Recently,the increasing demand of radio spectrum for the next generation communication systems due to the explosive growth of applications appetite for bandwidths has led to the problem of spectrum scarcity.The potent...Recently,the increasing demand of radio spectrum for the next generation communication systems due to the explosive growth of applications appetite for bandwidths has led to the problem of spectrum scarcity.The potential approaches among the proposed solutions to resolve this issue are well explored cognitive radio(CR)technology and recently introduced non-orthogonal multiple access(NOMA)techniques.Both the techniques are employed for efficient spectrum utilization and assure the significant improvement in the spectral efficiency.Further,the significant improvement in spectral efficiency can be achieved by combining both the techniques.Since the CR is well-explored technique as compared to that of the NOMA in the field of communication,therefore it is worth and wise to implement this technique over the CR.In this article,we have presented the frameworks of NOMA implementation over CR as well as the feasibility of proposed frameworks.Further,the differences between proposed CR-NOMA and conventional CR frameworks are discussed.Finally,the potential issues regarding the implementation of CR-NOMA are explored.展开更多
To solve the contradiction between limited spectrum resources and increasing communication demand,this paper proposes a wireless resource allocation scheme based on the Deep Q Network(DQN)to allocate radio resources i...To solve the contradiction between limited spectrum resources and increasing communication demand,this paper proposes a wireless resource allocation scheme based on the Deep Q Network(DQN)to allocate radio resources in a downlink multi-user cognitive radio(CR)network with slicing.Secondary users(SUs)are multiplexed using non-orthogonal multiple access(NOMA).The SUs use the hybrid spectrum access mode to improve the spectral efficiency(SE).Considering the demand for multiple services,the enhanced mobile broadband(eMBB)slice and ultrareliable low-latency communication(URLLC)slice were established.The proposed scheme can maximize the SE while ensuring Quality of Service(QoS)for the users.This study established a mapping relationship between resource allocation and the DQN algorithm in the CR-NOMA network.According to the signal-to-interference-plusnoise ratio(SINR)of the primary users(PUs),the proposed scheme can output the optimal channel selection and power allocation.The simulation results reveal that the proposed scheme can converge faster and obtain higher rewards compared with the Q-Learning scheme.Additionally,the proposed scheme has better SE than both the overlay and underlay only modes.展开更多
In this paper,we propose the Two-way Deep Reinforcement Learning(DRL)-Based resource allocation algorithm,which solves the problem of resource allocation in the cognitive downlink network based on the underlay mode.Se...In this paper,we propose the Two-way Deep Reinforcement Learning(DRL)-Based resource allocation algorithm,which solves the problem of resource allocation in the cognitive downlink network based on the underlay mode.Secondary users(SUs)in the cognitive network are multiplexed by a new Power Domain Sparse Code Multiple Access(PD-SCMA)scheme,and the physical resources of the cognitive base station are virtualized into two types of slices:enhanced mobile broadband(eMBB)slice and ultrareliable low latency communication(URLLC)slice.We design the Double Deep Q Network(DDQN)network output the optimal codebook assignment scheme and simultaneously use the Deep Deterministic Policy Gradient(DDPG)network output the optimal power allocation scheme.The objective is to jointly optimize the spectral efficiency of the system and the Quality of Service(QoS)of SUs.Simulation results show that the proposed algorithm outperforms the CNDDQN algorithm and modified JEERA algorithm in terms of spectral efficiency and QoS satisfaction.Additionally,compared with the Power Domain Non-orthogonal Multiple Access(PD-NOMA)slices and the Sparse Code Multiple Access(SCMA)slices,the PD-SCMA slices can dramatically enhance spectral efficiency and increase the number of accessible users.展开更多
When coexisting with dual-link primary systems,secondary systems in cognitive radios should first distinguish between the primary downlinks and uplinks in order to efficiently explore their respective spectrum opportu...When coexisting with dual-link primary systems,secondary systems in cognitive radios should first distinguish between the primary downlinks and uplinks in order to efficiently explore their respective spectrum opportunities.Because of the assumptive prior knowledge about the time-frequency locations of primary downlinks and uplinks,this procedure is usually not considered in the design of cognitive radios.In this paper,a cooperative method is proposed for the downlink/uplink identification of time-division duplex-based orthogonal frequency-division multiple access systems.In this method,the power level of the primary link is extracted as the key feature,which also contributes to the subsequent cognitive behaviours.The effects of the primary and secondary systems and the effects of the detection parameters on the identification accuracy are all analysed in detail.The simulation results show that the proposed method can identify the primary links precisely and quickly with low complexity.展开更多
针对认知无线电-非正交多址接入系统开放性带来的通信安全问题,提出一种基于DC(difference of convex)规划的CR-NOMA系统物理层安全方案.在非正交多址(non-orthogonal multiple access,NOMA)通信场景下,构建多用户窃听信道模型,推导出CR...针对认知无线电-非正交多址接入系统开放性带来的通信安全问题,提出一种基于DC(difference of convex)规划的CR-NOMA系统物理层安全方案.在非正交多址(non-orthogonal multiple access,NOMA)通信场景下,构建多用户窃听信道模型,推导出CR-NOMA系统的安全和速率表达式;并设计基于DC的载波功率分配算法,求解子信道功率分配的最优解,提高系统子载波的安全性.仿真结果表明,在不增加基站功率情况下,其安全和速率较OFDMA和NOMA分别提升了35%和10%;在相同安全和速率下,用户数量最大可增加200%.验证了该方案能够有效提升系统物理层安全.展开更多
为了解决移动通信系统中的高延迟和覆盖盲点问题,提出了一种基于认知无线电-非正交多址接入(Cognitive Radio Non-orthogonal Multiple Access,CR-NOMA)的工业物联网网络。在认知网络中次用户采用解码转发(Decode and Forward,DF)和放...为了解决移动通信系统中的高延迟和覆盖盲点问题,提出了一种基于认知无线电-非正交多址接入(Cognitive Radio Non-orthogonal Multiple Access,CR-NOMA)的工业物联网网络。在认知网络中次用户采用解码转发(Decode and Forward,DF)和放大转发(Amplify and Forward,AF)两种辅助解码方式下,推导了主用户和次用户在完全串行干扰或不完全串行干扰两种终端状态下的中断性能。当用户间链路条件相同时,认知中继采用AF方式优于DF方式,且不完全串行干扰技术后系统残留干扰噪声的增大也会导致主用户和次用户的中断概率增大。研究还发现,各用户移动导致用户之间距离增大时,主用户和次用户的中断概率也会增大。展开更多
利用认知无线电非正交多址接入(cognitive radio non-orthogonal multiple access,CR-NOMA)技术可缓解频谱资源短缺问题,提升传感设备的吞吐量。传感设备的能效问题一直制约着传感设备的应用。为此,针对CR-NOMA中的传感设备,提出基于深...利用认知无线电非正交多址接入(cognitive radio non-orthogonal multiple access,CR-NOMA)技术可缓解频谱资源短缺问题,提升传感设备的吞吐量。传感设备的能效问题一直制约着传感设备的应用。为此,针对CR-NOMA中的传感设备,提出基于深度确定策略梯度的能效优化(deep deterministic policy gradientbased energy efficiency optimization,DPEE)算法。DPEE算法通过联合优化传感设备的传输功率和时隙分裂系数,提升传感设备的能效。将能效优化问题建模成马尔可夫决策过程,再利用深度确定策略梯度法求解。最后,通过仿真分析了电路功耗、时隙时长和主设备数对传感能效的影响。仿真结果表明,能效随传感设备电路功耗的增加而下降。此外,相比于基准算法,提出的DPEE算法提升了能效。展开更多
针对认知无线电(Cognitive Radio)频谱不连续,随机性和变化性大,以及TDMA,FDMA,CDMA不适用的问题,提出了一个基于变换域通信(Transform Domain Communication System)平台的认知无线电多址接入系统.该系统发射机通过将非空闲的频谱幅度...针对认知无线电(Cognitive Radio)频谱不连续,随机性和变化性大,以及TDMA,FDMA,CDMA不适用的问题,提出了一个基于变换域通信(Transform Domain Communication System)平台的认知无线电多址接入系统.该系统发射机通过将非空闲的频谱幅度置0,实现对授权用户的躲避;采用m状态序列产生的伪随机相位矢量,生成近似正交的调制基函数实现用户的多址接入;接收端通过本地基函数与接收信号相关估计出原始数据,并理论分析了系统的误码率.仿真表明,系统的检测概率,多址接入的用户数以及收发两端基函数的不一致会影响系统的性能.该系统能利用非连续频谱,并且基函数能够自适应变化,适合认知无线电。展开更多
在密集小区的认知无线电非正交多址(cognitive radio non-orthogonal multiple access,CRNOMA)网络场景下,针对用户采取Underlay方式复用时信道频带利用率低的问题,提出了一种基于能效的组合用户动态功率分配算法.该算法在保证主用户服...在密集小区的认知无线电非正交多址(cognitive radio non-orthogonal multiple access,CRNOMA)网络场景下,针对用户采取Underlay方式复用时信道频带利用率低的问题,提出了一种基于能效的组合用户动态功率分配算法.该算法在保证主用户服务质量前提下,基于用户之间的干扰和信干噪比,优化了组合多用户的接入方案,使信道接入用户数量最大且提高了频带利用率.同时,根据增益排序下的功率差额配比改进了剩余功率再分配方案,使空闲功率重新利用更加合理和有效.仿真结果表明,本文算法可以有效实现接入用户数量最大化的同时提高了频谱利用率.展开更多
文摘Recently,the increasing demand of radio spectrum for the next generation communication systems due to the explosive growth of applications appetite for bandwidths has led to the problem of spectrum scarcity.The potential approaches among the proposed solutions to resolve this issue are well explored cognitive radio(CR)technology and recently introduced non-orthogonal multiple access(NOMA)techniques.Both the techniques are employed for efficient spectrum utilization and assure the significant improvement in the spectral efficiency.Further,the significant improvement in spectral efficiency can be achieved by combining both the techniques.Since the CR is well-explored technique as compared to that of the NOMA in the field of communication,therefore it is worth and wise to implement this technique over the CR.In this article,we have presented the frameworks of NOMA implementation over CR as well as the feasibility of proposed frameworks.Further,the differences between proposed CR-NOMA and conventional CR frameworks are discussed.Finally,the potential issues regarding the implementation of CR-NOMA are explored.
基金the National Natural Science Foundation of China(Grant No.61971057).
文摘To solve the contradiction between limited spectrum resources and increasing communication demand,this paper proposes a wireless resource allocation scheme based on the Deep Q Network(DQN)to allocate radio resources in a downlink multi-user cognitive radio(CR)network with slicing.Secondary users(SUs)are multiplexed using non-orthogonal multiple access(NOMA).The SUs use the hybrid spectrum access mode to improve the spectral efficiency(SE).Considering the demand for multiple services,the enhanced mobile broadband(eMBB)slice and ultrareliable low-latency communication(URLLC)slice were established.The proposed scheme can maximize the SE while ensuring Quality of Service(QoS)for the users.This study established a mapping relationship between resource allocation and the DQN algorithm in the CR-NOMA network.According to the signal-to-interference-plusnoise ratio(SINR)of the primary users(PUs),the proposed scheme can output the optimal channel selection and power allocation.The simulation results reveal that the proposed scheme can converge faster and obtain higher rewards compared with the Q-Learning scheme.Additionally,the proposed scheme has better SE than both the overlay and underlay only modes.
基金supported by the National Natural Science Foundation of China(Grant No.61971057).
文摘In this paper,we propose the Two-way Deep Reinforcement Learning(DRL)-Based resource allocation algorithm,which solves the problem of resource allocation in the cognitive downlink network based on the underlay mode.Secondary users(SUs)in the cognitive network are multiplexed by a new Power Domain Sparse Code Multiple Access(PD-SCMA)scheme,and the physical resources of the cognitive base station are virtualized into two types of slices:enhanced mobile broadband(eMBB)slice and ultrareliable low latency communication(URLLC)slice.We design the Double Deep Q Network(DDQN)network output the optimal codebook assignment scheme and simultaneously use the Deep Deterministic Policy Gradient(DDPG)network output the optimal power allocation scheme.The objective is to jointly optimize the spectral efficiency of the system and the Quality of Service(QoS)of SUs.Simulation results show that the proposed algorithm outperforms the CNDDQN algorithm and modified JEERA algorithm in terms of spectral efficiency and QoS satisfaction.Additionally,compared with the Power Domain Non-orthogonal Multiple Access(PD-NOMA)slices and the Sparse Code Multiple Access(SCMA)slices,the PD-SCMA slices can dramatically enhance spectral efficiency and increase the number of accessible users.
基金supported by the National Natural Science Foundation of China under Grants No. 60832008,No. 60902001
文摘When coexisting with dual-link primary systems,secondary systems in cognitive radios should first distinguish between the primary downlinks and uplinks in order to efficiently explore their respective spectrum opportunities.Because of the assumptive prior knowledge about the time-frequency locations of primary downlinks and uplinks,this procedure is usually not considered in the design of cognitive radios.In this paper,a cooperative method is proposed for the downlink/uplink identification of time-division duplex-based orthogonal frequency-division multiple access systems.In this method,the power level of the primary link is extracted as the key feature,which also contributes to the subsequent cognitive behaviours.The effects of the primary and secondary systems and the effects of the detection parameters on the identification accuracy are all analysed in detail.The simulation results show that the proposed method can identify the primary links precisely and quickly with low complexity.
文摘针对认知无线电-非正交多址接入系统开放性带来的通信安全问题,提出一种基于DC(difference of convex)规划的CR-NOMA系统物理层安全方案.在非正交多址(non-orthogonal multiple access,NOMA)通信场景下,构建多用户窃听信道模型,推导出CR-NOMA系统的安全和速率表达式;并设计基于DC的载波功率分配算法,求解子信道功率分配的最优解,提高系统子载波的安全性.仿真结果表明,在不增加基站功率情况下,其安全和速率较OFDMA和NOMA分别提升了35%和10%;在相同安全和速率下,用户数量最大可增加200%.验证了该方案能够有效提升系统物理层安全.
文摘为了解决移动通信系统中的高延迟和覆盖盲点问题,提出了一种基于认知无线电-非正交多址接入(Cognitive Radio Non-orthogonal Multiple Access,CR-NOMA)的工业物联网网络。在认知网络中次用户采用解码转发(Decode and Forward,DF)和放大转发(Amplify and Forward,AF)两种辅助解码方式下,推导了主用户和次用户在完全串行干扰或不完全串行干扰两种终端状态下的中断性能。当用户间链路条件相同时,认知中继采用AF方式优于DF方式,且不完全串行干扰技术后系统残留干扰噪声的增大也会导致主用户和次用户的中断概率增大。研究还发现,各用户移动导致用户之间距离增大时,主用户和次用户的中断概率也会增大。
文摘针对认知无线电(Cognitive Radio)频谱不连续,随机性和变化性大,以及TDMA,FDMA,CDMA不适用的问题,提出了一个基于变换域通信(Transform Domain Communication System)平台的认知无线电多址接入系统.该系统发射机通过将非空闲的频谱幅度置0,实现对授权用户的躲避;采用m状态序列产生的伪随机相位矢量,生成近似正交的调制基函数实现用户的多址接入;接收端通过本地基函数与接收信号相关估计出原始数据,并理论分析了系统的误码率.仿真表明,系统的检测概率,多址接入的用户数以及收发两端基函数的不一致会影响系统的性能.该系统能利用非连续频谱,并且基函数能够自适应变化,适合认知无线电。
文摘在密集小区的认知无线电非正交多址(cognitive radio non-orthogonal multiple access,CRNOMA)网络场景下,针对用户采取Underlay方式复用时信道频带利用率低的问题,提出了一种基于能效的组合用户动态功率分配算法.该算法在保证主用户服务质量前提下,基于用户之间的干扰和信干噪比,优化了组合多用户的接入方案,使信道接入用户数量最大且提高了频带利用率.同时,根据增益排序下的功率差额配比改进了剩余功率再分配方案,使空闲功率重新利用更加合理和有效.仿真结果表明,本文算法可以有效实现接入用户数量最大化的同时提高了频谱利用率.
