In this paper,we study a class of stochastic differential equations with additive noise that contains a non-stationary multifractional Brownian motion(mBm)with a Hurst parameter as a function of time and a Poisson poi...In this paper,we study a class of stochastic differential equations with additive noise that contains a non-stationary multifractional Brownian motion(mBm)with a Hurst parameter as a function of time and a Poisson point process of class(QL).The differential equation of this kind is motivated by the reserve processes in a general insurance model,in which between the claim payment and the past history of liability present the long term dependence.By using the variable order fractional calculus on the fractional Wiener-Poisson space and a multifractional derivative operator,and employing Girsanov theorem for multifractional Brownian motion,we prove the existence of weak solutions to the SDEs under consideration,As a consequence,we deduce the uniqueness in law and the pathwise uniqueness.展开更多
In the classical form,the Poisson Multi-Bernoulli Mixture(PMBM)filter uses a PMBM density to describe target birth,surviving,and death,which does not model the appearance of spawned targets.Although such a model can h...In the classical form,the Poisson Multi-Bernoulli Mixture(PMBM)filter uses a PMBM density to describe target birth,surviving,and death,which does not model the appearance of spawned targets.Although such a model can handle target birth,surviving,and death well,its performance may degrade when target spawning arises.The reason for this is that the original PMBM filter treats the spawned targets as birth targets,ignoring the surviving targets’information.In this paper,we propose a Kullback–Leibler Divergence(KLD)minimization based derivation for the PMBM prediction step,including target spawning,in which the spawned targets are modeled using a Poisson Point Process(PPP).Furthermore,to improve the computational efficiency,three approximations are used to implement the proposed algorithm,such as the Variational MultiBernoulli(VMB)filter,the Measurement-Oriented marginal MeMBer/Poisson(MOMB/P)filter,and the Track-Oriented marginal MeMBer/Poisson(TOMB/P)filter.Finally,simulation results demonstrate the validity of the proposed filter by using the spawning model in these three approximations.展开更多
Sensing coverage is a fundamental design issue in wireless sensor networks(WSNs),while sensor scheduling ensures coverage degree to the monitored event and extends the network lifetime.In this paper,we address k-cover...Sensing coverage is a fundamental design issue in wireless sensor networks(WSNs),while sensor scheduling ensures coverage degree to the monitored event and extends the network lifetime.In this paper,we address k-coverage scheduling problem in dense WSNs,we maintain a connected k-coverage energy efficiently through a novel Hard-Core based Coordinated Scheduling(HCCS),in which hardcore is a thinning process in stochastic geometry that inhibits more than one active sensor covering any area redundantly in a minimum distance. As compared with existing coordinated scheduling,HCCS allows coordination between sensors with little communication overhead.Moreover,due to the traditional sensing models in k-coverage analysis is unsuitable to describe the characteristic of transmit channel in dense WSNs,we propose a novel sensing model integrating Rayleigh Fading and Distribution of Active sensors(RFDA),and derive the coverage measure and k-coverage probability for the monitored event under RFDA. In addition,we analyze the influence factors,i.e. the transmit condition and monitoring degree to the k-coverage probability. Finally,through Monte Carlo simulations,it is shown that the k-coverage probability of HCCS outperforms that of its random scheduling counterpart.展开更多
Several software reliability growth models （SRGM） have been developed to monitor the reliability growth during the testing phase of software development. In most of the existing research available in the literatures...Several software reliability growth models （SRGM） have been developed to monitor the reliability growth during the testing phase of software development. In most of the existing research available in the literatures, it is considered that a similar testing effort is required on each debugging effort. However, in practice, different types of faults may require different amounts of testing efforts for their detection and removal. Consequently, faults are classified into three categories on the basis of severity： simple, hard and complex. This categorization may be extended to r type of faults on the basis of severity. Although some existing research in the literatures has incorporated this concept that fault removal rate （FRR） is different for different types of faults, they assume that the FRR remains constant during the overall testing period. On the contrary, it has been observed that as testing progresses, FRR changes due to changing testing strategy, skill, environment and personnel resources. In this paper, a general discrete SRGM is proposed for errors of different severity in software systems using the change-point concept. Then, the models are formulated for two particular environments. The models were validated on two real-life data sets. The results show better fit and wider applicability of the proposed models as to different types of failure datasets.展开更多
The increase in user mobility and density in modern cellular networks increases the risk of overloading certain base stations in popular locations such as shopping malls or stadiums,which can result in connection loss...The increase in user mobility and density in modern cellular networks increases the risk of overloading certain base stations in popular locations such as shopping malls or stadiums,which can result in connection loss for some users.To combat this,the traffic load of base stations should be kept as balanced as possible.In this paper,we propose an efficient load balancing-aware handover algorithm for highly dynamic beyond 5G heterogeneous networks by assigning mobile users to base stations with lighter loads when a handover is performed.The proposed algorithm is evaluated in a scenario with users having different levels of mobility,such as pedestrians and vehicles,and is shown to outperform the conventional handover mechanism,as well as another algorithm from the literature.As a secondary benefit,the overall energy consumption in the network is shown to be reduced with the proposed algorithm.展开更多
无线信道建模对于理解、设计和优化无线通信系统具有重要意义,是无线通信领域中不可或缺的一部分。为了满足车联网(vehicle to everything,V2X)环境中的通信需求,研究空间中障碍物的分布对信道衰落特性的影响,本文提出了一种新的随机散...无线信道建模对于理解、设计和优化无线通信系统具有重要意义,是无线通信领域中不可或缺的一部分。为了满足车联网(vehicle to everything,V2X)环境中的通信需求,研究空间中障碍物的分布对信道衰落特性的影响,本文提出了一种新的随机散射簇生成算法,即通过把Matérn硬核点过程和泊松簇过程相结合来模拟真实V2X信道中的障碍物。在算法中,依据真实环境障碍物的方位设置散射簇的坐标位置,根据周围障碍物密度合理设置簇内散射点数量。利用传播图论进行仿真,考虑直射路径和单跳散射路径,基于信道冲激响应(channel impulse response,CIR)分别研究了功率延迟分布(power delay profile,PDP)和多普勒功率谱密度(Doppler power spectrum density,DPSD),并分析了不同移动轨迹下的均方根(root mean square,RMS)时延扩展的累计分布函数(cumulative distribution function,CDF),以及莱斯K因子的分布特性和角度功率谱(power angular spectrum,PAS)的分布。本文研究验证得到,所提出的模型有助于分析车辆-基础设施(vehicle to infrastructure,V2I)通信场景下的时域非平稳特性,为V2X通信系统的设计和优化提供了重要参考。展开更多
文摘In this paper,we study a class of stochastic differential equations with additive noise that contains a non-stationary multifractional Brownian motion(mBm)with a Hurst parameter as a function of time and a Poisson point process of class(QL).The differential equation of this kind is motivated by the reserve processes in a general insurance model,in which between the claim payment and the past history of liability present the long term dependence.By using the variable order fractional calculus on the fractional Wiener-Poisson space and a multifractional derivative operator,and employing Girsanov theorem for multifractional Brownian motion,we prove the existence of weak solutions to the SDEs under consideration,As a consequence,we deduce the uniqueness in law and the pathwise uniqueness.
基金supported by the National Natural Science Foundation of China(No.61871301)。
文摘In the classical form,the Poisson Multi-Bernoulli Mixture(PMBM)filter uses a PMBM density to describe target birth,surviving,and death,which does not model the appearance of spawned targets.Although such a model can handle target birth,surviving,and death well,its performance may degrade when target spawning arises.The reason for this is that the original PMBM filter treats the spawned targets as birth targets,ignoring the surviving targets’information.In this paper,we propose a Kullback–Leibler Divergence(KLD)minimization based derivation for the PMBM prediction step,including target spawning,in which the spawned targets are modeled using a Poisson Point Process(PPP).Furthermore,to improve the computational efficiency,three approximations are used to implement the proposed algorithm,such as the Variational MultiBernoulli(VMB)filter,the Measurement-Oriented marginal MeMBer/Poisson(MOMB/P)filter,and the Track-Oriented marginal MeMBer/Poisson(TOMB/P)filter.Finally,simulation results demonstrate the validity of the proposed filter by using the spawning model in these three approximations.
基金supported by the National Science Foundation of China under Grant 61271186
文摘Sensing coverage is a fundamental design issue in wireless sensor networks(WSNs),while sensor scheduling ensures coverage degree to the monitored event and extends the network lifetime.In this paper,we address k-coverage scheduling problem in dense WSNs,we maintain a connected k-coverage energy efficiently through a novel Hard-Core based Coordinated Scheduling(HCCS),in which hardcore is a thinning process in stochastic geometry that inhibits more than one active sensor covering any area redundantly in a minimum distance. As compared with existing coordinated scheduling,HCCS allows coordination between sensors with little communication overhead.Moreover,due to the traditional sensing models in k-coverage analysis is unsuitable to describe the characteristic of transmit channel in dense WSNs,we propose a novel sensing model integrating Rayleigh Fading and Distribution of Active sensors(RFDA),and derive the coverage measure and k-coverage probability for the monitored event under RFDA. In addition,we analyze the influence factors,i.e. the transmit condition and monitoring degree to the k-coverage probability. Finally,through Monte Carlo simulations,it is shown that the k-coverage probability of HCCS outperforms that of its random scheduling counterpart.
文摘Several software reliability growth models （SRGM） have been developed to monitor the reliability growth during the testing phase of software development. In most of the existing research available in the literatures, it is considered that a similar testing effort is required on each debugging effort. However, in practice, different types of faults may require different amounts of testing efforts for their detection and removal. Consequently, faults are classified into three categories on the basis of severity： simple, hard and complex. This categorization may be extended to r type of faults on the basis of severity. Although some existing research in the literatures has incorporated this concept that fault removal rate （FRR） is different for different types of faults, they assume that the FRR remains constant during the overall testing period. On the contrary, it has been observed that as testing progresses, FRR changes due to changing testing strategy, skill, environment and personnel resources. In this paper, a general discrete SRGM is proposed for errors of different severity in software systems using the change-point concept. Then, the models are formulated for two particular environments. The models were validated on two real-life data sets. The results show better fit and wider applicability of the proposed models as to different types of failure datasets.
基金supported in part by the Istanbul Technical University Scientific Research Projects Coordination Unit under Grant FHD-2024-45764in part by TUBITAK 1515 Frontier R&D Laboratories Support Program for Turkcell 6GEN LAB under Grant 5229902Turkcell Technology R&D Center(Law no.5746)has partially supported this study。
文摘The increase in user mobility and density in modern cellular networks increases the risk of overloading certain base stations in popular locations such as shopping malls or stadiums,which can result in connection loss for some users.To combat this,the traffic load of base stations should be kept as balanced as possible.In this paper,we propose an efficient load balancing-aware handover algorithm for highly dynamic beyond 5G heterogeneous networks by assigning mobile users to base stations with lighter loads when a handover is performed.The proposed algorithm is evaluated in a scenario with users having different levels of mobility,such as pedestrians and vehicles,and is shown to outperform the conventional handover mechanism,as well as another algorithm from the literature.As a secondary benefit,the overall energy consumption in the network is shown to be reduced with the proposed algorithm.
文摘无线信道建模对于理解、设计和优化无线通信系统具有重要意义,是无线通信领域中不可或缺的一部分。为了满足车联网(vehicle to everything,V2X)环境中的通信需求,研究空间中障碍物的分布对信道衰落特性的影响,本文提出了一种新的随机散射簇生成算法,即通过把Matérn硬核点过程和泊松簇过程相结合来模拟真实V2X信道中的障碍物。在算法中,依据真实环境障碍物的方位设置散射簇的坐标位置,根据周围障碍物密度合理设置簇内散射点数量。利用传播图论进行仿真,考虑直射路径和单跳散射路径,基于信道冲激响应(channel impulse response,CIR)分别研究了功率延迟分布(power delay profile,PDP)和多普勒功率谱密度(Doppler power spectrum density,DPSD),并分析了不同移动轨迹下的均方根(root mean square,RMS)时延扩展的累计分布函数(cumulative distribution function,CDF),以及莱斯K因子的分布特性和角度功率谱(power angular spectrum,PAS)的分布。本文研究验证得到,所提出的模型有助于分析车辆-基础设施(vehicle to infrastructure,V2I)通信场景下的时域非平稳特性,为V2X通信系统的设计和优化提供了重要参考。
