The combination of orthogonal frequency division multiple access(OFDMA) with relaying techniques provides plentiful opportunities for high-performance and cost-effective networks.It requires intelligent radio resource...The combination of orthogonal frequency division multiple access(OFDMA) with relaying techniques provides plentiful opportunities for high-performance and cost-effective networks.It requires intelligent radio resource management schemes to harness these opportunities.This paper investigates the utility-based resource allocation problem in a real-time and non-real-time traffics mixed OFDMA cellular relay network to exploit the potentiality of relay.In order to apply utility theory to obtain an efficient tradeoff between throughput and fairness as well as satisfy the delay requirements of real-time traffics,a joint routing and scheduling scheme is proposed to resolve the resource allocation problem.Additionally,a low-complexity iterative algorithm is introduced to realize the scheme.The numerical results indicate that besides meeting the delay requirements of real-time traffic,the scheme can achieve the tradeoff between throughput and fairness effectively.展开更多
The development of communication technologies which support traffic-intensive applications presents new challenges in designing a real-time traffic analysis architecture and an accurate method that suitable for a wide...The development of communication technologies which support traffic-intensive applications presents new challenges in designing a real-time traffic analysis architecture and an accurate method that suitable for a wide variety of traffic types.Current traffic analysis methods are executed on the cloud,which needs to upload the traffic data.Fog computing is a more promising way to save bandwidth resources by offloading these tasks to the fog nodes.However,traffic analysis models based on traditional machine learning need to retrain all traffic data when updating the trained model,which are not suitable for fog computing due to the poor computing power.In this study,we design a novel fog computing based traffic analysis system using broad learning.For one thing,fog computing can provide a distributed architecture for saving the bandwidth resources.For another,we use the broad learning to incrementally train the traffic data,which is more suitable for fog computing because it can support incremental updates of models without retraining all data.We implement our system on the Raspberry Pi,and experimental results show that we have a 98%probability to accurately identify these traffic data.Moreover,our method has a faster training speed compared with Convolutional Neural Network(CNN).展开更多
In Cognitive Radio(CR) networks,CR user has to detect the spectrum channel periodically to make sure that the channel is idle during data transmission frame in order to avoid the collisions to the primary users.Hence ...In Cognitive Radio(CR) networks,CR user has to detect the spectrum channel periodically to make sure that the channel is idle during data transmission frame in order to avoid the collisions to the primary users.Hence recent research has been focused on the interference avoidance problem.Quality of Service(QoS) requirement of CR user will affect the time of data transmission in each frame.In this paper,in order to solve the interference avoidance and spectrum utilization problems without cooperation among CR users,a new scheme to obtain the optimal duration of data transmission frame is proposed to maximize the spectrum utilization and guarantee the protection to the primary users.The main advantages of our proposed scheme include the followings:(1) QoS requirement of CR user is concerned;(2) p-persistent Media Access Control(MAC) random access is used to avoid the collisions among CR users;(3) CR network system capacity is considered.We develop a Markov chain of the primary spectrum channel states and an exponential distribution of the CR user's traffic model to analyze the performance of our proposed scheme.Computer simulation shows that there is an optimal data transmission time to maximize the spectrum utilization.However,the regulatory constraint of the collision rate to the primary users has to be satisfied at the expense of spectrum utilization.And also the tradeoff between the spectrum utilization and the capacity of the CR system is taken into account.展开更多
基金Sponsored by the Self-Determined Research Funds of Huazhong Normal University from the Colleges’Basic Research and Operation of MOE
文摘The combination of orthogonal frequency division multiple access(OFDMA) with relaying techniques provides plentiful opportunities for high-performance and cost-effective networks.It requires intelligent radio resource management schemes to harness these opportunities.This paper investigates the utility-based resource allocation problem in a real-time and non-real-time traffics mixed OFDMA cellular relay network to exploit the potentiality of relay.In order to apply utility theory to obtain an efficient tradeoff between throughput and fairness as well as satisfy the delay requirements of real-time traffics,a joint routing and scheduling scheme is proposed to resolve the resource allocation problem.Additionally,a low-complexity iterative algorithm is introduced to realize the scheme.The numerical results indicate that besides meeting the delay requirements of real-time traffic,the scheme can achieve the tradeoff between throughput and fairness effectively.
基金supported by JSPS KAKENHI Grant Number JP16K00117, JP19K20250KDDI Foundationthe China Scholarship Council (201808050016)
文摘The development of communication technologies which support traffic-intensive applications presents new challenges in designing a real-time traffic analysis architecture and an accurate method that suitable for a wide variety of traffic types.Current traffic analysis methods are executed on the cloud,which needs to upload the traffic data.Fog computing is a more promising way to save bandwidth resources by offloading these tasks to the fog nodes.However,traffic analysis models based on traditional machine learning need to retrain all traffic data when updating the trained model,which are not suitable for fog computing due to the poor computing power.In this study,we design a novel fog computing based traffic analysis system using broad learning.For one thing,fog computing can provide a distributed architecture for saving the bandwidth resources.For another,we use the broad learning to incrementally train the traffic data,which is more suitable for fog computing because it can support incremental updates of models without retraining all data.We implement our system on the Raspberry Pi,and experimental results show that we have a 98%probability to accurately identify these traffic data.Moreover,our method has a faster training speed compared with Convolutional Neural Network(CNN).
基金Supported by the National Natural Science Foundation of China (No. 61171094,61001077,61071092)973 Program(2007 CB310607)National Science & Technology Key Project (2011ZX03001-006-02,2011ZX03005-004-03)
文摘In Cognitive Radio(CR) networks,CR user has to detect the spectrum channel periodically to make sure that the channel is idle during data transmission frame in order to avoid the collisions to the primary users.Hence recent research has been focused on the interference avoidance problem.Quality of Service(QoS) requirement of CR user will affect the time of data transmission in each frame.In this paper,in order to solve the interference avoidance and spectrum utilization problems without cooperation among CR users,a new scheme to obtain the optimal duration of data transmission frame is proposed to maximize the spectrum utilization and guarantee the protection to the primary users.The main advantages of our proposed scheme include the followings:(1) QoS requirement of CR user is concerned;(2) p-persistent Media Access Control(MAC) random access is used to avoid the collisions among CR users;(3) CR network system capacity is considered.We develop a Markov chain of the primary spectrum channel states and an exponential distribution of the CR user's traffic model to analyze the performance of our proposed scheme.Computer simulation shows that there is an optimal data transmission time to maximize the spectrum utilization.However,the regulatory constraint of the collision rate to the primary users has to be satisfied at the expense of spectrum utilization.And also the tradeoff between the spectrum utilization and the capacity of the CR system is taken into account.
