认知无线电网络的检查协作频谱感知技术

在认知无线电中,协作频谱感知通常被用来提高感知性能。但当用户个数较多时,控制信道带宽的限制和感知时延会影响协作感知的性能。作者提出采用检查协作频谱感知可以有效避免这些问题。检查协作频谱感知通过减少认知用户上报基站的感知信息,降低通信负荷和感知时延,从而提高系统的敏感性。通过最大化频谱利用率可以得到最优的不发送概率,从而在感知时延和接入频谱机会的错失上得到折衷。通过分析及仿真结果可以看出,检查协作感知与传统协作感知相比,有效提高了系统的敏感性。通过最优的不发送概率可以确定最佳的感知门限进行感知。     

采用软合并合作检测的认知无线电系统的吞吐量优化

为了最大化认知无线电系统的吞吐量,以采用等增益软合并合作检测的认知无线电系统为例,建立了在主用户得到充分保护的条件下系统吞吐量的优化模型,优化参数分别为本地检测时间和参与合作检测的用户数．利用最优化理论证明了系统吞吐量是本地检测时间的凹函数,并基于该结论给出了最大吞吐量的联合搜索算法．仿真结果验证了理论分析,并给出了不同传输开销下的最大吞吐量及其对应的最优参数．     

Joint optimization of cooperative sensing and transmission in energy-efficiency cognitive radio

Aiming at the low energy utilization caused by the sensing energy consumption of cognitive radio (CR), we propose to improve the energy efficiency (EE) of multi-channel CR by jointly optimizing cooperative spectrum sensing and transmission resources. Setting optimizing parameters such as cooperative spectrum sensing time, sensing threshold, transmission bandwidth and power, etc., the optimization model for maximizing EE is built based on the periodic cooperative spectrum sensing. The proposed non-convex optimization model is effectively resolved by a combined algorithm of the interior method and Dinkelbach's optimization. Simulation results show that when the detection probability is 0.6, compared with the traditional maximizing spectrum efficiency model, the transmission rate of the maximizing energy efficiency model increases by 100bit/(s·Hz^-1) under unit energy. The proposed model decreases the sensing power consumption and improves the energy utilization effectively.     

认知网络中控制信道受限的协作频谱感知

在噪声不确定的条件下,提出一种多频带联合协作感知方法,根据各频段噪声功率的不确定度分别计算出检测门槛上、下限后对本地主用户信号进行多频带联合检测.接收信号能量处于检测门槛上下限之间的频段为本地检测结果不确定的频段,需要进行多点协作频谱感知,认知节点可利用本地检测中确定空闲的频段来传递本节点的感知信息,实现由本节点可用信道分担传统协作感知方法中控制信道通信量的目标.仿真结果表明,对比传统协作感知方法,新提出的协作感知方法能有效减少频谱感知过程中控制信道的通信负载,并且在本地检测结果为不确定的频段能获得更小的误警概率.     

Opportunistic best-relay node selection for cooperative transmission improvement over underlay cognitive radio networks

In cognitive radio (CR) relay networks,most previous work concentrates on maximizing physical layer quality of service (QoS),e.g.,spectral efficiency and achievable data rate,as relay selection criteri...     

认知无线电安全研究综述

为深入理解认知无线电安全问题,掌握其研究现状及发展趋势,从传统型和特殊型两个角度,对目前认知无线电网络中存在的拒绝服务攻击、自私行为攻击、路由安全、密钥协商、GPS信息干扰、主用户伪造攻击、频谱感知数据篡改攻击等安全问题进行概述,并对解决安全问题的典型方案进行归纳总结。此外,针对目前相关研究中所存在的问题,明确了一些有待继续研究的方向。     

Distributed optimal relay selection for spectral efficiency improvement in underlay-paradigm based cognitive radio networks

A distributed best-relay node selection scheme is investigated for cooperative communications with adaptive modulation and coding(MAC) strategy over underlay-paradigm based cognitive radio(CR) networks.The scheme aims to maximize the average spectral efficiency and meanwhile to guarantee that the primary link is provided with a minimum-rate for a certain percentage of time.Simulation results demonstrate that the proposed scheme can significantly improve the spectral efficiency compared with other existing schemes.     

基于能量检测的频谱感知方法分析

简要介绍了认知无线电中基于能量检测的频谱感知方法,在分析能量检测法原理和性能基础上,研究了噪声的不确定性对检测性能的影响.仿真表明,能量检测法是一种简单、有效的频谱感知方法.     

Delay optimization scheduling algorithm in cognitive radio networks

In cognitive radio networks, delay scheduling optimization has attracted an increasing attention in recent years. Numerous researches have been performed on it with different scenarios. However, these approaches have either high computational complexity or relatively poor performance. Delay scheduling is a constraint optimization problem with non-deterministic polynomial (NP) hard feathers. In this paper, we proposed an immune algorithm-based suboptimal method to solve the problem. Suitable immune operators have been designed such as encoding, clone, mutation and selection. The simulation results show that the proposed algorithm yields near-optimal performance and operates with much lower computational complexity.     

认知无线电中基于分派问题模型的优化PAPR算法

基于WOFDM的认知无线电(CR)系统,将分派问题的优化模型应用于抑制峰均功率比(PAPR)的研究。在滤波器组级数固定的条件下,选择最优小波包基调制信号,使系统获得最优峰均功率比。分析及仿真表明,新算法既不损失系统误码率(BER)性能,又能明显地抑制系统PAPR,并且不需要任何边带信息。此外,新算法的设计满足并行计算的限制,可实现基于多核编程的并行计算,从而确保新算法的执行性能。     

保密MIMO无线携能系统的鲁棒能效优化

针对多输入多输出无线携能系统,研究了在多个窃听者存在且其信道状态信息不准确情况下的保密能量效率优化问题．在最大发射功率和最小收获能量的约束条件下,通过联合设计波束成形矩阵、辅助噪声方差矩阵和功率分配比,最大化系统最差情况的保密能量效率．基于分式理论,将原来的非凸分式问题转换成易处理的减式形式．通过S-procedure和一阶泰勒级数展开,将难于处理的非凸问题转化为凸问题．在此基础上提出了基于Dinkelbach方法的两级优化迭代算法,仿真结果验证了该算法的有效性和收敛性．     

认知无线电中移动认知用户功率控制方法

传统认知无线电中的功率控制问题都是基于认知用户位置不变的情况,本文针对可移动认知用户的功率控制问题进行深入研究. 首先对不同通信场景进行分析和归一化整理,建立通用通信模型,极大的简化了干扰估计和功率控制算法;其次根据认知用户的可移动性,推导出授权用户所受干扰与认知用户移动距离和运动矢量方向的函数表达式,实现了认知用户对授权用户干扰的实时预测;根据预测结果采用最小发射功率准则实现认知用户的功率控制. 仿真结果表明,本文方法能够实时、高效的对认知用户进行功率控制,与采用固定步长的功率控制算法相比能够节约功耗20%.     

认知无线电网络中的最佳可信度频谱检测算法

由于认知无线电网络中的典型硬决策协作频谱检测在数据融合时未考虑各认知用户检测结果的差异性,不能很好地提高检测性能,因此,提出了一种基于检测可信度的协作频谱检测算法.首先,利用各认知用户的平均接收信噪比来获得它们的检测可信度;然后,综合各认知用户的检测结果以及检测可信度来判断授权用户是否使用频带,从而提高了检测性能.仿真结果表明,在低信噪比情况下,相比典型硬决策协作频谱检测,该算法具有较优的接收特性曲线,并在合理选取认知用户检测阈值的条件下,具有较低的检测错误概率.     

Research on cooperative detection and multiple access for cognitive radio system

As cognitive radio (CR) needs to detect spectrum accurately and utilize the idle spectrum efficiently,a new model of CR is proposed.This model adopts energy detection with auto-adapted threshold and pr...     

认知无线电网络上行链路子载波和功率分配

在干扰温度和总发送功率的约束条件下,针对基于正交频分多址(OFDMA)接入方式的认知无线电网络上行链路提出了一种最优子载波和功率分配方案,目标为最大化系统吞吐量。该问题被建模为一个非凸优化问题,通过使用拉格朗日对偶分解和KKT条件,提出的算法收敛于该问题的最优解。仿真结果表明,该算法在大大降低复杂度的同时,达到了穷举方案的性能。     

多载波认知无线电无线携能通信资源分配算法

认知无线电可通过频谱感知提高资源利用率,但会产生感知能耗,降低传输能量.为了保证认知无线电的传输性能,提出认知无线电可利用多载波实现无线携能通信,并分配通信资源,实现系统性能优化.认知无线电利用部分子载波传输信息,采集剩余子载波上主用户射频能量,补充感知耗能.提出的子载波和子载波功率联合优化算法,在保证能量、干扰和总功率受约束的基础上,可最优化系统的吞吐量和能量.仿真结果表明,能量采集会占用传输资源,需要合理分配子载波,使其在速率和能量间取得性能折中.提出的算法通过采集能量补充感知能耗有效地提高了系统吞吐量.     

认知无线电最短传输时延路由算法

针对传统路由协议在认知网络中存在的缺陷,提出了一种基于最短传输时延的路由算法(SDCR)．SDCR综合考虑认知网络特性,通过计算给定数据包的链路传输时延,并将此传输时延作为链路的边权值,利用经典的迪克斯屈拉算法找出传输时延最短的路由．仿真分析表明,SDCR具有比传统路由协议更短的端到端时延．     

Statistical spectrum analysis and allocation in cognitive radio networks

The bandwidth of spectrum holes is time-varied in cognitive radio networks with dynamic spectrum environment, which leads to the traditional static spectrum allocation poor performance. To solve this issue, this paper derives the probability density function of bandwidth of spectrum holes and presents a novel spectrum allocation algorithm based on the stochastic multiple knapsack problem. Simulation results illustrate that the proposed algorithm can achieve a better performance than the existing algorithms when the bandwidth of spectrum holes is time-varied.     

A novel spectrum prediction scheme based on SVM in cognitive radio networks

In cognitive radio networks, Secondary Users (SUs) have opportunities to access the spectrum channel when primary user would not use it, which will enhance the resource utilization. In order to avoid interference to primary users, it is very important and essential for SUs to sense the idle spectrum channels, but also it is very hard to detect all the channels in a short time due to the hardware restriction. This paper proposes a novel spectrum prediction scheme based on Support Vector Machines (SVM), to save the time and energy consumed by spectrum sensing via predicting the channels’ state before detecting. Besides, spectrum utilization is further improved by using the cooperative mechanism, in which SUs could share spectrum channels’ history state information and prediction results with neighbor nodes. The simulation results show that the algorithm has high prediction accuracy under the condition of small training sample case, and can obviously reduce the detecting energy, which also leads to the improvement of spectrum utilization.     

认知网络中基于连续双向拍卖的动态频谱分配

非合作认知无线电网络中,多个主用户和多个第2用户并存．主用户和第2用户是自私的和理性的,主用户和第2用户都希望在不影响他人收益的前提下获得自己的最大收益．这符合连续双向拍卖市场对用户的假设条件．针对这一特点,基于实验经济学理论,提出了基于模糊逻辑连续双向拍卖的动态频谱分配策略．在频谱拍卖过程中,主用户和第2用户均采用基于模糊逻辑的报价策略．采用该方法,主用户和第2用户可以根据交易情况实时调整自己的报价步长,减少报价次数,迅速完成交易．仿真结果表明该方法的频谱分配效率为85％,较好地解决了非合作认知网络中多对多环境下的动态频谱分配问题．