Frameworks of Non-Orthogonal Multiple Access Techniques in Cognitive Radio Communication Systems

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.

Intelligent reflecting surface-assisted cognitive radio-inspired rate-splitting multiple access systems

Intelligent reflecting surface(IRS)has been widely regarded as a promising technology for configuring wireless propagation environments.In this paper,we utilize IRS to assist transmission of a secondary user(SU)in a cognitive radio-inspired rate-splitting multiple access(CR-RSMA)system in which a primary user's(PU's)quality of service(QoS)requirements must be guaranteed.Without introducing intolerable interference to deteriorate the PU's outage performance,the SU conducts rate-splitting to transmit its signal to the base-station through the direct link and IRS reflecting channels.For the IRS-assisted CR-RSMA(IRS-CR-RSMA)scheme,we derive the optimal transmit power allocation,target rate allocation,and successive interference cancellation decoding order to enhance the outage performance of the SU.The closed-form expression for the SU's outage probability achieved by the IRS-CR-RSMA scheme is derived.Various simulation results are presented to clarify the enhanced outage performance achieved by the proposed IRS-CR-RSMA scheme over the CR-RSMA scheme.

Research on Physical Layer Security in Cognitive Wireless Networks with Multiple Eavesdroppers Based on Resource Allocation Algorithm

With the rapid development of the Internet of Things (IoT), non-Orthogonal Multiple Access (NOMA) technology and cognitive wireless network are two promising technologies to improve the spectral efficiency of the system, which have been widely concerned in the field of wireless communication. However, due to the importance of ownership and privacy protection, the IoT system must provide corresponding security mechanisms. From the perspective of improving the transmission security of CR-NOMA system based on cognitive wireless network, and considering the shortcomings of traditional relay cooperative NOMA system, this paper mainly analyzes the eavesdropping channel model of multi-user CR-NOMA system and derives the expressions of system security and rate to improve the security performance of CR-NOMA system. The basic idea of DC planning algorithm and the scheme of sub-carrier power allocation to improve the transmission security of the system were introduced. An algorithm for DC-CR-NOMA was proposed to maximize the SSR of the system and minimize the energy loss. The simulation results show that under the same complexity, the security and speed of the system can be greatly improved compared with the traditional scheme.

Resource Allocation for Cognitive Network Slicing in PD-SCMA System Based on Two-Way Deep Reinforcement Learning

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.

Downlink Resource Allocation for NOMA-Based Hybrid Spectrum Access in Cognitive Network

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.

Research on User Pairing Techniques Based on NOMA in Cognitive Radio Networks

This paper outlined a Non-Orthogonal Multiple Access (NOMA) grouping transmission scheme for cognitive radio networks. To address the problems of small channel gain difference of the middle part users caused by the traditional far-near pairing algorithm, and the low transmission rate of the traditional Orthogonal Multiple Access (OMA) transmission, a joint pairing algorithm was proposed, which provided multiple pairing schemes according to the actual scene. Firstly, the secondary users were sorted according to their channel gain, and then different secondary user groups were divided, and the far-near pairing combined with (Uniform Channel Gain Difference (UCGD) algorithm was used to group the secondary users. After completing the user pairing, the power allocation problem was solved. Finally, the simulation data results showed that the proposed algorithm can effectively improve the system transmission rate.

Analysis of cumulative handoff delay for graded secondary users in cognitive radio networks

According to the fact that the secondary users＇ delay requirements for data transmission are not unitary in cognitive radio networks, the secondary users are divided into two classes, denoted by SU1 and SU2, respectively. It is assumed that SU1 has a higher priority to occupy the primary users＇ unutilized channels than SU2. A preemptive resume priority M/G/1 queuing network is used to model the multiple spectrum handoffs processing. By using a state transition probability matrix and a cost matrix, the average cumulative delays of SU1 and SU2 are calculated, respectively. Numerical results show that the more the primary user＇s traffic load, the more rapidly the SU2＇s cumulative handoff delay grows. Compared with the networks where secondary users are unitary, the lower the SUI＇s arrival rate, the more obviously both SUI＇s and SU2＇s handoff delays decrease. The admission access regions limited by the maximum tolerable delay can also facilitate the design of admission control rules for graded secondary users.

Resource Allocation for Throughput Maximization in Cognitive Radio Network with NOMA

Spectrum resources are the precious and limited natural resources.In order to improve the utilization of spectrum resources and maximize the network throughput,this paper studies the resource allocation of the downlink cognitive radio network with non-orthogonalmultiple access(CRN-NOMA).NOMA,as the key technology of the fifth-generation communication(5G),can effectively increase the capacity of 5G networks.The optimization problem proposed in this paper aims to maximize the number of secondary users(SUs)accessing the system and the total throughput in the CRN-NOMA.Under the constraints of total power,minimum rate,interference and SINR,CRN-NOMA throughput is maximized by allocating optimal transmission power.First,for the situation of multiple sub-users,an adaptive optimization method is proposed to reduce the complexity of the optimization solution.Secondly,for the optimization problem of nonlinear programming,a maximization throughput optimization algorithm based on Chebyshev and convex(MTCC)for CRN-NOMA is proposed,which converts multi-objective optimization problem into single-objective optimization problem to solve.At the same time,the convergence and time complexity of the algorithm are verified.Theoretical analysis and simulation results show that the algorithm can effectively improve the system throughput.In terms of interference and throughput,the performance of the sub-optimal solution is better than that of orthogonal-frequency-division-multiple-access(OFDMA).This paper provides important insights for the research and application of NOMA in future communications.

Downlink/Uplink Identification of Time-Division Duplexing-OFDMA Systems for Cognitive Radios

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.

CR-NOMA中基于深度确定策略梯度的能效优化策略

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。

基于解码转发CR-NOMA协同系统物理层安全性能分析

分析了认知无线电(Cognitive Radio,CR)非正交多址(Non-orthogonal Multiple Access,NOMA)网络中的物理层安全性能。考虑到现有窃听者,支持NOMA的CR通过Nakagami-m信道以解码转发协作模式传输数据。为了分析CR-NOMA物理层安全性能,通过连接中断概率和安全中断概率的闭式表达式来评估CR-NOMA的安全性能。此外,通过蒙特卡罗模拟仿真以验证推导出的分析结果,并深入分析了参数对系统性能的影响。

Qo E-based resource allocation protocols in cognitive OFDMA network with hybrid model

A resource allocation protocol is presented in an orthogonal frequency division multiple access （OFDMA） cognitive radio （CR） network with a hybrid model which combines overlay and underlay models. Without disrupting the primary user （PU） transmissions, the overlay model allows the secondary user （SU） to utilize opportunistically the idle sub-channels; the underlay model allows the SU to occupy the same sub-channels with PU. The proposed protocols are designed for maximizing the quality of experience （QoE） of CR users and switching dynamically between the overlay and underlay models. QoE is measured by the mean opinion score （MOS） rather than simply fulfilling the physical and medium access control （MAC） layer requirements. The simulations considering the file transfer and video stream services show that the proposed resource allocation strategy is spectrum efficient.

CR-NOMA系统中基于能效的功率分配算法

针对移动通信系统存在频谱利用率不高、能耗开销大和能量效率低的问题,在基于认知无线电非正交多址(Cognitive Radio Non-Orthogonal Multiple Access,CR-NOMA)网络系统中,提出一种基于改进人工鱼群算法的功率分配方案.系统包含多个主次用户,首先为提升频谱效率和降低解调的误码概率以及时延,次用户以非正交多址的形式接入系统,并采用一种均匀信道增益差的策略对用户进行分组.其次,考虑到传统人工鱼群算法对次用户功率寻优易掉进局部最优解、寻优能力弱和种群多样性差等不足,将约束算子机制和自适应策略引入人工鱼群算法中;最后,使用该算法联合优化各子信道间功率与子信道内次用户功率,寻求次用户最佳发射功率以最大化系统总能量效率.实验结果表明,在次用户为30的条件下,改进的人工鱼群算法所获总能量效率比传统人工鱼群算法提升了10.6%,具有更好的系统性能.

基于无线携能的全双工CR-NOMA系统物理层安全性能分析

针对认知非正交多址(CR-NOMA,cognitive radio non-orthogonal multiple access)系统在信息传输过程中存在能量受限和物理层安全问题,构建基于无线携能的全双工多中继协作CR-NOMA系统模型。首先,在多中继的基础上提出了一种最优中继选择策略。其次,推导了系统安全中断概率和安全吞吐量的近似表达式。最后,通过仿真验证了理论分析的正确性,分析了中继个数、目标安全速率、干扰功率阈值以及自干扰信道系数和功率分割系数等因素对系统安全性能的影响,为CR-NOMA网络安全通信提供了可行的传输策略。

Cooperative Spectrum Sensing Deployment for Cognitive Radio Networks for Internet of Things 5G Wireless Communication

Recently,Cooperative Spectrum Sensing(CSS)for Cognitive Radio Networks(CRN)plays a significant role in efficient 5G wireless communication.Spectrum sensing is a significant technology in CRN to identify underutilized spectrums.The CSS technique is highly applicable due to its fast and efficient performance.5G wireless communication is widely employed for the continuous development of efficient and accurate Internet of Things(IoT)networks.5G wireless communication will potentially lead the way for next generation IoT communication.CSS has established significant consideration as a feasible resource to improve identification performance by developing spatial diversity in receiving signal strength in IoT.In this paper,an optimal CSS for CRN is performed using Offset Quadrature Amplitude Modulation Universal Filtered Multi-Carrier Non-Orthogonal Multiple Access(OQAM/UFMC/NOMA)methodologies.Availability of spectrum and bandwidth utilization is a key challenge in CRN for IoT 5G wireless communication.The optimal solution for CRN in IoT-based 5G communication should be able to provide optimal bandwidth and CSS,low latency,Signal Noise Ratio(SNR)improvement,maximum capacity,offset synchronization,and Peak Average Power Ratio(PAPR)reduction.The Energy Efficient All-Pass Filter(EEAPF)algorithm is used to eliminate PAPR.The deployment approach improves Quality of Service(QoS)in terms of system reliability,throughput,and energy efficiency.Our in-depth experimental results show that the proposed methodology provides an optimal solution when directly compares against current existing methodologies.

认知无线电系统多接入用户信息新鲜度研究

为了解决物联网信道资源有限的问题以及提高物联网系统的信息时效性,考虑了包括一个主用户(primary user,PU)和两个次用户(secondary user,SU)节点的多接入认知无线电(CR)物联网系统模型。在PU工作状态和SU数据队列稳定的约束下,分别分析了第一个SU节点在先来先服务(first come first served,FCFS)、后来先服务(last come last served,LCLS)以及包丢弃队列下的平均信息年龄(age of information,AoI),推导了在阈值策略下第二个SU节点的平均AoI。然后,提出了使第一个SU平均AoI最小化,并且第二个SU的平均AoI低于给定阈值的优化问题。优化问题的约束条件是凸的,但所得到的目标函数是非凸的,故引入了一种次优技术,利用双层凸优化算法得到最优解。仿真结果给出了所考虑优化算法在不同系统参数下的性能,该算法在不同系统参数和多天线影响下的性能表现良好。后续工作可以考虑扩展到两个以上次用户的CR物联网系统。

采用无线携能技术的中继辅助CR-NOMA系统能效分析

针对现有关于认知无线电非正交多址接入网络的研究中终端电池容量有限和能源利用率低的缺点,采用了中继辅助用户进行传输,并且引入无线信息和能量同时传输的方式。在用户服务质量和最小能量捕获的约束条件下推导了次用户传输能效表达式,通过分式规划方法把非凸的目标函数转化为优化中继发射功率、中继功率分配和接收端功率分配三个凸的单目标问题,并分别用函数单调性、黄金分割算法、拉格朗日对偶算法和多目标联合优化算法进行优化,求得了全局最优解,使次用户系统传输能效最大化。对所采用的算法复杂度进行分析,仿真结果表明:与传统的正交多址接入方案相比较,在提高系统频谱利用率的同时,次用户传输能效有47%的提高。

一种面向CR-NOMA系统的动态功率分配算法

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.

基于非正交多址接入的星空地多用户认知网络性能研究

卫星通信(SatCom)因其强大的生存能力和无缝覆盖的独特优势,能够弥补地面通信网络受地形限制、覆盖范围小等短板,在当前和未来的无线通信系统中具有重要的地位。此外,空中辅助通信由于其在星地网中的灵活性和可扩展性,具有很高的研究价值。为克服星空地网络(ISATN)中频谱短缺问题,认知无线电(CR)和非正交多址接入(NOMA)被用于提高频谱利用率和传输性能。因此,该文研究了基于NOMA的星空地认知网络(CISATN)的性能,考虑多用户场景,分别得到了主网络和次级网络的中断概率(OP)的准确表达式和高信噪比下的渐进表达式,并给出了这两个网络的分集增益。最后,通过蒙特卡罗仿真验证了理论推导的正确性,并分析了关键变量对系统指标的影响。

两级中继选择的协作CR-NOMA网络性能分析

本文研究了中继选择方案对协作下认知非正交多址(CR-NOMA)网络中断性能的影响,提出了一种两级中继选择方案。第一时隙在保证主用户服务质量的基础上,次级网络源节点向认知中继集群广播叠加信号。第二时隙认知中继提供解码转发服务,协助源节点传输信息。基于上述假设,推导了次级用户中断概率的闭合表达式并给出了分析结果。证明相比于部分中继选择策略,两级中继选择策略可以达到更好的中断性能和更大的分集增益。同时本文的分析结果验证了备选中继节点数目和功率分配因子对系统中断性能的影响,蒙特卡罗仿真验证了理论结果。