The rapid advancement of 6G communication technologies and generative artificial intelligence(AI)is catalyzing a new wave of innovation at the intersection of networking and intelligent computing.On the one hand,6G en...The rapid advancement of 6G communication technologies and generative artificial intelligence(AI)is catalyzing a new wave of innovation at the intersection of networking and intelligent computing.On the one hand,6G envisions a hyper-connected environment that supports ubiquitous intelligence through ultra-low latency,high throughput,massive device connectivity,and integrated sensing and communication.On the other hand,generative AI,powered by large foundation models,has emerged as a powerful paradigm capable of creating.展开更多
Satellite Internet(SI)provides broadband access as a critical information infrastructure in 6G.However,with the integration of the terrestrial Internet,the influx of massive terrestrial traffic will bring significant ...Satellite Internet(SI)provides broadband access as a critical information infrastructure in 6G.However,with the integration of the terrestrial Internet,the influx of massive terrestrial traffic will bring significant threats to SI,among which DDoS attack will intensify the erosion of limited bandwidth resources.Therefore,this paper proposes a DDoS attack tracking scheme using a multi-round iterative Viterbi algorithm to achieve high-accuracy attack path reconstruction and fast internal source locking,protecting SI from the source.Firstly,to reduce communication overhead,the logarithmic representation of the traffic volume is added to the digests after modeling SI,generating the lightweight deviation degree to construct the observation probability matrix for the Viterbi algorithm.Secondly,the path node matrix is expanded to multi-index matrices in the Viterbi algorithm to store index information for all probability values,deriving the path with non-repeatability and maximum probability.Finally,multiple rounds of iterative Viterbi tracking are performed locally to track DDoS attack based on trimming tracking results.Simulation and experimental results show that the scheme can achieve 96.8%tracking accuracy of external and internal DDoS attack at 2.5 seconds,with the communication overhead at 268KB/s,effectively protecting the limited bandwidth resources of SI.展开更多
The adoption of 5G for Railways(5G-R)is expanding,particularly in high-speed trains,due to the benefits offered by 5G technology.High-speed trains must provide seamless connectivity and Quality of Service(QoS)to ensur...The adoption of 5G for Railways(5G-R)is expanding,particularly in high-speed trains,due to the benefits offered by 5G technology.High-speed trains must provide seamless connectivity and Quality of Service(QoS)to ensure passengers have a satisfactory experience throughout their journey.Installing base stations along urban environments can improve coverage but can dramatically reduce the experience of users due to interference.In particular,when a user with a mobile phone is a passenger in a high speed train traversing between urban centres,the coverage and the 5G resources in general need to be adequate not to diminish her experience of the service.The utilization of macro,pico,and femto cells may optimize the utilization of 5G resources.In this paper,a Genetic Algorithm(GA)-based approach to address the challenges of 5G network planning for 5G-R services is presented.The network is divided into three cell types,macro,pico,and femto cells—and the optimization process is designed to achieve a balance between key objectives:providing comprehensive coverage,minimizing interference,and maximizing energy efficiency.The study focuses on environments with high user density,such as high-speed trains,where reliable and high-quality connectivity is critical.Through simulations,the effectiveness of the GA-driven framework in optimizing coverage and performance in such scenarios is demonstrated.The algorithm is compared with the Particle Swarm Optimisation(PSO)and the Simulated Annealing(SA)methods and interesting insights emerged.The GA offers a strong balance between coverage and efficiency,achieving significantly higher coverage than PSO while maintaining competitive energy efficiency and interference levels.Its steady fitness improvement and adaptability make it well-suited for scenarios where wide coverage is a priority alongside acceptable performance trade-offs.展开更多
Long Term Evolution (LTE) is designed to revolutionize mobile broadband technology with key considerations of higher data rate, improved power efficiency, low latency and better quality of service. This work analyzes ...Long Term Evolution (LTE) is designed to revolutionize mobile broadband technology with key considerations of higher data rate, improved power efficiency, low latency and better quality of service. This work analyzes the impact of resource scheduling algorithms on the performance of LTE (4G) and WCDMA (3G) networks. In this paper, a full illustration of LTE system is given together with different scheduling algorithms. Thereafter, 3G WCDMA and 4G LTE networks were simulated using Simulink simulator embedded in MATLAB and performance evaluations were carried out. The performance metrics used for the evaluations are average system throughput, packet delay, latency and allocation of fairness using Round Robin, Best CQI and Proportional fair Packet Scheduling Algorithms. The results of the evaluations on both networks were analysed. The results showed that 4G LTE network performs better than 3G WCDMA network in all the three scheduling algorithms used.展开更多
The principles of G.729 algorithm are analyzed. It proposes an optimal approach of adaptive codebook search. Realized on fixed point DSP TMS320VC5410,the searching time of the optimal algorithm is thus significantly d...The principles of G.729 algorithm are analyzed. It proposes an optimal approach of adaptive codebook search. Realized on fixed point DSP TMS320VC5410,the searching time of the optimal algorithm is thus significantly decreased,and the result shows that the speech quality is not decreased.展开更多
The increasing demand for infotainment applications necessitates efficient bandwidth and energy resource allocation.Sixth-Generation(6G)networks,utilizing Cognitive Radio(CR)technology within CR Network(CRN),can enhan...The increasing demand for infotainment applications necessitates efficient bandwidth and energy resource allocation.Sixth-Generation(6G)networks,utilizing Cognitive Radio(CR)technology within CR Network(CRN),can enhance spectrum utilization by accessing unused spectrum when licensed Primary Mobile Equipment(PME)is inactive or served by a Primary Base Station(PrBS).Secondary Mobile Equipment(SME)accesses this spectrum through a Secondary Base Station(SrBS)using opportunistic access,i.e.,spectrum sensing.Hybrid Multiple Access(HMA),combining Orthogonal Multiple Access(OMA)and Non-Orthogonal Multiple Access(NOMA),can enhance Energy Efficiency(EE).Additionally,SME Clustering(SMEC)reduces inter-cluster interference,enhancing EE further.Despite these advancements,the integration of CR technology,HMA,and SMEC in CRN for better bandwidth utilization and EE remains unexplored.This paper introduces a new CRassisted SMEC-based Downlink HMA(CR-SMEC-DHMA)method for 6G CRN,aimed at jointly optimizing SME admission,SME association,sum rate,and EE subject to imperfect sensing,collision,and Quality of Service(QoS).A novel optimization problem,formulated as a non-linear fractional programming problem,is solved using the Charnes-Cooper Transformation(CCT)to convert into a concave optimization problem,and an𝜖-optimal Outer Approximation Algorithm(OAA)is employed to solve the concave optimization problem.Simulations demonstrate the effectiveness of the proposed CR-SMEC-DHMA,surpassing the performance of current OMAenabled CRN,NOMA-enabled CRN,SMEC-OMA enabled CRN,and SMEC-NOMA enabled CRN methods,with ε-optimal results obtained at ε=10^(−3),while satisfying Performance Measures(PMs)including SME admission in SMEC,SME association with SrBS,SME-channel opportunistic allocation through spectrum sensing,sum rate and overall EE within the 6G CRN.展开更多
The linear consecutive-k-out-of-n:failure(good)(Lin/Con/k/n:F(G))system consists of n interchangeable components that have different reliabilities.These components are arranged in a line path and different component a...The linear consecutive-k-out-of-n:failure(good)(Lin/Con/k/n:F(G))system consists of n interchangeable components that have different reliabilities.These components are arranged in a line path and different component assignments change the system reliability.The optimization of Lin/Con/k/n:F(G)system is to find an optimal component assignment to maximize the system reliability.As the number of components increases,the computation time for this problem increases considerably.In this paper,we propose a Birnbaum importance-based ant colony optimization(BIACO)algorithm to obtain quasi optimal assignments for such problems.We compare its performance using the Birnbaum importance based two-stage approach(BITA)and Birnbaum importancebased genetic local search(BIGLS)algorithm from previous researches.The experimental results show that the BIACO algorithm has a good performance in the optimization of Lin/Con/k/n:F(G)system.展开更多
This study presents a comparative analysis of optimisation strategies for designing hull shapes of Autonomous Underwater Vehicles(AUVs),paying special attention to drag,lift-to-drag ratio,and delivered power.A fully i...This study presents a comparative analysis of optimisation strategies for designing hull shapes of Autonomous Underwater Vehicles(AUVs),paying special attention to drag,lift-to-drag ratio,and delivered power.A fully integrated optimisation framework is developed accordingly,combining a single-objective Genetic Algorithm(GA)for design parameter generation,Computer-Aided Geometric Design(CAGD)for the creation of hull geometries and associated fluid domains,and a Reynolds-Averaged Navier-Stokes(RANS)solver for evaluating hydrodynamic performance metrics.This unified approach eliminates manual intervention,enabling automated determination of optimal hull configurations.Three distinct optimisation problems are addressed using the proposed methodology.First,the drag minimisation of a reference afterbody geometry(A1)at zero angle of attack is performed under constraints of fixed length and internal volume for various flow velocities spanning the range from 0.5 to 15 m/s.Second,the lift-to-drag ratio of A1 is maximised at a 6°angle of attack,maintaining constant total length and internal volume.Third,delivered power is minimised for A1 at a 0°angle of attack.The comparative analysis of results from all three optimisation cases reveals hull shapes with practical design significance.Notably,the shape optimised for minimum delivered power outperforms the other two across a range of velocities.Specifically,it achieves reductions in required power by 7.6%,7.8%,10.2%,and 13.04%at velocities of 0.5,1.0,1.5,and 2.152 m/s,respectively.展开更多
In the mobile radio industry, planning is a fundamental step for the deployment and commissioning of a Telecom network. The proposed models are based on the technology and the focussed architecture. In this context, w...In the mobile radio industry, planning is a fundamental step for the deployment and commissioning of a Telecom network. The proposed models are based on the technology and the focussed architecture. In this context, we introduce a comprehensive single-lens model for a fourth generation mobile network, Long Term Evolution Advanced Network (4G/LTE-A) technology which includes three sub assignments: cells in the core network. In the resolution, we propose an adaptation of the Genetic Evolutionary Algorithm for a global resolution. This is a combinatorial optimization problem that is considered as difficult. The use of this adaptive method does not necessarily lead to optimal solutions with the aim of reducing the convergence time towards a feasible solution.展开更多
文摘The rapid advancement of 6G communication technologies and generative artificial intelligence(AI)is catalyzing a new wave of innovation at the intersection of networking and intelligent computing.On the one hand,6G envisions a hyper-connected environment that supports ubiquitous intelligence through ultra-low latency,high throughput,massive device connectivity,and integrated sensing and communication.On the other hand,generative AI,powered by large foundation models,has emerged as a powerful paradigm capable of creating.
基金supported by the National Key R&D Program of China(Grant No.2022YFA1005000)the National Natural Science Foundation of China(Grant No.62025110 and 62101308).
文摘Satellite Internet(SI)provides broadband access as a critical information infrastructure in 6G.However,with the integration of the terrestrial Internet,the influx of massive terrestrial traffic will bring significant threats to SI,among which DDoS attack will intensify the erosion of limited bandwidth resources.Therefore,this paper proposes a DDoS attack tracking scheme using a multi-round iterative Viterbi algorithm to achieve high-accuracy attack path reconstruction and fast internal source locking,protecting SI from the source.Firstly,to reduce communication overhead,the logarithmic representation of the traffic volume is added to the digests after modeling SI,generating the lightweight deviation degree to construct the observation probability matrix for the Viterbi algorithm.Secondly,the path node matrix is expanded to multi-index matrices in the Viterbi algorithm to store index information for all probability values,deriving the path with non-repeatability and maximum probability.Finally,multiple rounds of iterative Viterbi tracking are performed locally to track DDoS attack based on trimming tracking results.Simulation and experimental results show that the scheme can achieve 96.8%tracking accuracy of external and internal DDoS attack at 2.5 seconds,with the communication overhead at 268KB/s,effectively protecting the limited bandwidth resources of SI.
文摘The adoption of 5G for Railways(5G-R)is expanding,particularly in high-speed trains,due to the benefits offered by 5G technology.High-speed trains must provide seamless connectivity and Quality of Service(QoS)to ensure passengers have a satisfactory experience throughout their journey.Installing base stations along urban environments can improve coverage but can dramatically reduce the experience of users due to interference.In particular,when a user with a mobile phone is a passenger in a high speed train traversing between urban centres,the coverage and the 5G resources in general need to be adequate not to diminish her experience of the service.The utilization of macro,pico,and femto cells may optimize the utilization of 5G resources.In this paper,a Genetic Algorithm(GA)-based approach to address the challenges of 5G network planning for 5G-R services is presented.The network is divided into three cell types,macro,pico,and femto cells—and the optimization process is designed to achieve a balance between key objectives:providing comprehensive coverage,minimizing interference,and maximizing energy efficiency.The study focuses on environments with high user density,such as high-speed trains,where reliable and high-quality connectivity is critical.Through simulations,the effectiveness of the GA-driven framework in optimizing coverage and performance in such scenarios is demonstrated.The algorithm is compared with the Particle Swarm Optimisation(PSO)and the Simulated Annealing(SA)methods and interesting insights emerged.The GA offers a strong balance between coverage and efficiency,achieving significantly higher coverage than PSO while maintaining competitive energy efficiency and interference levels.Its steady fitness improvement and adaptability make it well-suited for scenarios where wide coverage is a priority alongside acceptable performance trade-offs.
文摘Long Term Evolution (LTE) is designed to revolutionize mobile broadband technology with key considerations of higher data rate, improved power efficiency, low latency and better quality of service. This work analyzes the impact of resource scheduling algorithms on the performance of LTE (4G) and WCDMA (3G) networks. In this paper, a full illustration of LTE system is given together with different scheduling algorithms. Thereafter, 3G WCDMA and 4G LTE networks were simulated using Simulink simulator embedded in MATLAB and performance evaluations were carried out. The performance metrics used for the evaluations are average system throughput, packet delay, latency and allocation of fairness using Round Robin, Best CQI and Proportional fair Packet Scheduling Algorithms. The results of the evaluations on both networks were analysed. The results showed that 4G LTE network performs better than 3G WCDMA network in all the three scheduling algorithms used.
文摘The principles of G.729 algorithm are analyzed. It proposes an optimal approach of adaptive codebook search. Realized on fixed point DSP TMS320VC5410,the searching time of the optimal algorithm is thus significantly decreased,and the result shows that the speech quality is not decreased.
文摘The increasing demand for infotainment applications necessitates efficient bandwidth and energy resource allocation.Sixth-Generation(6G)networks,utilizing Cognitive Radio(CR)technology within CR Network(CRN),can enhance spectrum utilization by accessing unused spectrum when licensed Primary Mobile Equipment(PME)is inactive or served by a Primary Base Station(PrBS).Secondary Mobile Equipment(SME)accesses this spectrum through a Secondary Base Station(SrBS)using opportunistic access,i.e.,spectrum sensing.Hybrid Multiple Access(HMA),combining Orthogonal Multiple Access(OMA)and Non-Orthogonal Multiple Access(NOMA),can enhance Energy Efficiency(EE).Additionally,SME Clustering(SMEC)reduces inter-cluster interference,enhancing EE further.Despite these advancements,the integration of CR technology,HMA,and SMEC in CRN for better bandwidth utilization and EE remains unexplored.This paper introduces a new CRassisted SMEC-based Downlink HMA(CR-SMEC-DHMA)method for 6G CRN,aimed at jointly optimizing SME admission,SME association,sum rate,and EE subject to imperfect sensing,collision,and Quality of Service(QoS).A novel optimization problem,formulated as a non-linear fractional programming problem,is solved using the Charnes-Cooper Transformation(CCT)to convert into a concave optimization problem,and an𝜖-optimal Outer Approximation Algorithm(OAA)is employed to solve the concave optimization problem.Simulations demonstrate the effectiveness of the proposed CR-SMEC-DHMA,surpassing the performance of current OMAenabled CRN,NOMA-enabled CRN,SMEC-OMA enabled CRN,and SMEC-NOMA enabled CRN methods,with ε-optimal results obtained at ε=10^(−3),while satisfying Performance Measures(PMs)including SME admission in SMEC,SME association with SrBS,SME-channel opportunistic allocation through spectrum sensing,sum rate and overall EE within the 6G CRN.
基金the National Natural Science Foundation of China(Nos.71871181 and 71471147)the Overseas Expertise Introduction Project for Discipline Innovation(No.B13044)the Top International University Visiting Program for Outstanding Young Scholars of Northwestern Polytechnical University(No.201806295008)。
文摘The linear consecutive-k-out-of-n:failure(good)(Lin/Con/k/n:F(G))system consists of n interchangeable components that have different reliabilities.These components are arranged in a line path and different component assignments change the system reliability.The optimization of Lin/Con/k/n:F(G)system is to find an optimal component assignment to maximize the system reliability.As the number of components increases,the computation time for this problem increases considerably.In this paper,we propose a Birnbaum importance-based ant colony optimization(BIACO)algorithm to obtain quasi optimal assignments for such problems.We compare its performance using the Birnbaum importance based two-stage approach(BITA)and Birnbaum importancebased genetic local search(BIGLS)algorithm from previous researches.The experimental results show that the BIACO algorithm has a good performance in the optimization of Lin/Con/k/n:F(G)system.
文摘This study presents a comparative analysis of optimisation strategies for designing hull shapes of Autonomous Underwater Vehicles(AUVs),paying special attention to drag,lift-to-drag ratio,and delivered power.A fully integrated optimisation framework is developed accordingly,combining a single-objective Genetic Algorithm(GA)for design parameter generation,Computer-Aided Geometric Design(CAGD)for the creation of hull geometries and associated fluid domains,and a Reynolds-Averaged Navier-Stokes(RANS)solver for evaluating hydrodynamic performance metrics.This unified approach eliminates manual intervention,enabling automated determination of optimal hull configurations.Three distinct optimisation problems are addressed using the proposed methodology.First,the drag minimisation of a reference afterbody geometry(A1)at zero angle of attack is performed under constraints of fixed length and internal volume for various flow velocities spanning the range from 0.5 to 15 m/s.Second,the lift-to-drag ratio of A1 is maximised at a 6°angle of attack,maintaining constant total length and internal volume.Third,delivered power is minimised for A1 at a 0°angle of attack.The comparative analysis of results from all three optimisation cases reveals hull shapes with practical design significance.Notably,the shape optimised for minimum delivered power outperforms the other two across a range of velocities.Specifically,it achieves reductions in required power by 7.6%,7.8%,10.2%,and 13.04%at velocities of 0.5,1.0,1.5,and 2.152 m/s,respectively.
文摘In the mobile radio industry, planning is a fundamental step for the deployment and commissioning of a Telecom network. The proposed models are based on the technology and the focussed architecture. In this context, we introduce a comprehensive single-lens model for a fourth generation mobile network, Long Term Evolution Advanced Network (4G/LTE-A) technology which includes three sub assignments: cells in the core network. In the resolution, we propose an adaptation of the Genetic Evolutionary Algorithm for a global resolution. This is a combinatorial optimization problem that is considered as difficult. The use of this adaptive method does not necessarily lead to optimal solutions with the aim of reducing the convergence time towards a feasible solution.
