest that such an integrated approach can effectively synergize value guidance with skill cultivation,though its success hinges on overcoming issues related to pedagogical naturalness,resource allocation,and standardized evaluation.展开更多
Accurate prediction of environmental temperature is pivotal for promoting sustainable crop growth.At present,the most effective temperature sensing and prediction system is the Agricultural Internet of Things(AIoT),wh...Accurate prediction of environmental temperature is pivotal for promoting sustainable crop growth.At present,the most effective temperature sensing and prediction system is the Agricultural Internet of Things(AIoT),which deploys a large number of sensors to collect meteorological data and transmits them to the cloud server for prediction.However,this procedure is computationally and communicationally expensive for resourceconstrained AIoT.Recently,Semantic Communication(SC)has shown potential in efficient data transmission,but existing methods overlook the repetitive semantic information whilst sensing data,bringing additional overheads.With the resource-constraint nature of AIoT in mind,we propose the Semantic Communication-enabled Cognitive Agriculture Framework(SC-CAF)for delivering accurate temperature predictions.The proposed SC-CAF incorporates an intelligent analysis layer that performs the temperature prediction and model training and distribution,while a semantic layer transmitting the semantic information extracted from raw data based on the download model,ultimately to reduce communication overheads in AIoT.Furthermore,we propose a novel model called the Light Temperature Semantic Communication(LTSC)by adopting skip-attention and semantic compressor to avoid unnecessary computation and repetitive information,thereby addressing the semantic redundancy issues in sensing data.We also develop a Semantic-based Model Compression(SCMC)algorithm to alleviate the computation and bandwidth burden,enabling AIoT to explore the extensive usage of SC.Experimental results demonstrate that the proposed SC-CAF achieves the lowest prediction error while reducing Floating Point Operations(FLOPs)by 95.88%,memory requirements by 78.30%,Graphics Processing Unit(GPU)power by 50.77%,and time latency by 84.44%,outperforming notable state-of-the-art methods.展开更多
This paper divides the centuries-long communication of traditional Chinese medicine(TCM)in France into three progressive stages:the first stage(17th to 19th centuries),characterized by academic recognition and knowled...This paper divides the centuries-long communication of traditional Chinese medicine(TCM)in France into three progressive stages:the first stage(17th to 19th centuries),characterized by academic recognition and knowledge transmission;the second stage(mid-19th century to late 20th century),focusing on clinical verification and school-based innovation;and the third stage(late 20th century to the present),marked by cultural integration and pluralistic coexistence within systems.The introduction of TCM in France is a process of cross-cultural adaptation and coexistence driven by specific health needs in French society,such as chronic disease management and complementary therapies.The French medical community and sociocultural context have not only verified and interpreted TCM through an empirical scientific perspective,but also realized creative localization by developing indigenous schools such as electroacupuncture and auricular acupuncture.Eventually,through institutional measures including national certification,terminology standardization,and networked healthcare services,TCM has been deeply integrated into France’s medical system and social context,forming a stable ecosystem of cross-cultural adaptation and pluralistic coexistence.The French experience,which takes aligning with local health needs as the starting point,stimulating localized cultural innovation as the core,and promoting systematic integration into local systems as the support,presents a picture of traditional medicine serving modern society,the improvement of global health,as well as mutual learning and symbiosis among different civilizations.展开更多
Dear Editor,This letter studies the motion planning issue for an autonomous underwater vehicle(AUV)in obstacle environment.We propose a novel integrated detection-communication waveform that enables simultaneous obsta...Dear Editor,This letter studies the motion planning issue for an autonomous underwater vehicle(AUV)in obstacle environment.We propose a novel integrated detection-communication waveform that enables simultaneous obstacle detection and self-localization.展开更多
Ningxia is an ethnic gathering area boasting abundant tourism and cultural resources.Developing the cause of tourism and culture is an important way to encourage all ethnic groups to respect differences,embrace divers...Ningxia is an ethnic gathering area boasting abundant tourism and cultural resources.Developing the cause of tourism and culture is an important way to encourage all ethnic groups to respect differences,embrace diversity,and demonstrate their interactions,exchanges,and integration in tourism activities.As an important preserve of the distinctive cultures of the Chinese nation and a prominent world tourist destination,Ningxia should strive to foster and consolidate the sense of a community with a shared future for the Chinese nation in developing its tourism and culture under the new historical conditions.It is imperative to advance the prosperity and development of tourism and culture in boosting ethnic interactions,exchanges,and integration through the formulation of tourism and cultural policies and plans,as well as the development and design of tourism and cultural projects.展开更多
This article studies the problem of image segmentation-based semantic communication in autonomous driving.In real traffic scenes,the detecting of objects(e.g.,vehicles and pedestrians)is more important to guarantee dr...This article studies the problem of image segmentation-based semantic communication in autonomous driving.In real traffic scenes,the detecting of objects(e.g.,vehicles and pedestrians)is more important to guarantee driving safety,which is always ignored in existing works.Therefore,we propose a vehicular image segmentation-oriented semantic communication system,termed VIS-SemCom,focusing on transmitting and recovering image semantic features of high-important objects to reduce transmission redundancy.First,we develop a semantic codec based on Swin Transformer architecture,which expands the perceptual field thus improving the segmentation accuracy.To highlight the important objects'accuracy,we propose a multi-scale semantic extraction method by assigning the number of Swin Transformer blocks for diverse resolution semantic features.Also,an importance-aware loss incorporating important levels is devised,and an online hard example mining(OHEM)strategy is proposed to handle small sample issues in the dataset.Finally,experimental results demonstrate that the proposed VIS-SemCom can achieve a significant mean intersection over union(mIoU)performance in the SNR regions,a reduction of transmitted data volume by about 60%at 60%mIoU,and improve the segmentation accuracy of important objects,compared to baseline image communication.展开更多
In data communication,limited communication resources often lead to measurement bias,which adversely affects subsequent system estimation if not effectively handled.This paper proposes a novel bias calibration algorit...In data communication,limited communication resources often lead to measurement bias,which adversely affects subsequent system estimation if not effectively handled.This paper proposes a novel bias calibration algorithm under communication constraints to achieve accurate system states of the interested system.An output-based event-triggered scheme is first employed to alleviate transmission burden.Accounting for the limited-communication-induced measurement bias,a novel bias calibration algorithm following the Kalman filtering line is developed to restrain the effect of the measurement bias on system estimation,thereby achieving accurate system state estimates.Subsequently,the Field Programmable Gate Array(FPGA)implementation of the proposed algorithm is also realized with the hope of providing fast bias calibration in practical scenarios.A simulation about a numerical example and a practical example(for gyroscope’s angular velocity bias calibration)on MATLAB is provided to demonstrate the feasibility and effectiveness of the proposed algorithm.展开更多
Integrated sensing and communication(ISAC)is an appealing approach to address spectrum congestion and beamforming is an effective method to realize ISAC.In this paper,we investigate the beamforming design problem for ...Integrated sensing and communication(ISAC)is an appealing approach to address spectrum congestion and beamforming is an effective method to realize ISAC.In this paper,we investigate the beamforming design problem for multiple-input multipleoutput(MIMO)ISAC systems and propose to maximize the radar beampattern gain of the target direction while ensuring the signal-to-interference-plus-noise ratio(SINR)constraints of communication users.Particularly,we discuss two cases of ISAC transmit beamforming,i.e.,Case-Ⅰand Case-Ⅱ,which do not have and do have the dedicated probing signal,respectively.For these two cases of transmit beamforming design problems,we start from the single-user scenario and provide the closed-form solutions for MIMO ISAC beamforming vectors.Then,we consider the multiuser scenario and utilize the semidefinite relaxation technique to convert the beamforming design problems into convex semidefinite programming problems.Furthermore,we investigate the impact of the channel correlation between radar and communication on the performance gain of MIMO ISAC systems and characterize the performance tradeoff.Numerical results validate that the dedicated probing signal is unnecessary in the single-user scenario,whereas it has a slight improvement in target detection performance at low SINR thresholds in the multi-user scenario.It is also shown that the stronger the correlation between radar and communication channels,the greater the performance gain of the system.展开更多
Federated learning often experiences slow and unstable convergence due to edge-side data heterogeneity.This problem becomes more severe when edge participation rate is low,as the information collected from different e...Federated learning often experiences slow and unstable convergence due to edge-side data heterogeneity.This problem becomes more severe when edge participation rate is low,as the information collected from different edge devices varies significantly.As a result,communication overhead increases,which further slows down the convergence process.To address this challenge,we propose a simple yet effective federated learning framework that improves consistency among edge devices.The core idea is clusters the lookahead gradients collected from edge devices on the cloud server to obtain personalized momentum for steering local updates.In parallel,a global momentum is applied during model aggregation,enabling faster convergence while preserving personalization.This strategy enables efficient propagation of the estimated global update direction to all participating edge devices and maintains alignment in local training,without introducing extra memory or communication overhead.We conduct extensive experiments on benchmark datasets such as Cifar100 and Tiny-ImageNet.The results confirm the effectiveness of our framework.On CIFAR-100,our method reaches 55%accuracy with 37 fewer rounds and achieves a competitive final accuracy of 65.46%.Even under extreme non-IID scenarios,it delivers significant improvements in both accuracy and communication efficiency.The implementation is publicly available at https://github.com/sjmp525/CollaborativeComputing/tree/FedCCM(accessed on 20 October 2025).展开更多
Cascading failures pose a serious threat to the survivability of underwater unmanned swarm networks(UUSNs),significantly limiting their service ability in collaborative missions such as military reconnaissance and env...Cascading failures pose a serious threat to the survivability of underwater unmanned swarm networks(UUSNs),significantly limiting their service ability in collaborative missions such as military reconnaissance and environmental monitoring.Existing failure models primarily focus on power grids and traffic systems,and don't address the unique challenges of weak-communication UUSNs.In UUSNs,cascading failure present a complex and dynamic process driven by the coupling of unstable acoustic channels,passive node drift,adversarial attacks,and network heterogeneity.To address these challenges,a directed weighted graph model of UUSNs is first developed,in which node positions are updated according to ocean-current-driven drift and link weights reflect the probability of successful acoustic transmission.Building on this UUSNs graph model,a cascading failure model is proposed that integrates a normal-failure-recovery state-cycle mechanism,multiple attack strategies,and routingbased load redistribution.Finally,under a five-level connectivity UUSNs scheme,simulations are conducted to analyze how dynamic topology,network load,node recovery delay,and attack modes jointly affect network survivability.The main findings are:(1)moderate node drift can improve survivability by activating weak links;(2)based-energy routing(BER)outperform based-depth routing(BDR)in harsh conditions;(3)node self-recovery time is critical to network survivability;(4)traditional degree-based critical node metrics are inadequate for weak-communication UUSNs.These results provide a theoretical foundation for designing robust survivability mechanisms in weak-communication UUSNs.展开更多
This paper presents an image encryption scheme for underwater optical wireless communication(UOWC)systems based on dynamically generated hyperchaotic S-boxes,aiming to enhance both data security and transmission perfo...This paper presents an image encryption scheme for underwater optical wireless communication(UOWC)systems based on dynamically generated hyperchaotic S-boxes,aiming to enhance both data security and transmission performance in underwater environments.The proposed encryption approach provides strong confusion and diffusion properties and is evaluated over five Jerlov water types with different optical attenuation characteristics.Security analysis demonstrates that the encrypted images achieve information entropy values close to the ideal value of 8(7.9925–7.9993),with very low correlation coefficients in horizontal,vertical,and diagonal directions,as well as the system achieves high values in key metrics such as the Unified Average Changing Intensity(UACI)and Number of Pixel Change Rate(NPCR),ranging from 33.42 to 33.47 and from 99.58%to 99.62%,respectively,both near their theoretical optima.In addition to improving confidentiality,the hyperchaotic encryption process decorrelates pixel intensities and redistributes image spectral content,which enhances robustness against underwater absorption and scattering effects.As a result,improved transmission performance is observed;for example,in Jerlov type I(JI)water,the effective transmission distance is extended from16mfor plain images to 24mfor encrypted images,while the Peak Signal to Noise Ratio(PSNR)at 24 m increases from 9.25 to 20.13 dB after decryption and enhancement.These results confirmthat the proposed scheme provides a dual benefit of secure and reliable image transmission in UOWC systems.展开更多
To tackle the physical layer security challenges in wireless communication,this paper introduces a multiuser architecture that leverages single-channel blind source separation,centered around a Multi-source Signal Mix...To tackle the physical layer security challenges in wireless communication,this paper introduces a multiuser architecture that leverages single-channel blind source separation,centered around a Multi-source Signal Mixture Separator(MSMS).This architecture consists of a multi-user encoder,a channel layer,and a separation decoder,allowing it to handle multiple functions simultaneously,including encoding,modulation,signal separation,demodulation,and decoding.The MSMS receiver effectively enables the separation of numerous user signals,making it exceedingly difficult for unauthorized eavesdroppers to extract valuable information from the mixed signals,thus significantly enhancing communication security.The MSMS can address the challenges of few-shot sample training and achieve joint optimization during transmission by employing a deep learning-based network design.The design of a single receiver reduces system costs and improves spectrum efficiency.The MSMS outperforms traditional Space-time Block Coding(STBC)strategies regarding separation performance,particularly in Block Error Rate(BLER)metrics.Modulation constellation diagrams further analyze the effectiveness of multi-source signal mixture separation.Moreover,this study extends the MSMS framework from a two-user scenario to a three-user scenario,further demonstrating the flexibility and scalability of the proposed architecture.展开更多
This paper studies wireless vehicular communication(VehCom)in intelligent transportation systems using an orthogonal frequency division multiplexing with index modulation(OFDM-IM).In the concept of IM,data is transmit...This paper studies wireless vehicular communication(VehCom)in intelligent transportation systems using an orthogonal frequency division multiplexing with index modulation(OFDM-IM).In the concept of IM,data is transmitted not only through the modulated symbols but also via the indices of the active subcarriers.In contrast to the original OFDM,OFDM-IM activates only non-zero subcarriers,increasing energy efficiency.However,the pilotassisted channel estimation(CE)method is a significant challenge in OFDM-IM,where the desired pilot subcarrier interval is related to the OFDM-IM subblock length.This paper proposes a walsh-scattered pilot-assisted CE for OFDM-IM VehCom.The optimum walsh-scattered pilot assignment is proposed to improve the transmission efficiency.Furthermore,a space-time block code with a high transmit diversity gain is employed for OFDM-IM VehCom to enhance VehCom's signal quality.The results show that the proposed method performs higher CE accuracy and better bit-error rate with significant spectral and energy efficiencies than conventional methods.展开更多
Efficient energy utilization in covert communication sustains covertness while assuring communication quality and efficiency.This paper investigates covert communication energy efficiency(EE)in direct uplink satellite...Efficient energy utilization in covert communication sustains covertness while assuring communication quality and efficiency.This paper investigates covert communication energy efficiency(EE)in direct uplink satellite-ground communications,focusing on enhancing system EE via optimized transmit beamforming and satellite orbit altitude selection.This paper first establishes an optimization problem to maximize system EE in a direct uplink satelliteground covert communication scenario.To solve this non-convex optimization problem,it is decomposed into two subproblems and solved using the successive convex approximation(SCA)method.Based on the above methods,this paper proposes an overall iterative optimization algorithm.Simulation results demonstrate that the proposed algorithm surpasses the conventional baseline algorithms in terms of system EE.Furthermore,they elucidate the correlation between the amount of information received by the receiver and the variations in the satellite’s orbital altitude.展开更多
Long-term exposure to ambient fine particulate matter(PM2.5)may increase the risk of neurotoxicity in human populations.However,research studies on the underlying mechanisms of chronic PM2.5-induced depression-like be...Long-term exposure to ambient fine particulate matter(PM2.5)may increase the risk of neurotoxicity in human populations.However,research studies on the underlying mechanisms of chronic PM2.5-induced depression-like behaviors,and potential therapeutical strategies,remain scarce.In the present study,after long-term exposure to real-world PM2.5 for 15 weeks,male mice displayed depression-like behaviors,which were revealed using the open field and sucrose preference tests.Mechanistically,chronic PM2.5 exposure promoted astrocytic A1 polarization and disrupted reduction-oxidation balance in the mouse hippocampus.Furthermore,PM2.5-exposed mice displayed pathological damage to hippocampal neurons as well as the inhibition of nuclear factor erythroid 2-related factor 2 signaling.Astrocytic ablation of nuclear factor erythroid 2-related factor 2 exacerbated PM2.5-induced hippocampal neuronal injury in mice via the disruption of astrocyte-to-microglia communication;this finding was confirmed in mice with bilateral and unilateral hippocampal astrocytic Nfe2l2 knockdown.Importantly,the upregulation of nuclear factor erythroid 2-related factor 2 activation by procyanidin significantly ameliorated PM2.5-induced depression-like behaviors through the remodeling of astrocyte-to-microglia communication.Together,our findings shed light on the important role of hippocampal astrocytic nuclear factor erythroid 2-related factor 2 activation for maintaining astrocyte-to-microglia communication,and indicate potential research avenues for therapeutic strategies against PM2.5-induced depresson-like behaviors.展开更多
文摘At this historic juncture of deepening technological revolution and industrial transformation,China's communication sector stands on the eve of another great leap forward.Reflecting on the development of communications over the past two decades,China has forged an innovative path from catching up to keeping pace and then to leading the way.Today,at the new starting point of 6G development and facing the paradigm shift brought about by“AI+communications,”China's scientific research community,with the courage to venture into uncharted territory,is advancing original theories such as the new communication paradigm based on a unified theoretical framework of information theory to the global forefront.
文摘The modern world remains vulnerable to natural disasters,including floods,earthquakes,wildfires,and others.These events remain unpredictable and inevitable,and recovering quickly and effectively requires significant effort and expense.Monitoring is becoming more efficient thanks to technologies such as Unmanned Aerial Vehicles(UAVs),which can access hard-to-reach areas and provide real-time data.However,in disaster-affected areas,these monitoring systems may encounter many obstacles when communicating with servers or transmitting monitored data.This paper proposes an adaptive communication model to overcome the challenges faced in disaster-affected areas.A base station is responsible for collecting data(such as images and videos)captured by UAVs performing surveillance within its communication range.This station is typically a tower providing fixed cellular network service.However,in the absence of such a tower,a selected UAV may serve as the station,depending on the situation.If surveillance needs to be performed outside the coverage area,it can continue to communicate via nearby UAVs through cooperative communication.UAVs with internet support,known as the Internet of Flying Things(IoFT),will also be utilized to enhance communication capacity and efficiency.The proposed communication model is validated through experiments,showing superior data transmission performance and higher throughput.Analysis indicates it outperforms traditional systems,even in rural areas,with or without internet access.
基金National Natural Science Foundation of China under Grants 62122069,62071431,62072490,62301490Science and Technology Development Fund of Macao,Macao,China under Grant 0158/2022/A+2 种基金Guangdong Basic and Applied Basic Research Foundation(2022A1515011287)MYRG2020-00107-IOTSCFDCT SKL-IOTSC(UM)-2021-2023。
文摘Text semantic extraction has been envisioned as a promising solution to improve the data transmission efficiency with the limited radio resources for the autonomous interactions among machines and things in the future sixth-generation(6G)wireless networks.In this paper,we propose a Chinese text semantic extraction model,namely T-Pointer,to improve the quality of semantic extraction by integrating the Transformer with the pointer-generator network.The proposed T-Pointer model consists of a semantic encoder and a semantic decoder.In the encoding stage,we use the multi-head attention mechanism of the Transformer to extract semantic features from the input Chinese text.In the decoding stage,we first use the Transformer to extract multi-level global text features.Then,we introduce the pointer-generator network model to directly copy the keyword information from the source text.The simulation results demonstrate that the T-Pointer model can improve the bilingual evaluation understudy(BLEU)and recalloriented understudy for gisting evaluation(ROUGE)by 14.69%and 14.87%on average in comparison with the state-of-the-art models,respectively.Also,we implement the T-Pointer model on a semantic communication system based on the universal software radio peripheral(USRP)platform.The result shows that the packet delay of semantic transmission can be reduced by 52.05%on average,compared to traditional information transmission.
基金supported by the Natural Science Foundation of Shandong Province under Grant ZR2024MF062the open research fund of National Mobile Communications Research Laboratory,Southeast University under Grants 2025D03+1 种基金the Future Plan Program for Young Scholars of Shandong University,and the Innovation and Technology Support Program for Young Scholars of Colleges and Universities in Shandong Province under Grant 2022KJ009The B6G R&D Group in Shandong University is greatly thanked for channel measurements.
文摘The smart meter communication system has substantial application value for the construction and upgrading of the entire power system.The deployment of the transmitter(Tx)of the smart meter system in the residential scenarios is vexed by the need for more theoretical support.This paper mainly studies the communication channel between the Tx at semibasement and receiver(Rx)at outdoor.The design of an effective communication system relies on an accurate understanding of channel characteristics.Channel measurements and ray-tracing channel modeling are conducted to obtain channel data.The influence of different positions at same semi-basement is studied.Typical channel characteristics are analyzed,such as power delay profile(PDP),power angular profile(PAP),root-mean-square(RMS)delay spread(DS),channel capacity,received power,and path loss.The influence of different semi-basement placements and different floor heights is also compared.Besides,the channel measurements and simulation data fit well,which can illustrate the validity and reliability of the acquired channel data.This paper can provide theoretical support for the design and optimization of smart meter communication systems in semi-basement scenarios.
基金Funding Source:2024 Heilongjiang Province Higher Education Teaching Reform Key Research Project.Project Name:Practice and Exploration of Curriculum-Based Political Education in the Intercultural Communication Course Under the New Liberal Arts Framework(Grant No.SJGZB2024063).
文摘This study investigates how to pedagogically integrate ideological education with competency development in the Intercultural Communication course,a challenge arising from China’s dual reform contexts of the New Liberal Arts initiative and the national curriculum ideology policy.As global interactions intensify,cultivating foreign language professionals who possess both firm cultural confidence and sophisticated intercultural competence have become a critical educational imperative.This exploratory study investigates how a three-dimensional“Value-Knowledge-Competency”framework can guide the redesign of course content,task design,and assessment to achieve organic fusion.Drawing on qualitative data from a case study,it analyzes specific implementation pathways,synthesizes teacher and student feedback,and discusses the resultant challenges and broader implications for foreign language curriculum reform.The findings suggest that such an integrated approach can effectively synergize value guidance with skill cultivation,though its success hinges on overcoming issues related to pedagogical naturalness,resource allocation,and standardized evaluation.
基金supported by the Key Research and Development Project of Hubei Province(No.2024BAB070),China。
文摘Accurate prediction of environmental temperature is pivotal for promoting sustainable crop growth.At present,the most effective temperature sensing and prediction system is the Agricultural Internet of Things(AIoT),which deploys a large number of sensors to collect meteorological data and transmits them to the cloud server for prediction.However,this procedure is computationally and communicationally expensive for resourceconstrained AIoT.Recently,Semantic Communication(SC)has shown potential in efficient data transmission,but existing methods overlook the repetitive semantic information whilst sensing data,bringing additional overheads.With the resource-constraint nature of AIoT in mind,we propose the Semantic Communication-enabled Cognitive Agriculture Framework(SC-CAF)for delivering accurate temperature predictions.The proposed SC-CAF incorporates an intelligent analysis layer that performs the temperature prediction and model training and distribution,while a semantic layer transmitting the semantic information extracted from raw data based on the download model,ultimately to reduce communication overheads in AIoT.Furthermore,we propose a novel model called the Light Temperature Semantic Communication(LTSC)by adopting skip-attention and semantic compressor to avoid unnecessary computation and repetitive information,thereby addressing the semantic redundancy issues in sensing data.We also develop a Semantic-based Model Compression(SCMC)algorithm to alleviate the computation and bandwidth burden,enabling AIoT to explore the extensive usage of SC.Experimental results demonstrate that the proposed SC-CAF achieves the lowest prediction error while reducing Floating Point Operations(FLOPs)by 95.88%,memory requirements by 78.30%,Graphics Processing Unit(GPU)power by 50.77%,and time latency by 84.44%,outperforming notable state-of-the-art methods.
文摘This paper divides the centuries-long communication of traditional Chinese medicine(TCM)in France into three progressive stages:the first stage(17th to 19th centuries),characterized by academic recognition and knowledge transmission;the second stage(mid-19th century to late 20th century),focusing on clinical verification and school-based innovation;and the third stage(late 20th century to the present),marked by cultural integration and pluralistic coexistence within systems.The introduction of TCM in France is a process of cross-cultural adaptation and coexistence driven by specific health needs in French society,such as chronic disease management and complementary therapies.The French medical community and sociocultural context have not only verified and interpreted TCM through an empirical scientific perspective,but also realized creative localization by developing indigenous schools such as electroacupuncture and auricular acupuncture.Eventually,through institutional measures including national certification,terminology standardization,and networked healthcare services,TCM has been deeply integrated into France’s medical system and social context,forming a stable ecosystem of cross-cultural adaptation and pluralistic coexistence.The French experience,which takes aligning with local health needs as the starting point,stimulating localized cultural innovation as the core,and promoting systematic integration into local systems as the support,presents a picture of traditional medicine serving modern society,the improvement of global health,as well as mutual learning and symbiosis among different civilizations.
基金supported in part by the National Natural Science Foundation of China(U25A20473,62222314)the YanZhao Young Scientist Project of Hebei Province(F2024203047)+2 种基金the Natural Science Foundation of Hebei Province(F2022203001,F2024203072)the State Key Laboratory of Submarine Geoscience(sglkt2025-7)the Education Department Foundation of Hebei Province(JCZX2025027)。
文摘Dear Editor,This letter studies the motion planning issue for an autonomous underwater vehicle(AUV)in obstacle environment.We propose a novel integrated detection-communication waveform that enables simultaneous obstacle detection and self-localization.
文摘Ningxia is an ethnic gathering area boasting abundant tourism and cultural resources.Developing the cause of tourism and culture is an important way to encourage all ethnic groups to respect differences,embrace diversity,and demonstrate their interactions,exchanges,and integration in tourism activities.As an important preserve of the distinctive cultures of the Chinese nation and a prominent world tourist destination,Ningxia should strive to foster and consolidate the sense of a community with a shared future for the Chinese nation in developing its tourism and culture under the new historical conditions.It is imperative to advance the prosperity and development of tourism and culture in boosting ethnic interactions,exchanges,and integration through the formulation of tourism and cultural policies and plans,as well as the development and design of tourism and cultural projects.
基金National Natural Science Foundation of China under Grants No.62171047,U22B2001,62271065,62001051Beijing Natural Science Foundation under Grant L223027BUPT Excellent Ph.D Students Foundation under Grants CX2021114。
文摘This article studies the problem of image segmentation-based semantic communication in autonomous driving.In real traffic scenes,the detecting of objects(e.g.,vehicles and pedestrians)is more important to guarantee driving safety,which is always ignored in existing works.Therefore,we propose a vehicular image segmentation-oriented semantic communication system,termed VIS-SemCom,focusing on transmitting and recovering image semantic features of high-important objects to reduce transmission redundancy.First,we develop a semantic codec based on Swin Transformer architecture,which expands the perceptual field thus improving the segmentation accuracy.To highlight the important objects'accuracy,we propose a multi-scale semantic extraction method by assigning the number of Swin Transformer blocks for diverse resolution semantic features.Also,an importance-aware loss incorporating important levels is devised,and an online hard example mining(OHEM)strategy is proposed to handle small sample issues in the dataset.Finally,experimental results demonstrate that the proposed VIS-SemCom can achieve a significant mean intersection over union(mIoU)performance in the SNR regions,a reduction of transmitted data volume by about 60%at 60%mIoU,and improve the segmentation accuracy of important objects,compared to baseline image communication.
基金support from the National Natural Science Foundation of China(Grant Nos.U2330206,U2230206,62173068)Sichuan Science and Technology Program(Grants Nos.2024NSFSC1483,2024ZYD0156,2023NSFC1962,DQ202412).
文摘In data communication,limited communication resources often lead to measurement bias,which adversely affects subsequent system estimation if not effectively handled.This paper proposes a novel bias calibration algorithm under communication constraints to achieve accurate system states of the interested system.An output-based event-triggered scheme is first employed to alleviate transmission burden.Accounting for the limited-communication-induced measurement bias,a novel bias calibration algorithm following the Kalman filtering line is developed to restrain the effect of the measurement bias on system estimation,thereby achieving accurate system state estimates.Subsequently,the Field Programmable Gate Array(FPGA)implementation of the proposed algorithm is also realized with the hope of providing fast bias calibration in practical scenarios.A simulation about a numerical example and a practical example(for gyroscope’s angular velocity bias calibration)on MATLAB is provided to demonstrate the feasibility and effectiveness of the proposed algorithm.
基金National Natural Science Foundation of China under Grant 62571248 and Grant 62201266Key Laboratory of Intelligent Space TTC&O(Space Engineering University),Ministry of Education under Grant CYK2025-01-12。
文摘Integrated sensing and communication(ISAC)is an appealing approach to address spectrum congestion and beamforming is an effective method to realize ISAC.In this paper,we investigate the beamforming design problem for multiple-input multipleoutput(MIMO)ISAC systems and propose to maximize the radar beampattern gain of the target direction while ensuring the signal-to-interference-plus-noise ratio(SINR)constraints of communication users.Particularly,we discuss two cases of ISAC transmit beamforming,i.e.,Case-Ⅰand Case-Ⅱ,which do not have and do have the dedicated probing signal,respectively.For these two cases of transmit beamforming design problems,we start from the single-user scenario and provide the closed-form solutions for MIMO ISAC beamforming vectors.Then,we consider the multiuser scenario and utilize the semidefinite relaxation technique to convert the beamforming design problems into convex semidefinite programming problems.Furthermore,we investigate the impact of the channel correlation between radar and communication on the performance gain of MIMO ISAC systems and characterize the performance tradeoff.Numerical results validate that the dedicated probing signal is unnecessary in the single-user scenario,whereas it has a slight improvement in target detection performance at low SINR thresholds in the multi-user scenario.It is also shown that the stronger the correlation between radar and communication channels,the greater the performance gain of the system.
基金supported by the National Natural Science Foundation of China(62462040)the Yunnan Fundamental Research Projects(202501AT070345)the Major Science and Technology Projects in Yunnan Province(202202AD080013).
文摘Federated learning often experiences slow and unstable convergence due to edge-side data heterogeneity.This problem becomes more severe when edge participation rate is low,as the information collected from different edge devices varies significantly.As a result,communication overhead increases,which further slows down the convergence process.To address this challenge,we propose a simple yet effective federated learning framework that improves consistency among edge devices.The core idea is clusters the lookahead gradients collected from edge devices on the cloud server to obtain personalized momentum for steering local updates.In parallel,a global momentum is applied during model aggregation,enabling faster convergence while preserving personalization.This strategy enables efficient propagation of the estimated global update direction to all participating edge devices and maintains alignment in local training,without introducing extra memory or communication overhead.We conduct extensive experiments on benchmark datasets such as Cifar100 and Tiny-ImageNet.The results confirm the effectiveness of our framework.On CIFAR-100,our method reaches 55%accuracy with 37 fewer rounds and achieves a competitive final accuracy of 65.46%.Even under extreme non-IID scenarios,it delivers significant improvements in both accuracy and communication efficiency.The implementation is publicly available at https://github.com/sjmp525/CollaborativeComputing/tree/FedCCM(accessed on 20 October 2025).
基金supported in part by the National Natural Science Foundation of China(Key Program)under Grant No.62031021。
文摘Cascading failures pose a serious threat to the survivability of underwater unmanned swarm networks(UUSNs),significantly limiting their service ability in collaborative missions such as military reconnaissance and environmental monitoring.Existing failure models primarily focus on power grids and traffic systems,and don't address the unique challenges of weak-communication UUSNs.In UUSNs,cascading failure present a complex and dynamic process driven by the coupling of unstable acoustic channels,passive node drift,adversarial attacks,and network heterogeneity.To address these challenges,a directed weighted graph model of UUSNs is first developed,in which node positions are updated according to ocean-current-driven drift and link weights reflect the probability of successful acoustic transmission.Building on this UUSNs graph model,a cascading failure model is proposed that integrates a normal-failure-recovery state-cycle mechanism,multiple attack strategies,and routingbased load redistribution.Finally,under a five-level connectivity UUSNs scheme,simulations are conducted to analyze how dynamic topology,network load,node recovery delay,and attack modes jointly affect network survivability.The main findings are:(1)moderate node drift can improve survivability by activating weak links;(2)based-energy routing(BER)outperform based-depth routing(BDR)in harsh conditions;(3)node self-recovery time is critical to network survivability;(4)traditional degree-based critical node metrics are inadequate for weak-communication UUSNs.These results provide a theoretical foundation for designing robust survivability mechanisms in weak-communication UUSNs.
基金funded by Prince Sattam bin Abdulaziz University,grant number PSAU/2025/01/34620.
文摘This paper presents an image encryption scheme for underwater optical wireless communication(UOWC)systems based on dynamically generated hyperchaotic S-boxes,aiming to enhance both data security and transmission performance in underwater environments.The proposed encryption approach provides strong confusion and diffusion properties and is evaluated over five Jerlov water types with different optical attenuation characteristics.Security analysis demonstrates that the encrypted images achieve information entropy values close to the ideal value of 8(7.9925–7.9993),with very low correlation coefficients in horizontal,vertical,and diagonal directions,as well as the system achieves high values in key metrics such as the Unified Average Changing Intensity(UACI)and Number of Pixel Change Rate(NPCR),ranging from 33.42 to 33.47 and from 99.58%to 99.62%,respectively,both near their theoretical optima.In addition to improving confidentiality,the hyperchaotic encryption process decorrelates pixel intensities and redistributes image spectral content,which enhances robustness against underwater absorption and scattering effects.As a result,improved transmission performance is observed;for example,in Jerlov type I(JI)water,the effective transmission distance is extended from16mfor plain images to 24mfor encrypted images,while the Peak Signal to Noise Ratio(PSNR)at 24 m increases from 9.25 to 20.13 dB after decryption and enhancement.These results confirmthat the proposed scheme provides a dual benefit of secure and reliable image transmission in UOWC systems.
基金supported by the National Social Science Foundation of China under Grant 2022-SKJJ-B-112。
文摘To tackle the physical layer security challenges in wireless communication,this paper introduces a multiuser architecture that leverages single-channel blind source separation,centered around a Multi-source Signal Mixture Separator(MSMS).This architecture consists of a multi-user encoder,a channel layer,and a separation decoder,allowing it to handle multiple functions simultaneously,including encoding,modulation,signal separation,demodulation,and decoding.The MSMS receiver effectively enables the separation of numerous user signals,making it exceedingly difficult for unauthorized eavesdroppers to extract valuable information from the mixed signals,thus significantly enhancing communication security.The MSMS can address the challenges of few-shot sample training and achieve joint optimization during transmission by employing a deep learning-based network design.The design of a single receiver reduces system costs and improves spectrum efficiency.The MSMS outperforms traditional Space-time Block Coding(STBC)strategies regarding separation performance,particularly in Block Error Rate(BLER)metrics.Modulation constellation diagrams further analyze the effectiveness of multi-source signal mixture separation.Moreover,this study extends the MSMS framework from a two-user scenario to a three-user scenario,further demonstrating the flexibility and scalability of the proposed architecture.
文摘This paper studies wireless vehicular communication(VehCom)in intelligent transportation systems using an orthogonal frequency division multiplexing with index modulation(OFDM-IM).In the concept of IM,data is transmitted not only through the modulated symbols but also via the indices of the active subcarriers.In contrast to the original OFDM,OFDM-IM activates only non-zero subcarriers,increasing energy efficiency.However,the pilotassisted channel estimation(CE)method is a significant challenge in OFDM-IM,where the desired pilot subcarrier interval is related to the OFDM-IM subblock length.This paper proposes a walsh-scattered pilot-assisted CE for OFDM-IM VehCom.The optimum walsh-scattered pilot assignment is proposed to improve the transmission efficiency.Furthermore,a space-time block code with a high transmit diversity gain is employed for OFDM-IM VehCom to enhance VehCom's signal quality.The results show that the proposed method performs higher CE accuracy and better bit-error rate with significant spectral and energy efficiencies than conventional methods.
基金supported in part by the National Natural Science Foundation of China under Grants 62025110,62271093sponsored by Natural Science Foundation of Chongqing,China,under Grant CSTB2023NSCQ-LZX0108.
文摘Efficient energy utilization in covert communication sustains covertness while assuring communication quality and efficiency.This paper investigates covert communication energy efficiency(EE)in direct uplink satellite-ground communications,focusing on enhancing system EE via optimized transmit beamforming and satellite orbit altitude selection.This paper first establishes an optimization problem to maximize system EE in a direct uplink satelliteground covert communication scenario.To solve this non-convex optimization problem,it is decomposed into two subproblems and solved using the successive convex approximation(SCA)method.Based on the above methods,this paper proposes an overall iterative optimization algorithm.Simulation results demonstrate that the proposed algorithm surpasses the conventional baseline algorithms in terms of system EE.Furthermore,they elucidate the correlation between the amount of information received by the receiver and the variations in the satellite’s orbital altitude.
基金National Basic Research Plan Project of China,No.2023YFC3708303the National Natural Science Foundation of China,No.82241084the High-level Talent in Public Health of Beijing,No.Discipline Leaders-03-29(all to XL).
文摘Long-term exposure to ambient fine particulate matter(PM2.5)may increase the risk of neurotoxicity in human populations.However,research studies on the underlying mechanisms of chronic PM2.5-induced depression-like behaviors,and potential therapeutical strategies,remain scarce.In the present study,after long-term exposure to real-world PM2.5 for 15 weeks,male mice displayed depression-like behaviors,which were revealed using the open field and sucrose preference tests.Mechanistically,chronic PM2.5 exposure promoted astrocytic A1 polarization and disrupted reduction-oxidation balance in the mouse hippocampus.Furthermore,PM2.5-exposed mice displayed pathological damage to hippocampal neurons as well as the inhibition of nuclear factor erythroid 2-related factor 2 signaling.Astrocytic ablation of nuclear factor erythroid 2-related factor 2 exacerbated PM2.5-induced hippocampal neuronal injury in mice via the disruption of astrocyte-to-microglia communication;this finding was confirmed in mice with bilateral and unilateral hippocampal astrocytic Nfe2l2 knockdown.Importantly,the upregulation of nuclear factor erythroid 2-related factor 2 activation by procyanidin significantly ameliorated PM2.5-induced depression-like behaviors through the remodeling of astrocyte-to-microglia communication.Together,our findings shed light on the important role of hippocampal astrocytic nuclear factor erythroid 2-related factor 2 activation for maintaining astrocyte-to-microglia communication,and indicate potential research avenues for therapeutic strategies against PM2.5-induced depresson-like behaviors.
