Federated learning(FL)is a distributed machine learning approach that could provide secure 6G communications to preserve user privacy.In 6G communications,unmanned aerial vehicles(UAVs)are widely used as FL parameter ...Federated learning(FL)is a distributed machine learning approach that could provide secure 6G communications to preserve user privacy.In 6G communications,unmanned aerial vehicles(UAVs)are widely used as FL parameter servers to collect and broadcast related parameters due to the advantages of easy deployment and high flexibility.However,the challenge of limited energy restricts the populariza⁃tion of UAV-enabled FL applications.An airground integrated low-energy federated learning framework is proposed,which minimizes the overall energy consumption of application communication while maintaining the quality of the FL model.Specifically,a hierarchical FL framework is proposed,where base stations(BSs)aggregate model parameters updated from their surrounding users separately and send the aggregated model parameters to the server,thereby reducing the energy consumption of communication.In addition,we optimize the deploy⁃ment of UAVs through a deep Q-network approach to minimize their energy consumption for transmission as well as movement,thus improv⁃ing the energy efficiency of the airground integrated system.The evaluation results show that our proposed method can reduce the system en⁃ergy consumption while maintaining the accuracy of the FL model.展开更多
As the 5G communication networks are being widely deployed worldwide,both industry and academia have started to move beyond 5G and explore 6G communications.It is generally believed that 6G will be established on ubiq...As the 5G communication networks are being widely deployed worldwide,both industry and academia have started to move beyond 5G and explore 6G communications.It is generally believed that 6G will be established on ubiquitous Artificial Intelligence(AI)to achieve data-driven Machine Learning(ML)solutions in heterogeneous and massive-scale networks.However,traditional ML techniques require centralized data collection and processing by a central server,which is becoming a bottleneck of large-scale implementation in daily life due to significantly increasing privacy concerns.Federated learning,as an emerging distributed AI approach with privacy preservation nature,is particularly attractive for various wireless applications,especially being treated as one of the vital solutions to achieve ubiquitous AI in 6G.In this article,we first introduce the integration of 6G and federated learning and provide potential federated learning applications for 6G.We then describe key technical challenges,the corresponding federated learning methods,and open problems for future research on federated learning in the context of 6G communications.展开更多
With the development of wireless mobile communication technology,the demand for wireless communication rate and frequency increases year by year.Existing wireless mobile communication frequency tends to be saturated,w...With the development of wireless mobile communication technology,the demand for wireless communication rate and frequency increases year by year.Existing wireless mobile communication frequency tends to be saturated,which demands for new solutions.Terahertz(THz)communication has great potential for the future mobile communications(Beyond 5G),and is also an important technique for the high data rate transmission in spatial information network.THz communication has great application prospects in military-civilian integration and coordinated development.In China,important breakthroughs have been achieved for the key techniques of THz high data rate communications,which is practically keeping up with the most advanced technological level in the world.Therefore,further intensifying efforts on the development of THz communication have the strategic importance for China in leading the development of future wireless communication techniques and the standardization process of Beyond 5G.This paper analyzes the performance of the MIMO channel in the Terahertz(THz)band and a discrete mathematical method is used to propose a novel channel model.Then,a channel capacity model is proposed by the combination of path loss and molecular absorption in the THz band based on the CSI at the receiver.Simulation results show that the integration of MIMO in the THz band gives better data rate and channel capacity as compared with a single channel.展开更多
The rapid advancement of 6G communication networks presents both considerable problems and opportunities in network management,necessitating sophisticated solutions that extend beyond conventional methods.This study s...The rapid advancement of 6G communication networks presents both considerable problems and opportunities in network management,necessitating sophisticated solutions that extend beyond conventional methods.This study seeks to investigate and evaluate autonomous network management solutions designed for 6G communication networks,highlighting their technical advantages and potential implications.We examine the role of Artificial Intelligence(AI),Machine Learning(ML),and network automation in facilitating self-organization,optimization,and decision-making within critical network domains,including spectrum management,traffic load balancing,fault detection,and security and privacy.We examine the integration of edge computing and Distributed Ledger Technologies(DLT),specifically blockchain,to improve trust,transparency,and security in autonomous networks.This study provides a comprehensive understanding of the technological developments driving fully autonomous,efficient,and resilient 6G network infrastructures by methodically analyzing existing methodologies,identifying significant research gaps,and exploring potential prospects.The results offer significant insights for researchers,engineers,and industry experts involved in the development and deployment of advanced autonomous network management systems.展开更多
Future 6G communications will open up opportunities for innovative applications,including Cyber-Physical Systems,edge computing,supporting Industry 5.0,and digital agriculture.While automation is creating efficiencies...Future 6G communications will open up opportunities for innovative applications,including Cyber-Physical Systems,edge computing,supporting Industry 5.0,and digital agriculture.While automation is creating efficiencies,it can also create new cyber threats,such as vulnerabilities in trust and malicious node injection.Denialof-Service(DoS)attacks can stop many forms of operations by overwhelming networks and systems with data noise.Current anomaly detection methods require extensive software changes and only detect static threats.Data collection is important for being accurate,but it is often a slow,tedious,and sometimes inefficient process.This paper proposes a new wavelet transformassisted Bayesian deep learning based probabilistic(WT-BDLP)approach tomitigate malicious data injection attacks in 6G edge networks.The proposed approach combines outlier detection based on a Bayesian learning conditional variational autoencoder(Bay-LCVariAE)and traffic pattern analysis based on continuous wavelet transform(CWT).The Bay-LCVariAE framework allows for probabilistic modelling of generative features to facilitate capturing how features of interest change over time,spatially,and for recognition of anomalies.Similarly,CWT allows emphasizing the multi-resolution spectral analysis and permits temporally relevant frequency pattern recognition.Experimental testing showed that the flexibility of the Bayesian probabilistic framework offers a vast improvement in anomaly detection accuracy over existing methods,with a maximum accuracy of 98.21%recognizing anomalies.展开更多
Adaptive robust secure framework plays a vital role in implementing intelligent automation and decentralized decision making of Industry 5.0.Latency,privacy risks and the complexity of industrial networks have been pr...Adaptive robust secure framework plays a vital role in implementing intelligent automation and decentralized decision making of Industry 5.0.Latency,privacy risks and the complexity of industrial networks have been preventing attempts at traditional cloud-based learning systems.We demonstrate that,to overcome these challenges,for instance,the EdgeGuard-IoT framework,a 6G edge intelligence framework enhancing cybersecurity and operational resilience of the smart grid,is needed on the edge to integrate Secure Federated Learning(SFL)and Adaptive Anomaly Detection(AAD).With ultra-reliable low latency communication(URLLC)of 6G,artificial intelligence-based network orchestration,and massive machine type communication(mMTC),EdgeGuard-IoT brings real-time,distributed intelligence on the edge,and mitigates risks in data transmission and enhances privacy.EdgeGuard-IoT,with a hierarchical federated learning framework,helps edge devices to collaboratively train models without revealing the sensitive grid data,which is crucial in the smart grid where real-time power anomaly detection and the decentralization of the energy management are a big deal.The hybrid AI models driven adaptive anomaly detection mechanism immediately raises the thumb if the grid stability and strength are negatively affected due to cyber threats,faults,and energy distribution,thereby keeping the grid stable with resilience.The proposed framework also adopts various security means within the blockchain and zero-trust authentication techniques to reduce the adversarial attack risks and model poisoning during federated learning.EdgeGuard-IoT shows superior detection accuracy,response time,and scalability performance at a much reduced communication overhead via extensive simulations and deployment in real-world case studies in smart grids.This research pioneers a 6G-driven federated intelligence model designed for secure,self-optimizing,and resilient Industry 5.0 ecosystems,paving the way for next-generation autonomous smart grids and industrial cyber-physical systems.展开更多
The integration of the dynamic adaptive routing(DAR)algorithm in unmanned aerial vehicle(UAV)networks offers a significant advancement in addressing the challenges posed by next-generation communication systems like 6...The integration of the dynamic adaptive routing(DAR)algorithm in unmanned aerial vehicle(UAV)networks offers a significant advancement in addressing the challenges posed by next-generation communication systems like 6G.DAR’s innovative framework incorporates real-time path adjustments,energy-aware routing,and predictive models,optimizing reliability,latency,and energy efficiency in UAV operations.This study demonstrated DAR’s superior performance in dynamic,large-scale environments,proving its adaptability and scalability for real-time applications.As 6G networks evolve,challenges such as bandwidth demands,global spectrum management,security vulnerabilities,and financial feasibility become prominent.DAR aligns with these demands by offering robust solutions that enhance data transmission while ensuring network reliability.However,obstacles like global route optimization and signal interference in urban areas necessitate further refinement.Future directions should explore hybrid approaches,the integration of machine learning,and comprehensive real-world testing to maximize DAR’s capabilities.The findings underscore DAR’s pivotal role in enabling efficient and sustainable UAV communication systems,contributing to the broader landscape of wireless technology and laying a foundation for the seamless transition to 6G networks.展开更多
A novel digital twin(DT)enabled channel model for 6G vehicular communications in Beijing Central Business District(Beijing CBD)is proposed,which can support the design of intelligent transportation systems(ITSs).A DT ...A novel digital twin(DT)enabled channel model for 6G vehicular communications in Beijing Central Business District(Beijing CBD)is proposed,which can support the design of intelligent transportation systems(ITSs).A DT space for Beijing CBD is constructed,and two typical transportation periods,i.e.,peak and off-peak hours,are considered to characterize the vehicular communication channel better.Based on the constructed DT space,a DT-enabled vehicular communication dataset is developed,including light detection and ranging(LiDAR)point clouds,RGB images,and channel information.With the assistance of LiDAR point clouds and RGB images,the scatterer parameters,including number,distance,angle,power,and velocity,are analyzed under different transportation periods.The channel non-stationarity and consistency are mimicked in the proposed model.The key channel statistical properties are derived and simulated.Compared to ray-tracing(RT)results,the accuracy of the proposed model is verified.展开更多
The advancement of 6G wireless communication technology has facilitated the integration of Vehicular Ad-hoc Networks(VANETs).However,the messages transmitted over the public channel in the open and dynamic VANETs are ...The advancement of 6G wireless communication technology has facilitated the integration of Vehicular Ad-hoc Networks(VANETs).However,the messages transmitted over the public channel in the open and dynamic VANETs are vulnerable to malicious attacks.Although numerous researchers have proposed authentication schemes to enhance the security of Vehicle-to-Vehicle(V2V)communication,most existing methodologies face two significant challenges:(1)the majority of the schemes are not lightweight enough to support realtime message interaction among vehicles;(2)the sensitive information like identity and position is at risk of being compromised.To tackle these issues,we propose a lightweight dual authentication protocol for V2V communication based on Physical Unclonable Function(PUF).The proposed scheme accomplishes dual authentication between vehicles by the combination of Zero-Knowledge Proof(ZKP)and MASK function.The security analysis proves that our scheme provides both anonymous authentication and information unlinkability.Additionally,the performance analysis demonstrates that the computation overhead of our scheme is approximately reduced 23.4% compared to the state-of-the-art schemes.The practical simulation conducted in a 6G network environment demonstrates the feasibility of 6G-based VANETs and their potential for future advancements.展开更多
Future networks communication scenarios by the 2030s will include notable applications are three-dimensional(3D)calls,haptics communications,unmanned mobility,tele-operated driving,bio-internet of things,and the Nanoi...Future networks communication scenarios by the 2030s will include notable applications are three-dimensional(3D)calls,haptics communications,unmanned mobility,tele-operated driving,bio-internet of things,and the Nanointernet of things.Unlike the current scenario in which megahertz bandwidth are sufficient to drive the audio and video components of user applications,the future networks of the 2030s will require bandwidths in several gigahertzes(GHz)(from tens of gigahertz to 1 terahertz[THz])to perform optimally.Based on the current radio frequency allocation chart,it is not possible to obtain such a wide contiguous radio spectrum below 90 GHz(0.09 THz).Interestingly,these contiguous blocks of radio spectrum are readily available in the higher electromagnetic spectrum,specifically in the Terahertz(THz)frequency band.The major contribution of this study is discussing the substantial issues and key features of THz waves,which include(i)key features and significance of THz frequency;(ii)recent regulatory;(iii)the most promising applications;and(iv)possible open research issues.These research topics were deeply investigated with the aim of providing a specific,synopsis,and encompassing conclusion.Thus,this article will be as a catalyst towards exploring new frontiers for future networks of the 2030s.展开更多
Since around 1980,a new generation of wireless technology has arisen approximately every 10 years.First-generation(1G)and secondgeneration(2G)began with voice and eventually introduced more and more data in third-gene...Since around 1980,a new generation of wireless technology has arisen approximately every 10 years.First-generation(1G)and secondgeneration(2G)began with voice and eventually introduced more and more data in third-generation(3G)and became highly popular in the fourthgeneration(4G).To increase the data rate along with low latency and mass connectivity the fifth-generation(5G)networks are being installed from 2020.However,the 5G technology will not be able to fulfill the data demand at the end of this decade.Therefore,it is expected that 6G communication networks will rise,providing better services through the implementation of new enabling technologies and allowing users to connect everywhere.6G technology would not be confined to cellular communications networks,but would also comply with non-terrestrial communication system requirements,such as satellite communication.The ultimate objectives of this work are to address the major challenges of the evolution of cellular communication networks and to discourse the recent growth of the industry based on the key scopes of application and challenges.The main areas of research topics are summarized into(i)major 6G wireless networkmilestones;(ii)key performance indicators;(iii)future new applications;and(iv)potential fields of research,challenges,and open issues.展开更多
The mobility and connective capabilities of unmanned aerial vehicles(UAVs)are becoming more and more important in defense,commercial,and research domains.However,their open communication makes UAVs susceptible toundes...The mobility and connective capabilities of unmanned aerial vehicles(UAVs)are becoming more and more important in defense,commercial,and research domains.However,their open communication makes UAVs susceptible toundesirablepassive attacks suchas eavesdroppingor jamming.Recently,the inefficiencyof traditional cryptography-based techniques has led to the addition of Physical Layer Security(PLS).This study focuses on the advanced PLS method for passive eavesdropping in UAV-aided vehicular environments,proposing a solution to complement the conventional cryptography approach.Initially,we present a performance analysis of first-order secrecy metrics in 6G-enabled UAV systems,namely hybrid outage probability(HOP)and secrecy outage probability(SOP)over 2×2 Nakagami-m channels.Later,we propose a novel technique for mitigating passive eavesdropping,which considers first-order secrecy metrics as an optimization problem and determines their lower and upper bounds.Finally,we conduct an analysis of bounded HOP and SOP using the interactive Nakagami-m channel,considering the multiple-input-multiple-output configuration of the UAV system.The findings indicate that 2×2 Nakagami-mis a suitable fadingmodel under constant velocity for trustworthy receivers and eavesdroppers.The results indicate that UAV mobility has some influence on an eavesdropper’s intrusion during line-of-sight-enabled communication and can play an important role in improving security against passive eavesdroppers.展开更多
In this paper,ambient IoT is used as a typical use case of massive connections for the sixth generation(6G)mobile communications where we derive the performance requirements to facilitate the evaluation of technical s...In this paper,ambient IoT is used as a typical use case of massive connections for the sixth generation(6G)mobile communications where we derive the performance requirements to facilitate the evaluation of technical solutions.A rather complete design of unsourced multiple access is proposed in which two key parts:a compressed sensing module for active user detection,and a sparse interleaver-division multiple access(SIDMA)module are simulated side by side on a same platform at balanced signal to noise ratio(SNR)operating points.With a proper combination of compressed sensing matrix,a convolutional encoder,receiver algorithms,the simulated performance results appear superior to the state-of-the-art benchmark,yet with relatively less complicated processing.展开更多
In 5G networks,optimization of antenna beam weights of base stations has become the key application of AI for network optimization.For 6G,higher frequency bands and much denser cells are expected,and the importance of...In 5G networks,optimization of antenna beam weights of base stations has become the key application of AI for network optimization.For 6G,higher frequency bands and much denser cells are expected,and the importance of automatic and accurate beamforming assisted by AI will become more prominent.In existing network,servers are“patched”to network equipment to act as a centralized brain for model training and inference leading to high transmission overhead,large inference latency and potential risks of data security.Decentralized architectures have been proposed to achieve flexible parameter configuration and fast local response,but it is inefficient in collecting and sharing global information among base stations.In this paper,we propose a novel solution based on a collaborative cloud edge architecture for multi-cell joint beamforming optimization.We analyze the performance and costs of the proposed solution with two other architectural solutions by simulation.Compared with the centralized solution,our solution improves prediction accuracy by 24.66%,and reduces storage cost by 83.82%.Compared with the decentralized solution,our solution improves prediction accuracy by 68.26%,and improves coverage performance by 0.4 dB.At last,the future research work is prospected.展开更多
Spatio-temporal cellular network traffic prediction at wide-area level plays an important role in resource reconfiguration,traffic scheduling and intrusion detection,thus potentially supporting connected intelligence ...Spatio-temporal cellular network traffic prediction at wide-area level plays an important role in resource reconfiguration,traffic scheduling and intrusion detection,thus potentially supporting connected intelligence of the sixth generation of mobile communications technology(6G).However,the existing studies just focus on the spatio-temporal modeling of traffic data of single network service,such as short message,call,or Internet.It is not conducive to accurate prediction of traffic data,characterised by diverse network service,spatio-temporality and supersize volume.To address this issue,a novel multi-task deep learning framework is developed for citywide cellular network traffic prediction.Functionally,this framework mainly consists of a dual modular feature sharing layer and a multi-task learning layer(DMFS-MT).The former aims at mining long-term spatio-temporal dependencies and local spatio-temporal fluctuation trends in data,respectively,via a new combination of convolutional gated recurrent unit(ConvGRU)and 3-dimensional convolutional neural network(3D-CNN).For the latter,each task is performed for predicting service-specific traffic data based on a fully connected network.On the real-world Telecom Italia dataset,simulation results demonstrate the effectiveness of our proposal through prediction performance measure,spatial pattern comparison and statistical distribution verification.展开更多
Sixth Generation(6G)wireless communication network has been expected to provide global coverage,enhanced spectral efficiency,and AI(Artificial Intelligence)-native intelligence,etc.To meet these requirements,the compu...Sixth Generation(6G)wireless communication network has been expected to provide global coverage,enhanced spectral efficiency,and AI(Artificial Intelligence)-native intelligence,etc.To meet these requirements,the computational concept of Decision-Making of cognition intelligence,its implementation framework adapting to foreseen innovations on networks and services,and its empirical evaluations are key techniques to guarantee the generationagnostic intelligence evolution of wireless communication networks.In this paper,we propose an Intelligent Decision Making(IDM)framework,acting as the role of network brain,based on Reinforcement Learning modelling philosophy to empower autonomous intelligence evolution capability to 6G network.Besides,usage scenarios and simulation demonstrate the generality and efficiency of IDM.We hope that some of the ideas of IDM will assist the research of 6G network in a new or different light.展开更多
The application of Non-Orthogonal Multiple Access(NOMA) technology into satelliteaerial-ground integrated networks can meet the requirements of ultra-high rate and massive connectivity for the Sixth-Generation(6G) com...The application of Non-Orthogonal Multiple Access(NOMA) technology into satelliteaerial-ground integrated networks can meet the requirements of ultra-high rate and massive connectivity for the Sixth-Generation(6G) communication systems. We consider an uplink NOMA scenario for such a satellite-aerial-ground integrated network where multiple users communicate with satellite under the help of an Unmanned Aerial Vehicle(UAV) as an aerial relay equipped with a phased array. Supposing that buffer-aided decode-and-forward protocol is adopted at the UAV relay, we first formulate an optimization problem to maximize Ergodic Sum Rate(ESR) of the considered system subject to individual power constraint and quality-of-service constraint of each user.Then, with known imperfect channel state information of each user, we propose a joint power allocation and robust Beam Forming(BF) iterative algorithm to maximize ESR for the user-to-UAV link. Besides, to take the advantages of Free-Space Optical(FSO) and millimeter Wave(mmWave)communications, we present a switch-based hybrid FSO/mmWave scheme and a robust BF algorithm for the UAV-to-satellite link to achieve higher rate. Moreover, a closed-form ESR expression is derived. Finally, the effectiveness and correctness of the proposed solutions are verified by numerical simulations, and the performance evaluation results show that the proposed solutions not only achieve performance enhancement and robustness, but also outperform the orthogonal multiple access significantly.展开更多
Quantum key agreement is a promising key establishing protocol that can play a significant role in securing 5G/6G communication networks.Recently,Liu et al.(Quantum Information Processing 18(8):1-10,2019)proposed a mu...Quantum key agreement is a promising key establishing protocol that can play a significant role in securing 5G/6G communication networks.Recently,Liu et al.(Quantum Information Processing 18(8):1-10,2019)proposed a multi-party quantum key agreement protocol based on four-qubit cluster states was proposed.The aim of their protocol is to agree on a shared secret key among multiple remote participants.Liu et al.employed four-qubit cluster states to be the quantum resources and the X operation to securely share a secret key.In addition,Liu et al.’s protocol guarantees that each participant makes an equal contribution to the final key.The authors also claimed that the proposed protocol is secure against participant attack and dishonest participants cannot generate the final shared key alone.However,we show here that Liu et al.protocol is insecure against a collusive attack,where dishonest participants can retrieve the private inputs of a trustworthy participant without being caught.Additionally,the corresponding modifications are presented to address these security flaws in Liu et al.’s protocol.展开更多
Simultaneously transmitting and reflecting reconfigurable intelligent surfaces(STAR-RISs)have been attracting significant attention in both academia and industry for their advantages of achieving 360°coverage and...Simultaneously transmitting and reflecting reconfigurable intelligent surfaces(STAR-RISs)have been attracting significant attention in both academia and industry for their advantages of achieving 360°coverage and enhanced degrees-of-freedom.This article first identifies the fundamentals of STAR-RIS,by discussing the hardware models,channel models,and signal models.Then,three representative categorizing approaches for STAR-RISs are introduced from the phase-shift,directional,and energy consumption perspectives.Furthermore,the beamforming design of STAR-RISs is investigated for both independent and coupled phase-shift cases.As a recent advance,a general optimization framework,which has high compatibility and provable optimality regardless of the application scenarios,is proposed.As a further advance,several promising applications are discussed to demonstrate the potential benefits of applying STAR-RISs in sixth-generation wireless communication.Lastly,a few future directions and research opportunities are highlighted.展开更多
Near-field communication using large-scale antenna arrays is one of the hot research topics in the sixth-generation(6G)wireless communication.Reconfigurable intelligent surface(RIS)is a cost-effective method for manip...Near-field communication using large-scale antenna arrays is one of the hot research topics in the sixth-generation(6G)wireless communication.Reconfigurable intelligent surface(RIS)is a cost-effective method for manipulating electromagnetic waves in the near field.We propose a 2-bit dual-polarized RIS that has the merits of low cost,low power consumption,high phase accuracy,and polarization diversity.Each element consists of an aperture-coupled microstrip patch,two single-pole-fourthrow(SP4T)switches,and two groups of microstrip delay lines.Two-bit phase shift is achieved by using only one SP4T switch that controls the connection of four parallel delay branches.Dual polarization is generated by placing two orthogonal slots with two 2-bit phase shifters.A 15×15 RIS prototype operating in the 3.6 GHz band is fabricated and measured.The beam can be scanned in the±60°range,with a peak aperture efficiency of 40.1%for horizontal polarization and 38.3%for vertical polarization.What is more,the total power consumption of the RIS is merely about 100 mW,which is very attractive for massive deployment in 6G near-field communication.展开更多
基金supported in part by the National Key Research and Development Program of China under Grant No. 2021ZD0112400the NSFC under Grant No. 62202080+3 种基金the NSFC-Liaoning Province United Foundation under Grant No. U1908214the CCF-Tencent Open Fund under Grant No. IAGR20210116the Fundamental Research Funds for the Central Universities under Grant Nos. DUT21TD107 and DUT20RC(3)039the Liaoning Revitalization Talents Program under Grant No. XLYC2008017
文摘Federated learning(FL)is a distributed machine learning approach that could provide secure 6G communications to preserve user privacy.In 6G communications,unmanned aerial vehicles(UAVs)are widely used as FL parameter servers to collect and broadcast related parameters due to the advantages of easy deployment and high flexibility.However,the challenge of limited energy restricts the populariza⁃tion of UAV-enabled FL applications.An airground integrated low-energy federated learning framework is proposed,which minimizes the overall energy consumption of application communication while maintaining the quality of the FL model.Specifically,a hierarchical FL framework is proposed,where base stations(BSs)aggregate model parameters updated from their surrounding users separately and send the aggregated model parameters to the server,thereby reducing the energy consumption of communication.In addition,we optimize the deploy⁃ment of UAVs through a deep Q-network approach to minimize their energy consumption for transmission as well as movement,thus improv⁃ing the energy efficiency of the airground integrated system.The evaluation results show that our proposed method can reduce the system en⁃ergy consumption while maintaining the accuracy of the FL model.
基金supported by the National Research Foundation(NRF),Singapore,under Singapore Energy Market Authority(EMA),Energy Resilience,NRF2017EWT-EP003-041,Singapore NRF2015NRF-ISF001-2277Singapore NRF National Satellite of Excellence,Design Science and Technology for Secure Critical Infrastructure NSoE DeST-SCI2019-0007+4 种基金A*STARNTU-SUTD Joint Research Grant on Artificial Intelligence for the Future of Manufacturing RGANS1906,Wallenberg AI,Autonomous Systems and Software Program and Nanyang Technological University(WASP/NTU)under grant M4082187(4080),and NTU-We Bank JRI(NWJ-2020-004)Alibaba Group through Alibaba Innovative Research(AIR)Program and Alibaba-NTU Singapore Joint Research Institute(JRI),NTU,SingaporeNational Key Research and Development Program of China under Grant 2018YFC0809803 and Grant 2019YFB2101901Young Innovation Talents Project in Higher Education of Guangdong Province,China under grant No.2018KQNCX333in part by the National Science Foundation of China under Grant 61702364。
文摘As the 5G communication networks are being widely deployed worldwide,both industry and academia have started to move beyond 5G and explore 6G communications.It is generally believed that 6G will be established on ubiquitous Artificial Intelligence(AI)to achieve data-driven Machine Learning(ML)solutions in heterogeneous and massive-scale networks.However,traditional ML techniques require centralized data collection and processing by a central server,which is becoming a bottleneck of large-scale implementation in daily life due to significantly increasing privacy concerns.Federated learning,as an emerging distributed AI approach with privacy preservation nature,is particularly attractive for various wireless applications,especially being treated as one of the vital solutions to achieve ubiquitous AI in 6G.In this article,we first introduce the integration of 6G and federated learning and provide potential federated learning applications for 6G.We then describe key technical challenges,the corresponding federated learning methods,and open problems for future research on federated learning in the context of 6G communications.
基金Hallym University Research Fund,2019(HRF-201905-013).
文摘With the development of wireless mobile communication technology,the demand for wireless communication rate and frequency increases year by year.Existing wireless mobile communication frequency tends to be saturated,which demands for new solutions.Terahertz(THz)communication has great potential for the future mobile communications(Beyond 5G),and is also an important technique for the high data rate transmission in spatial information network.THz communication has great application prospects in military-civilian integration and coordinated development.In China,important breakthroughs have been achieved for the key techniques of THz high data rate communications,which is practically keeping up with the most advanced technological level in the world.Therefore,further intensifying efforts on the development of THz communication have the strategic importance for China in leading the development of future wireless communication techniques and the standardization process of Beyond 5G.This paper analyzes the performance of the MIMO channel in the Terahertz(THz)band and a discrete mathematical method is used to propose a novel channel model.Then,a channel capacity model is proposed by the combination of path loss and molecular absorption in the THz band based on the CSI at the receiver.Simulation results show that the integration of MIMO in the THz band gives better data rate and channel capacity as compared with a single channel.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2025-00559546)supported by the IITP(Institute of Information&Communications Technology Planning&Evaluation)-ITRC(Information Technology Research Center)grant funded by the Korea government(Ministry of Science and ICT)(IITP-2025-RS-2023-00259004)+1 种基金the support by the Deanship of Scientific Research through King Khalid UniversitySaudi Arabia funded by the Large Group Research Project RGP2/267/46。
文摘The rapid advancement of 6G communication networks presents both considerable problems and opportunities in network management,necessitating sophisticated solutions that extend beyond conventional methods.This study seeks to investigate and evaluate autonomous network management solutions designed for 6G communication networks,highlighting their technical advantages and potential implications.We examine the role of Artificial Intelligence(AI),Machine Learning(ML),and network automation in facilitating self-organization,optimization,and decision-making within critical network domains,including spectrum management,traffic load balancing,fault detection,and security and privacy.We examine the integration of edge computing and Distributed Ledger Technologies(DLT),specifically blockchain,to improve trust,transparency,and security in autonomous networks.This study provides a comprehensive understanding of the technological developments driving fully autonomous,efficient,and resilient 6G network infrastructures by methodically analyzing existing methodologies,identifying significant research gaps,and exploring potential prospects.The results offer significant insights for researchers,engineers,and industry experts involved in the development and deployment of advanced autonomous network management systems.
文摘Future 6G communications will open up opportunities for innovative applications,including Cyber-Physical Systems,edge computing,supporting Industry 5.0,and digital agriculture.While automation is creating efficiencies,it can also create new cyber threats,such as vulnerabilities in trust and malicious node injection.Denialof-Service(DoS)attacks can stop many forms of operations by overwhelming networks and systems with data noise.Current anomaly detection methods require extensive software changes and only detect static threats.Data collection is important for being accurate,but it is often a slow,tedious,and sometimes inefficient process.This paper proposes a new wavelet transformassisted Bayesian deep learning based probabilistic(WT-BDLP)approach tomitigate malicious data injection attacks in 6G edge networks.The proposed approach combines outlier detection based on a Bayesian learning conditional variational autoencoder(Bay-LCVariAE)and traffic pattern analysis based on continuous wavelet transform(CWT).The Bay-LCVariAE framework allows for probabilistic modelling of generative features to facilitate capturing how features of interest change over time,spatially,and for recognition of anomalies.Similarly,CWT allows emphasizing the multi-resolution spectral analysis and permits temporally relevant frequency pattern recognition.Experimental testing showed that the flexibility of the Bayesian probabilistic framework offers a vast improvement in anomaly detection accuracy over existing methods,with a maximum accuracy of 98.21%recognizing anomalies.
基金supported by Department of Information Technology,University of Tabuk,Tabuk,71491,Saudi Arabia.
文摘Adaptive robust secure framework plays a vital role in implementing intelligent automation and decentralized decision making of Industry 5.0.Latency,privacy risks and the complexity of industrial networks have been preventing attempts at traditional cloud-based learning systems.We demonstrate that,to overcome these challenges,for instance,the EdgeGuard-IoT framework,a 6G edge intelligence framework enhancing cybersecurity and operational resilience of the smart grid,is needed on the edge to integrate Secure Federated Learning(SFL)and Adaptive Anomaly Detection(AAD).With ultra-reliable low latency communication(URLLC)of 6G,artificial intelligence-based network orchestration,and massive machine type communication(mMTC),EdgeGuard-IoT brings real-time,distributed intelligence on the edge,and mitigates risks in data transmission and enhances privacy.EdgeGuard-IoT,with a hierarchical federated learning framework,helps edge devices to collaboratively train models without revealing the sensitive grid data,which is crucial in the smart grid where real-time power anomaly detection and the decentralization of the energy management are a big deal.The hybrid AI models driven adaptive anomaly detection mechanism immediately raises the thumb if the grid stability and strength are negatively affected due to cyber threats,faults,and energy distribution,thereby keeping the grid stable with resilience.The proposed framework also adopts various security means within the blockchain and zero-trust authentication techniques to reduce the adversarial attack risks and model poisoning during federated learning.EdgeGuard-IoT shows superior detection accuracy,response time,and scalability performance at a much reduced communication overhead via extensive simulations and deployment in real-world case studies in smart grids.This research pioneers a 6G-driven federated intelligence model designed for secure,self-optimizing,and resilient Industry 5.0 ecosystems,paving the way for next-generation autonomous smart grids and industrial cyber-physical systems.
基金This research was supported by ESIEA Paris through internal research resources provided by esieaLab LDR.
文摘The integration of the dynamic adaptive routing(DAR)algorithm in unmanned aerial vehicle(UAV)networks offers a significant advancement in addressing the challenges posed by next-generation communication systems like 6G.DAR’s innovative framework incorporates real-time path adjustments,energy-aware routing,and predictive models,optimizing reliability,latency,and energy efficiency in UAV operations.This study demonstrated DAR’s superior performance in dynamic,large-scale environments,proving its adaptability and scalability for real-time applications.As 6G networks evolve,challenges such as bandwidth demands,global spectrum management,security vulnerabilities,and financial feasibility become prominent.DAR aligns with these demands by offering robust solutions that enhance data transmission while ensuring network reliability.However,obstacles like global route optimization and signal interference in urban areas necessitate further refinement.Future directions should explore hybrid approaches,the integration of machine learning,and comprehensive real-world testing to maximize DAR’s capabilities.The findings underscore DAR’s pivotal role in enabling efficient and sustainable UAV communication systems,contributing to the broader landscape of wireless technology and laying a foundation for the seamless transition to 6G networks.
基金supported in part by the National Natural Science Foundation of China under Grant Nos.62371273,62125101 and 62341101the Taishan Scholars Program under Grant No.tsqn202312307+7 种基金the Young Elite Scientists Sponsorship Program by CAST under Grant No.YESS20230372the Shandong Natural Science Foundation under Grant No.ZR2023YQ058the New Cornerstone Science Foundation through the Xplorer Prizethe Xiaomi Young Talents Programthe open research fund of National Mobile Communications Research Laboratory,Southeast University under Grant No.2025D04the China National Postdoctoral Program for Innovative Talents under Grant No.BX20240007the China Postdoctoral Science Foundation under Grant No.2024M760111the Beijing Natural Science Foundation under Grant No.4254067。
文摘A novel digital twin(DT)enabled channel model for 6G vehicular communications in Beijing Central Business District(Beijing CBD)is proposed,which can support the design of intelligent transportation systems(ITSs).A DT space for Beijing CBD is constructed,and two typical transportation periods,i.e.,peak and off-peak hours,are considered to characterize the vehicular communication channel better.Based on the constructed DT space,a DT-enabled vehicular communication dataset is developed,including light detection and ranging(LiDAR)point clouds,RGB images,and channel information.With the assistance of LiDAR point clouds and RGB images,the scatterer parameters,including number,distance,angle,power,and velocity,are analyzed under different transportation periods.The channel non-stationarity and consistency are mimicked in the proposed model.The key channel statistical properties are derived and simulated.Compared to ray-tracing(RT)results,the accuracy of the proposed model is verified.
文摘The advancement of 6G wireless communication technology has facilitated the integration of Vehicular Ad-hoc Networks(VANETs).However,the messages transmitted over the public channel in the open and dynamic VANETs are vulnerable to malicious attacks.Although numerous researchers have proposed authentication schemes to enhance the security of Vehicle-to-Vehicle(V2V)communication,most existing methodologies face two significant challenges:(1)the majority of the schemes are not lightweight enough to support realtime message interaction among vehicles;(2)the sensitive information like identity and position is at risk of being compromised.To tackle these issues,we propose a lightweight dual authentication protocol for V2V communication based on Physical Unclonable Function(PUF).The proposed scheme accomplishes dual authentication between vehicles by the combination of Zero-Knowledge Proof(ZKP)and MASK function.The security analysis proves that our scheme provides both anonymous authentication and information unlinkability.Additionally,the performance analysis demonstrates that the computation overhead of our scheme is approximately reduced 23.4% compared to the state-of-the-art schemes.The practical simulation conducted in a 6G network environment demonstrates the feasibility of 6G-based VANETs and their potential for future advancements.
基金the Research Program through the National Research Foundation of Korea(NRF-2019R1A2C1005920).
文摘Future networks communication scenarios by the 2030s will include notable applications are three-dimensional(3D)calls,haptics communications,unmanned mobility,tele-operated driving,bio-internet of things,and the Nanointernet of things.Unlike the current scenario in which megahertz bandwidth are sufficient to drive the audio and video components of user applications,the future networks of the 2030s will require bandwidths in several gigahertzes(GHz)(from tens of gigahertz to 1 terahertz[THz])to perform optimally.Based on the current radio frequency allocation chart,it is not possible to obtain such a wide contiguous radio spectrum below 90 GHz(0.09 THz).Interestingly,these contiguous blocks of radio spectrum are readily available in the higher electromagnetic spectrum,specifically in the Terahertz(THz)frequency band.The major contribution of this study is discussing the substantial issues and key features of THz waves,which include(i)key features and significance of THz frequency;(ii)recent regulatory;(iii)the most promising applications;and(iv)possible open research issues.These research topics were deeply investigated with the aim of providing a specific,synopsis,and encompassing conclusion.Thus,this article will be as a catalyst towards exploring new frontiers for future networks of the 2030s.
基金This research was supported by the National Research Foundation(NRF),Korea(2019R1C1C1007277)funded by the Ministry of Science and ICT(MSIT),Korea.
文摘Since around 1980,a new generation of wireless technology has arisen approximately every 10 years.First-generation(1G)and secondgeneration(2G)began with voice and eventually introduced more and more data in third-generation(3G)and became highly popular in the fourthgeneration(4G).To increase the data rate along with low latency and mass connectivity the fifth-generation(5G)networks are being installed from 2020.However,the 5G technology will not be able to fulfill the data demand at the end of this decade.Therefore,it is expected that 6G communication networks will rise,providing better services through the implementation of new enabling technologies and allowing users to connect everywhere.6G technology would not be confined to cellular communications networks,but would also comply with non-terrestrial communication system requirements,such as satellite communication.The ultimate objectives of this work are to address the major challenges of the evolution of cellular communication networks and to discourse the recent growth of the industry based on the key scopes of application and challenges.The main areas of research topics are summarized into(i)major 6G wireless networkmilestones;(ii)key performance indicators;(iii)future new applications;and(iv)potential fields of research,challenges,and open issues.
基金funded by Taif University,Taif,Saudi Arabia,Project No.(TUDSPP-2024-139).
文摘The mobility and connective capabilities of unmanned aerial vehicles(UAVs)are becoming more and more important in defense,commercial,and research domains.However,their open communication makes UAVs susceptible toundesirablepassive attacks suchas eavesdroppingor jamming.Recently,the inefficiencyof traditional cryptography-based techniques has led to the addition of Physical Layer Security(PLS).This study focuses on the advanced PLS method for passive eavesdropping in UAV-aided vehicular environments,proposing a solution to complement the conventional cryptography approach.Initially,we present a performance analysis of first-order secrecy metrics in 6G-enabled UAV systems,namely hybrid outage probability(HOP)and secrecy outage probability(SOP)over 2×2 Nakagami-m channels.Later,we propose a novel technique for mitigating passive eavesdropping,which considers first-order secrecy metrics as an optimization problem and determines their lower and upper bounds.Finally,we conduct an analysis of bounded HOP and SOP using the interactive Nakagami-m channel,considering the multiple-input-multiple-output configuration of the UAV system.The findings indicate that 2×2 Nakagami-mis a suitable fadingmodel under constant velocity for trustworthy receivers and eavesdroppers.The results indicate that UAV mobility has some influence on an eavesdropper’s intrusion during line-of-sight-enabled communication and can play an important role in improving security against passive eavesdroppers.
文摘In this paper,ambient IoT is used as a typical use case of massive connections for the sixth generation(6G)mobile communications where we derive the performance requirements to facilitate the evaluation of technical solutions.A rather complete design of unsourced multiple access is proposed in which two key parts:a compressed sensing module for active user detection,and a sparse interleaver-division multiple access(SIDMA)module are simulated side by side on a same platform at balanced signal to noise ratio(SNR)operating points.With a proper combination of compressed sensing matrix,a convolutional encoder,receiver algorithms,the simulated performance results appear superior to the state-of-the-art benchmark,yet with relatively less complicated processing.
基金supported by the National Key Research and Development Program of China(2020YFB1806800)funded by Beijing University of Posts and Telecommuns(BUPT)China Mobile Research Institute Joint Innoviation Center。
文摘In 5G networks,optimization of antenna beam weights of base stations has become the key application of AI for network optimization.For 6G,higher frequency bands and much denser cells are expected,and the importance of automatic and accurate beamforming assisted by AI will become more prominent.In existing network,servers are“patched”to network equipment to act as a centralized brain for model training and inference leading to high transmission overhead,large inference latency and potential risks of data security.Decentralized architectures have been proposed to achieve flexible parameter configuration and fast local response,but it is inefficient in collecting and sharing global information among base stations.In this paper,we propose a novel solution based on a collaborative cloud edge architecture for multi-cell joint beamforming optimization.We analyze the performance and costs of the proposed solution with two other architectural solutions by simulation.Compared with the centralized solution,our solution improves prediction accuracy by 24.66%,and reduces storage cost by 83.82%.Compared with the decentralized solution,our solution improves prediction accuracy by 68.26%,and improves coverage performance by 0.4 dB.At last,the future research work is prospected.
基金supported in part by the Science and Technology Project of Hebei Education Department(No.ZD2021088)in part by the S&T Major Project of the Science and Technology Ministry of China(No.2017YFE0135700)。
文摘Spatio-temporal cellular network traffic prediction at wide-area level plays an important role in resource reconfiguration,traffic scheduling and intrusion detection,thus potentially supporting connected intelligence of the sixth generation of mobile communications technology(6G).However,the existing studies just focus on the spatio-temporal modeling of traffic data of single network service,such as short message,call,or Internet.It is not conducive to accurate prediction of traffic data,characterised by diverse network service,spatio-temporality and supersize volume.To address this issue,a novel multi-task deep learning framework is developed for citywide cellular network traffic prediction.Functionally,this framework mainly consists of a dual modular feature sharing layer and a multi-task learning layer(DMFS-MT).The former aims at mining long-term spatio-temporal dependencies and local spatio-temporal fluctuation trends in data,respectively,via a new combination of convolutional gated recurrent unit(ConvGRU)and 3-dimensional convolutional neural network(3D-CNN).For the latter,each task is performed for predicting service-specific traffic data based on a fully connected network.On the real-world Telecom Italia dataset,simulation results demonstrate the effectiveness of our proposal through prediction performance measure,spatial pattern comparison and statistical distribution verification.
基金supported by National Key Research and Development Project 2018YFE0205503Beijing University of Posts and Telecommunications-China Mobile Research Institute Joint Innovation Center。
文摘Sixth Generation(6G)wireless communication network has been expected to provide global coverage,enhanced spectral efficiency,and AI(Artificial Intelligence)-native intelligence,etc.To meet these requirements,the computational concept of Decision-Making of cognition intelligence,its implementation framework adapting to foreseen innovations on networks and services,and its empirical evaluations are key techniques to guarantee the generationagnostic intelligence evolution of wireless communication networks.In this paper,we propose an Intelligent Decision Making(IDM)framework,acting as the role of network brain,based on Reinforcement Learning modelling philosophy to empower autonomous intelligence evolution capability to 6G network.Besides,usage scenarios and simulation demonstrate the generality and efficiency of IDM.We hope that some of the ideas of IDM will assist the research of 6G network in a new or different light.
基金co-supported by the Key International Cooperation Research Project,China(No.61720106003)Jiangsu Province Science and Technology Project,China(No.BE2021031)+4 种基金the Shanghai Aerospace Science and Technology Innovation Foundation,China(No.SAST2019-095)NUPTSF(No.NY220111)the Research Project of Science and Technology on Complex Electronic System Simulation Laboratory,China(No.DXZT-JC-ZZ-2019-009)the National Natural Science Foundation of China(No.61801234)the Postgraduate Research and Practice Innovation Program of Jiangsu Province,China(No.KYCX210739)。
文摘The application of Non-Orthogonal Multiple Access(NOMA) technology into satelliteaerial-ground integrated networks can meet the requirements of ultra-high rate and massive connectivity for the Sixth-Generation(6G) communication systems. We consider an uplink NOMA scenario for such a satellite-aerial-ground integrated network where multiple users communicate with satellite under the help of an Unmanned Aerial Vehicle(UAV) as an aerial relay equipped with a phased array. Supposing that buffer-aided decode-and-forward protocol is adopted at the UAV relay, we first formulate an optimization problem to maximize Ergodic Sum Rate(ESR) of the considered system subject to individual power constraint and quality-of-service constraint of each user.Then, with known imperfect channel state information of each user, we propose a joint power allocation and robust Beam Forming(BF) iterative algorithm to maximize ESR for the user-to-UAV link. Besides, to take the advantages of Free-Space Optical(FSO) and millimeter Wave(mmWave)communications, we present a switch-based hybrid FSO/mmWave scheme and a robust BF algorithm for the UAV-to-satellite link to achieve higher rate. Moreover, a closed-form ESR expression is derived. Finally, the effectiveness and correctness of the proposed solutions are verified by numerical simulations, and the performance evaluation results show that the proposed solutions not only achieve performance enhancement and robustness, but also outperform the orthogonal multiple access significantly.
基金This project was financially supported by the Academy of Scientific Research and Technology(ASRT)in Egypt,under the project of Science Up,Grant no.6626.
文摘Quantum key agreement is a promising key establishing protocol that can play a significant role in securing 5G/6G communication networks.Recently,Liu et al.(Quantum Information Processing 18(8):1-10,2019)proposed a multi-party quantum key agreement protocol based on four-qubit cluster states was proposed.The aim of their protocol is to agree on a shared secret key among multiple remote participants.Liu et al.employed four-qubit cluster states to be the quantum resources and the X operation to securely share a secret key.In addition,Liu et al.’s protocol guarantees that each participant makes an equal contribution to the final key.The authors also claimed that the proposed protocol is secure against participant attack and dishonest participants cannot generate the final shared key alone.However,we show here that Liu et al.protocol is insecure against a collusive attack,where dishonest participants can retrieve the private inputs of a trustworthy participant without being caught.Additionally,the corresponding modifications are presented to address these security flaws in Liu et al.’s protocol.
基金Project supported by CHIST-ERA(SUNRISE CHIST-ERA-20-SICT-005)the Engineering and Physical Sciences Research Council(No.EP/W035588/1)the PHC Alliance Franco-British Joint Research Programme(No.822326028)。
文摘Simultaneously transmitting and reflecting reconfigurable intelligent surfaces(STAR-RISs)have been attracting significant attention in both academia and industry for their advantages of achieving 360°coverage and enhanced degrees-of-freedom.This article first identifies the fundamentals of STAR-RIS,by discussing the hardware models,channel models,and signal models.Then,three representative categorizing approaches for STAR-RISs are introduced from the phase-shift,directional,and energy consumption perspectives.Furthermore,the beamforming design of STAR-RISs is investigated for both independent and coupled phase-shift cases.As a recent advance,a general optimization framework,which has high compatibility and provable optimality regardless of the application scenarios,is proposed.As a further advance,several promising applications are discussed to demonstrate the potential benefits of applying STAR-RISs in sixth-generation wireless communication.Lastly,a few future directions and research opportunities are highlighted.
基金Project supported by the National Natural Science Foundation of China(No.62071037)。
文摘Near-field communication using large-scale antenna arrays is one of the hot research topics in the sixth-generation(6G)wireless communication.Reconfigurable intelligent surface(RIS)is a cost-effective method for manipulating electromagnetic waves in the near field.We propose a 2-bit dual-polarized RIS that has the merits of low cost,low power consumption,high phase accuracy,and polarization diversity.Each element consists of an aperture-coupled microstrip patch,two single-pole-fourthrow(SP4T)switches,and two groups of microstrip delay lines.Two-bit phase shift is achieved by using only one SP4T switch that controls the connection of four parallel delay branches.Dual polarization is generated by placing two orthogonal slots with two 2-bit phase shifters.A 15×15 RIS prototype operating in the 3.6 GHz band is fabricated and measured.The beam can be scanned in the±60°range,with a peak aperture efficiency of 40.1%for horizontal polarization and 38.3%for vertical polarization.What is more,the total power consumption of the RIS is merely about 100 mW,which is very attractive for massive deployment in 6G near-field communication.
