In this paper, we present a non-transferable utility coalition graph game (NTU-CGG) based resource allocation scheme with relay selection for a downlink orthogonal frequency division multiplexing (OFDMA) based cog...In this paper, we present a non-transferable utility coalition graph game (NTU-CGG) based resource allocation scheme with relay selection for a downlink orthogonal frequency division multiplexing (OFDMA) based cognitive radio networks to maximize both system throughput and system faimess. In this algorithm, with the assistance of others SUs, SUs with less available channels to improve their throughput and fairness by forming a directed tree graph according to spectrum availability and traffic demands of SUs. So this scheme can effectively exploit both space and frequency diversity of the system. Performance results show that, NTU-CGG significantly improves system faimess level while not reducing the throughput comparing with other existing algorithms.展开更多
This paper investigates the power control and routing problem in the communication process of an energy harvesting(EH)multi-hop cognitive radio network(CRN).The secondary user(SU)nodes(i.e.,source node and relay nodes...This paper investigates the power control and routing problem in the communication process of an energy harvesting(EH)multi-hop cognitive radio network(CRN).The secondary user(SU)nodes(i.e.,source node and relay nodes)harvest energy from the environment and use the energy exclusively for transmitting data.The SU nodes(i.e.,relay nodes)on the path,store and forward the received data to the destination node.We consider a real world scenario where the EH-SU node has only local causal knowledge,i.e.,at any time,each EH-SU node only has knowledge of its own EH process,channel state and currently received data.In order to study the power and routing issues,an optimization problem that maximizes path throughput considering quality of service(QoS)and available energy constraints is proposed.To solve this optimization problem,we propose a hybrid game theory routing and power control algorithm(HGRPC).The EH-SU nodes on the same path cooperate with each other,but EH-SU nodes on the different paths compete with each other.By selecting the best next hop node,we find the best strategy that can maximize throughput.In addition,we have established four steps to achieve routing,i.e.,route discovery,route selection,route reply,and route maintenance.Compared with the direct transmission,HGRPC has advantages in longer distances and higher hop counts.The algorithm generates more energy,reduces energy consumption and increases predictable residual energy.In particular,the time complexity of HGRPC is analyzed and its convergence is proved.In simulation experiments,the performance(i.e.,throughput and bit error rate(BER))of HGRPC is evaluated.Finally,experimental results show that HGRPC has higher throughput,longer network life,less latency,and lower energy consumption.展开更多
随着无线网络技术的发展,电视频谱资源日益稀缺。提出一种认知无线电网络(Cognitive Radio Network,CRN)中基于区块链的电视频谱资源分配方法。主用户(Primary Users,PUs)可以在满足自己通信质量要求的情况下对次用户(Secondary Users,S...随着无线网络技术的发展,电视频谱资源日益稀缺。提出一种认知无线电网络(Cognitive Radio Network,CRN)中基于区块链的电视频谱资源分配方法。主用户(Primary Users,PUs)可以在满足自己通信质量要求的情况下对次用户(Secondary Users,SUs)的干扰功率进行定价来控制SUs的传输,SUs根据自身利益,选择是否付出一定的代价接入PUs的频段,且资源分配方案通过智能合约记录在区块链上。将PUs与SUs之间的相互作用制定为一个斯塔克尔伯格(Stackelberg)博弈问题,利用所采用的算法求解均衡。仿真结果表明了所提方法的有效性。展开更多
From an end-to-end performance perspective,a multi-agent-based cognitive resource management(MA-CRM) framework is proposed in this article.More importantly,we introduce a novel concept of resource flow(RF) as integrat...From an end-to-end performance perspective,a multi-agent-based cognitive resource management(MA-CRM) framework is proposed in this article.More importantly,we introduce a novel concept of resource flow(RF) as integrated CRM in a multi-dimensional environment scenario.We concentrate on the autonomous CRM framework in cognitive radio(CR) networks.Specifically,we first summarize the necessity of the novel concept for implementing intelligent and autonomous resource management considering both the requirements of various types of resource and the unified framework of the CRM scheme.Then,we introduce the concept of RF,including the technical aspects,purpose,classification,and description.Finally,we give a use case of RF for autonomous CRM,where the optimal RF is achieved to guarantee the resource-imbalanced requests of different service traffic flows.展开更多
Non-orthogonal multiple access(NOMA)based fog radio access networks(F-RANs)offer high spectrum efficiency,ultra-low delay,and huge network throughput,and this is made possible by edge computing and communication funct...Non-orthogonal multiple access(NOMA)based fog radio access networks(F-RANs)offer high spectrum efficiency,ultra-low delay,and huge network throughput,and this is made possible by edge computing and communication functions of the fog access points(F-APs).Meanwhile,caching-enabled F-APs are responsible for edge caching and delivery of a large volume of multimedia files during the caching phase,which facilitates further reduction in the transmission energy and burden.The need of the prevailing situation in industry is that in NOMA-based F-RANs,energy-efficient resource allocation,which consists of cache placement(CP)and radio resource allocation(RRA),is crucial for network performance enhancement.To this end,in this paper,we first characterize an NOMA-based F-RAN in which F-APs of caching capabilities underlaid with the radio remote heads serve user equipments via the NOMA protocol.Then,we formulate a resource allocation problem for maximizing the defined performance indicator,namely network profit,which takes caching cost,revenue,and energy efficiency into consideration.The NP-hard problem is decomposed into two sub-problems,namely the CP sub-problem and RRA sub-problem.Finally,we propose an iterative method and a Stackelberg game based method to solve them,and numerical results show that the proposed solution can significantly improve network profit compared to some existing schemes in NOMA-based F-RANs.展开更多
为有效利用频谱资源,提高频谱效率,文中利用环境感知技术,设计出认知无线电跨层结构框架,提出一种新的功率控制博弈BPCG(Bandwidth and Power Control Game Algorithm)算法,研究不同用户的频谱带宽分配和功率控制,该算法在确保频谱带宽...为有效利用频谱资源,提高频谱效率,文中利用环境感知技术,设计出认知无线电跨层结构框架,提出一种新的功率控制博弈BPCG(Bandwidth and Power Control Game Algorithm)算法,研究不同用户的频谱带宽分配和功率控制,该算法在确保频谱带宽有效分配前提下,通过对用户功率的有效控制,实现网络总吞吐量的提高。仿真结果表明该算法在相同的功率消耗前提下,网络吞吐量显著提高,并随频谱带宽的增加,实现网络吞吐量的最大化。展开更多
提出了一种在LTE-A(long term evolution advanced,长期演进技术增强)技术下的无线资源管理跨层模型,阐述了模型的基本功能特征。以博弈论为依据,分析了无线网络资源的分配方式,并根据无线网络资源和系统协议栈中各层之间的联系,通过设...提出了一种在LTE-A(long term evolution advanced,长期演进技术增强)技术下的无线资源管理跨层模型,阐述了模型的基本功能特征。以博弈论为依据,分析了无线网络资源的分配方式,并根据无线网络资源和系统协议栈中各层之间的联系,通过设计跨层结构,使各层博弈的目标统一。提出的理论模型面向多种无线网络资源,涉及多个无线网络协议栈层,实现了无线资源的综合管理以及各层之间的联合优化。展开更多
基金supported by the National Natural Science Funds of China for Young Scholar(61001115)the Beijing Natural Science Foundation of China(4102044)the National Natural Science Foundation of China(61271182)
文摘In this paper, we present a non-transferable utility coalition graph game (NTU-CGG) based resource allocation scheme with relay selection for a downlink orthogonal frequency division multiplexing (OFDMA) based cognitive radio networks to maximize both system throughput and system faimess. In this algorithm, with the assistance of others SUs, SUs with less available channels to improve their throughput and fairness by forming a directed tree graph according to spectrum availability and traffic demands of SUs. So this scheme can effectively exploit both space and frequency diversity of the system. Performance results show that, NTU-CGG significantly improves system faimess level while not reducing the throughput comparing with other existing algorithms.
基金This work was partially supported by the National Natural Science Foundation of China(No.61771410,No.61876089)by the Postgraduate Innovation Fund Project by Southwest University of Science and Technology(No.19ycx0106)+2 种基金by the Artificial Intelligence Key Laboratory of Sichuan Province(No.2017RYY05,No.2018RYJ03)by the Zigong City Key Science and Technology Plan Project(2019YYJC16)by and by the Horizontal Project(No.HX2017134,No.HX2018264,Nos.E10203788,HX2019250).
文摘This paper investigates the power control and routing problem in the communication process of an energy harvesting(EH)multi-hop cognitive radio network(CRN).The secondary user(SU)nodes(i.e.,source node and relay nodes)harvest energy from the environment and use the energy exclusively for transmitting data.The SU nodes(i.e.,relay nodes)on the path,store and forward the received data to the destination node.We consider a real world scenario where the EH-SU node has only local causal knowledge,i.e.,at any time,each EH-SU node only has knowledge of its own EH process,channel state and currently received data.In order to study the power and routing issues,an optimization problem that maximizes path throughput considering quality of service(QoS)and available energy constraints is proposed.To solve this optimization problem,we propose a hybrid game theory routing and power control algorithm(HGRPC).The EH-SU nodes on the same path cooperate with each other,but EH-SU nodes on the different paths compete with each other.By selecting the best next hop node,we find the best strategy that can maximize throughput.In addition,we have established four steps to achieve routing,i.e.,route discovery,route selection,route reply,and route maintenance.Compared with the direct transmission,HGRPC has advantages in longer distances and higher hop counts.The algorithm generates more energy,reduces energy consumption and increases predictable residual energy.In particular,the time complexity of HGRPC is analyzed and its convergence is proved.In simulation experiments,the performance(i.e.,throughput and bit error rate(BER))of HGRPC is evaluated.Finally,experimental results show that HGRPC has higher throughput,longer network life,less latency,and lower energy consumption.
文摘随着无线网络技术的发展,电视频谱资源日益稀缺。提出一种认知无线电网络(Cognitive Radio Network,CRN)中基于区块链的电视频谱资源分配方法。主用户(Primary Users,PUs)可以在满足自己通信质量要求的情况下对次用户(Secondary Users,SUs)的干扰功率进行定价来控制SUs的传输,SUs根据自身利益,选择是否付出一定的代价接入PUs的频段,且资源分配方案通过智能合约记录在区块链上。将PUs与SUs之间的相互作用制定为一个斯塔克尔伯格(Stackelberg)博弈问题,利用所采用的算法求解均衡。仿真结果表明了所提方法的有效性。
基金supported by the National Basic Research Program of China(2009CB320400)the Program for Changjiang Scholars and Innovative Research Teams in Universities,National High Technology Research and Development Program of China(2007AA01Z288)+2 种基金the National Natural Science Foundation of China(60572146,60902032,60902033 and 60972047)Natural Science Basic Research Plan in Shaanxi Province of China(2012JQ8012)the Program of Introducing Talents of Discipline to Universities(B08038)
文摘From an end-to-end performance perspective,a multi-agent-based cognitive resource management(MA-CRM) framework is proposed in this article.More importantly,we introduce a novel concept of resource flow(RF) as integrated CRM in a multi-dimensional environment scenario.We concentrate on the autonomous CRM framework in cognitive radio(CR) networks.Specifically,we first summarize the necessity of the novel concept for implementing intelligent and autonomous resource management considering both the requirements of various types of resource and the unified framework of the CRM scheme.Then,we introduce the concept of RF,including the technical aspects,purpose,classification,and description.Finally,we give a use case of RF for autonomous CRM,where the optimal RF is achieved to guarantee the resource-imbalanced requests of different service traffic flows.
基金the National Natural Science Foundation of China(Nos.U21A20444 and 61901044)Young Elite Scientist Sponsorship Program by China Institute of Communications。
文摘Non-orthogonal multiple access(NOMA)based fog radio access networks(F-RANs)offer high spectrum efficiency,ultra-low delay,and huge network throughput,and this is made possible by edge computing and communication functions of the fog access points(F-APs).Meanwhile,caching-enabled F-APs are responsible for edge caching and delivery of a large volume of multimedia files during the caching phase,which facilitates further reduction in the transmission energy and burden.The need of the prevailing situation in industry is that in NOMA-based F-RANs,energy-efficient resource allocation,which consists of cache placement(CP)and radio resource allocation(RRA),is crucial for network performance enhancement.To this end,in this paper,we first characterize an NOMA-based F-RAN in which F-APs of caching capabilities underlaid with the radio remote heads serve user equipments via the NOMA protocol.Then,we formulate a resource allocation problem for maximizing the defined performance indicator,namely network profit,which takes caching cost,revenue,and energy efficiency into consideration.The NP-hard problem is decomposed into two sub-problems,namely the CP sub-problem and RRA sub-problem.Finally,we propose an iterative method and a Stackelberg game based method to solve them,and numerical results show that the proposed solution can significantly improve network profit compared to some existing schemes in NOMA-based F-RANs.
文摘为有效利用频谱资源,提高频谱效率,文中利用环境感知技术,设计出认知无线电跨层结构框架,提出一种新的功率控制博弈BPCG(Bandwidth and Power Control Game Algorithm)算法,研究不同用户的频谱带宽分配和功率控制,该算法在确保频谱带宽有效分配前提下,通过对用户功率的有效控制,实现网络总吞吐量的提高。仿真结果表明该算法在相同的功率消耗前提下,网络吞吐量显著提高,并随频谱带宽的增加,实现网络吞吐量的最大化。
文摘提出了一种在LTE-A(long term evolution advanced,长期演进技术增强)技术下的无线资源管理跨层模型,阐述了模型的基本功能特征。以博弈论为依据,分析了无线网络资源的分配方式,并根据无线网络资源和系统协议栈中各层之间的联系,通过设计跨层结构,使各层博弈的目标统一。提出的理论模型面向多种无线网络资源,涉及多个无线网络协议栈层,实现了无线资源的综合管理以及各层之间的联合优化。