Multi-criteria user selection scheme for learning-based multiuser MIMO cognitive radio networks

For multiuser multiple-input-multiple-output （MIMO） cognitive radio （CR） networks a four-stage transmiision structure is proposed. In learning stage, the learning-based algorithm with low overhead and high flexibility is exploited to estimate the channel state information （ CSI ） between primary （PR） terminals and CR terminals. By using channel training in the second stage of CR frame, the channels between CR terminals can be achieved. In the third stage, a multi-criteria user selection scheme is proposed to choose the best user set for service. In data transmission stage, the total capacity maximization problem is solved with the interference constraint of PR terminals. Finally, simulation results show that the multi-criteria user selection scheme, which has the ability of changing the weights of criterions, is more flexible than the other three traditional schemes and achieves a tradeoff between user fairness and system performance.

基于预留信道机制的CR频谱切换描述及改进

利用IEEE802.22标准草案中的预留信道机制,分析和描述认知无线电的3种基本频谱切换方案。针对预留信道机制以牺牲新呼阻塞率换取较低切换阻塞率的不足,提出对新呼用户进行排队缓冲的方法,并利用二维马尔可夫模型和排队理论,给出其状态转移图。仿真结果表明,该方法在保证切换性能的条件下,能有效降低新呼阻塞率,并使GoA值大幅下降。

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。

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.

CR系统中基于博弈论的频谱分配算法及仿真

在分析了无线电频谱管理现状及频谱资源紧张的前提下,引出频谱管理中的认知无线电技术,同时提出了基于博弈论的电磁频谱管理的模型化方法,深入地分析了博弈论算法的收敛性及效用函数的选择,并且通过Matlab仿真以最小化系统间总干扰为目标描述了博弈论模型在电磁频谱动态管理中的应用。

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。

认知智能电网中基于非合作博弈的电视频谱资源共享研究

智能电网(Smart Grid,SG)中的需求响应管理(Demand Response Management,DRM)是SG的控制单元,用来平衡实时负荷及转移高峰时段负荷。通信对于DRM的准确性和最优性至关重要,在智能电网的邻域网中广泛采用无线网络作为通信网,但是用于无线通信的频谱资源目前未被充分利用。随着模拟广播电视向数字电视的过渡,在电视频谱中产生更多的电视空白(TV White Space,TVWS)频谱。基于此,通过及建立Underlay模式下的TVWS频谱共享分层网络模型,以提高频谱利用率,并提出基于非合作博弈功率控制算法。数值结果表明,提出的方法可以提高频谱的利用率,有益于发挥DRM的性能。

L-CR系统中分布式压缩感知最小角回归信号重构

在低轨(LEO)微小卫星感知无线电(L-CR)系统中,多个LEO卫星节点具备一定的频谱感知功能,卫星节点通过分布式组网对地面信关站发射的信息进行感知、传输和处理,地面汇聚节点对LEO卫星节点转发信号进行重构。考虑LEO系统中授权频带的主用户(PU)对卫星认知用户(SU)的干扰,认知用户感知到的信号同时存在PU干扰和噪声,地面汇聚节点通过高效的重构算法进行含噪信号恢复是L-CR系统实现的重要问题。论文研究了LCR系统中基于分布式压缩感知的信号重构方法。针对L-CR特点,分别分析了汇聚节点在低信噪比情况下采用凸松弛法中的基追踪去噪(BPDN)、同伦(Homotopy)法和最小角回归(Lars)的重构均方误差(MSE)与重构复杂度。研究表明,BPDN具有最小的重构MSE,但其重构复杂度最高。Lars可以有效折衷重构MSE与复杂度。在此基础上,提出了基于分布式压缩感知的最小角回归(DCS-Lars)信号重构方案。仿真结果表明,所提DCS-Lars方法可以在低信噪比情况下有效重构感知信号,并具有良好的频谱检测能力,同时重构复杂度大大降低。

基于博弈论的电视频谱感知与传输安全策略

利用认知无线电(Cognitive Radio,CR)技术,次用户(Secondary Users,SU)在感知电视空白信道时会面临干扰攻击,在传输数据阶段也会受到大量干扰与窃听攻击。针对感知和传输两阶段都存在的恶意攻击,首先利用能量采集(Energy Harvesting,EH)技术建立EH-CR系统模型,并提出时隙下的效用函数。其次,利用势博弈与Stackelberg博弈两层博弈分别研究了SU最优传输信道与最优时隙分配策略,逐渐优化感知检测概率和传输保密容量。再次,为了进一步提高安全性能,在每个时隙最后给出发射功率迭代更新公式,合理利用SU剩余能量。最后,通过仿真验证了所提方法在检测率和保密容量上的优越性。

干扰攻击下基于MAPPO的电视频谱资源分配研究

将认知无线电(Cognitive Radio,CR)与能量采集(Energy Harvesting,EH)进行组合是一种提高电视系统频谱性能的有效方案,但由于CR的开放性,电视网络容易遭受干扰攻击。基于此,研究了干扰攻击下EH-CR网络的联合信道和功率分配问题,考虑网络中存在随机和反应扫描两种干扰攻击,通过信道接入和功率分配,使次用户(Secondary Users,SUs)平均吞吐量最大化。将EH-CR网络建模为部分可观测的马尔可夫决策过程,提出了一个基于多智能体近端策略优化(Multi-Agent Proximal Policy Optimization,MAPPO)的联合信道和功率分配方法。仿真结果表明,提出的方法能够显著提高干扰攻击下SUs的平均吞吐量。

不完全SIC下CR-NOMA系统的功率分配算法

在不完全连续干扰消除(SIC)条件下,对认知无线电-非正交多址混合系统中的次用户总传输速率进行研究,提出一种基于参数变换和KKT条件的功率分配算法。采用非正交多址方式使次用户接入授权信道,在主次用户服务质量、最大发射功率等约束条件下,通过参数变换对原约束条件进行改写设计新的优化问题,并利用KKT条件求解最优功率分配因子进而实现系统中次用户总传输速率的最大化。仿真结果表明,与CNPA算法和等功率分配算法相比,该算法可明显提高系统中次用户的总传输速率,并且对于不完全SIC具有更强的承受能力。

Quantum fireworks algorithm for optimal cooperation mechanism of energy harvesting cognitive radio

For acquiring high energy efficiency and the maximal throughput, a new time slot structure is designed for energy harvesting(EH) cognitive radio(CR). Considering the CR system with EH and cooperative relay, a best cooperative mechanism(BCM)is proposed for CR with EH. To get the optimal estimation performance, a quantum fireworks algorithm(QFA) is designed to resolve the difficulties of maximal throughput and EH, and the proposed cooperative mechanism is called as QFA-BCM. The proposed QFA combines the advantages of quantum computation theory with the fireworks algorithm(FA). Thus the QFA is able to obtain the optimal solution and its convergence performance is proved. By using the new cooperation mechanism and computing algorithm, the proposed QFA-BCM method can achieve comparable maximal throughput in the new timeslot structure. Simulation results have proved that the QFA-BCM method is superior to previous non-cooperative and cooperative mechanisms.

MODELING RADIO RESOURCE MANAGEMENT IN COGNITIVE RADIO SYSTEM BASED ON OFDMA USING COLORED PETRI NET

Cognitive Radio(CR) system based on Orthogonal Frequency Division Multiple Access(OFDMA),such as Wireless Regional Area Networks(WRAN) and Worldwide Interoperability for Microwave Access(WiMAX),often attempt to improve performance via dynamic radio resource management,which is characterized as concurrent processing of different traffic and nondeterministic system capacity.It is essential to design and evaluate such complex system using proper modeling and analysis tools.In the previous work,most of the communication systems were modeled as Markov Chain(MC) and Stochastic Petri Nets(SPN),which have the explicit limitation in evaluating adaptive OFDMA CR system with wide area traffic.In this paper,we develop an executable top-down hier-archical Colored Petri Net(CPN) model for adaptive OFDMA CR system,and analyze its performance using CPN tools.The results demonstrate that the CPN can model different radio resource manage-ment algorithms in CR Systems,and the CPN tools require less computational effort than Markov model using Matlab,with its flexibility and adaptability to the traffics which arrival interval and processing time are not exponentially distributed.

A DYNAMIC SPECTRUM ACCESS NETWORK BASED ON COGNITIVE RADIO

Dynamic spectrum access technologies based on Cognitive Radio(CR) is under intensive research carried out by the wireless communication society and is expected to solve the problem of spectrum scarcity.However,most enabling technologies related to dynamic spectrum access are con-sidered individually.In this paper,we consider these key technologies jointly and introduce a new implementation scheme for a Dynamic Spectrum Access Network Based on Cognitive Radio(DSAN-BCR).We start with a flexible hardware platform for DSAN-BCR,as well as a flexible protocol structure that dominates the operation of DSAN-BCR.We then focus on the state of the art of key technologies such as spectrum sensing,spectrum resources management,dynamic spectrum access,and routing that are below the network layer in DSAN-BCR,as well as the development of technologies related to higher layers.Last but not the least,we analyze the challenges confronted by these men-tioned technologies in DSAN-BCR,and give the perspectives on the future development of these technologies.The DSAN-BCR introduced is expected to provide a system level guidance to alleviate the problem of spectrum scarcity.

SPECTRUM HANDOFF IN COGNITIVE RADIO WITH FUZZY LOGIC CONTROL

The secondary usage of spectrum has been investigated in Cognitive Radio(CR) network to resolving the spectrum scarcity issue in wireless communication.When Primary Users(PU) who own the spectrum appear,spectrum handoff is needed to maintain the communications of Secondary Users.But the decision making of spectrum handoff is a challenge issue for CR network,because the input of decision making,which obtain through spectrum sensing,is heterogeneous and inexact.In this paper we will use fuzzy logic control theory to solve this issue and make use of new information for handoff operation:the probability of PU's occupancy at a certain channel.Our new algorithm can make more intelligent decision compared to simple traditional spectrum handoff decision making and reduce the probability of spectrum handoff,also the performance of SU's communication can be enhanced.

A HIGH SENSITIVITY AND WIDE DYNAMIC RANGE ZERO-IF RF RECEIVER FOR COGNITIVE RADIO APPLICATION

This paper presents an RF receiver of zero-Intermediate Frequency(IF) architecture for Cognitive Radio(CR) communication systems.Zero-IF architecture reduce the image reject filter and IF filter,so it is excellent in low cost,compact volume,and low power dissipation.The receiver employs three digital attenuator and a high gain,high linearity low noise amplifier to achieve wide dynamic range of 70 dB and high receiving sensitivity of-81 dBm.A fully balanced I/Q demodulator and a differential Local Oscillator(LO) chips are used to minimize the negative effects caused by second-order distortion and LO leakage.In order to select an 8 MHz-channel from 14 continuous ones located in UHF band(694-806 MHz) accurately,approach of channel selectivity circuits is proposed.The RF receiver has been designed,fabricated,and test.The measured result shows that the noise figure is 3.4 dB,and the error vector magnitude is 7.5% when the input power is-81 dBm.

NOVEL SPECTRUM SENSING METHOD BASED ON THE SPATIAL SPECTRUM FOR COGNITIVE RADIO SYSTEMS

Spectrum sensing is the key problem for Cognitive Radio(CR) systems.A method based on the Peak-to-Average Amplitude-Ratio(PAAR) of the Spatial Spectrum(SS) of the received signals is proposed to sense the available spectrum for the cognitive users with the help of the multiple antennas at the receiver of the cognitive users.The greatest advantage of the new method is that it requires no information of the noise power and is free of the noise power uncertainty.Both the simulation and the analytical results show that the proposed method is robust to noise uncertainty,and greatly outperform the classical Energy Detector(ED) method.

Optimal spectrum allocation of primary users in light-handed cognitive radio networks

In traditional cognitive radio(CR) network,secondary users(SUs) are always assumed to obey the rule of"introducing no interference to the primary users(PUs) ".However,this assumption may be not realistic as the CR devices becoming more and more intelligent nowadays.In this paper,with the concept of lighthanded CR,which is proposed to deal with the above mentioned problem by enforcing"punishment"to illegal CR transmissions,the action decisions of primary users(PUs) are modeled as a partially observable Markov decision process(POMDP),and the optimal spectrum allocation scheme with the objective of maximizing their reward is proposed,which is defined by the utility function.Furthermore,a reduced scheme with much smaller state space has been proposed in this paper for lower computational complexity.Extensive simulation results show that the proposed schemes improve the reward significantly compared to the existing scheme.

Tracking performance of large margin classifier in automatic modulation classification with a software radio environment

Automatic modulation classification is the process of identification of the modulation type of a signal in a general environment. This paper proposes a new method to evaluate the tracking performance of large margin classifier against signal-tonoise ratio （SNR）, and classifies all forms of primary user＇s signals in a cognitive radio environment. For achieving this objective, two structures of a large margin are developed in additive white Gaussian noise （AWGN） channels with priori unknown SNR. A combination of higher order statistics and instantaneous characteristics is selected as effective features. Simulation results show that the classification rates of the proposed structures are well robust against environmental SNR changes.

A COLLABORATIVE SPECTRUM SENSING SCHEME USING FUZZY COMPREHENSIVE EVALUATION IN COGNITIVE RADIO

Cognitive Radio(CR) is a promising technology to solve the challenging spectrum scarcity problem.However, to implement CR, spectrum sensing is the groundwork and the precondition.In this paper, a collaborative spectrum sensing scheme using fuzzy comprehensive evaluation is proposed.The final sensing decision of the proposed scheme is based on the combination of distributed sensing results of different Secondary Users(SUs).To improve the reliability of the sensing decision, the combination procedure takes into account the credibility of each SU, which is evaluated using fuzzy comprehensive evaluation.The effect of the presence of malicious SUs and malfunctioning SUs on the performance of the proposed scheme is also investigated.The efficiency of the scheme is validated through analysis and simulation.