认知无线电的频谱感知技术探讨

频谱感知允许非许可用户伺机访问未用的许可频带资源,可以极大改善频谱利用率,并且具有较低的部署成本和较好的兼容性。文中首先介绍了认知无线电中频谱感知的相关概念。然后,详细探讨了频谱感知的基本技术手段和面临的挑战。最后,对频谱感知的设计问题进行了说明。     

感知不确定下卫星认知无线网络多频谱接入优化策略

针对卫星认知无线网络频谱感知不确定性较大导致传统频谱接入机制效率降低的问题,该文提出一种基于动态多频谱感知的信道接入优化策略。认知LEO卫星根据频谱检测概率与授权用户干扰门限之间的关系,实时调整不同频谱感知结果下的信道接入概率。在此基础上以系统吞吐量最大化为目标,设计了一种基于频谱检测概率和虚警概率联合优化的判决门限选取策略,并推导了最佳感知频谱数量。仿真结果表明,认知用户能够在不大于授权用户最大干扰门限的前提下,根据授权信道空闲状态动态选择最佳频谱感知策略,且在检测信号信噪比较低时以更加积极的方式接入授权频谱,降低了频谱感知不确定性对信道接入效率的影响,提高了认知系统吞吐量。     

认知无线电网络中的频谱感知技术及面临的挑战

频谱感知作为认知无线电的关键技术之一,允许非授权用户伺机访问未使用的授权频带资源,从而大大改善了频谱利用率,并且具有较低的部署成本和较好的兼容性。文章首先介绍了认知无线电的概念和频谱感知提出的背景;然后详细探讨了频谱感知面临的技术挑战和设计权衡,并考虑了安全性问题;最后对可能威胁频谱感知的安全问题进行了说明并给出了结论。     

感知无线电中的频谱检测技术

感知无线电可以自动感知外界的无线环境并能调整系统参数以适应环境的变化。频谱检测是感知无线电的关键技术之一，要求感知用户可靠、快速地检测频谱空洞。文中按照主用户发射端检测和主用户接收端检测，对当前的主要频谱检测算法进行了分类，并对频谱检测算法进行了讨论和对比研究，给出了在IEEE802．22和频谱池结构中的频谱检测的具体应用。     

频谱异构认知无线电中基于吞吐量降的空时频谱机会感知

在认知无线电(CR)中,频谱感知是实现动态频谱接入的关键技术之一。为适当保护主用户并最大化次级用户的性能,目前大部分相关工作均是用虚报概率和漏检概率作为感知度量来确定最佳感知参数的。但这种度量是用主次用户的碰撞概率来衡量次级用户对主用户的影响的,没有考虑干扰强度的影响,仅适合同构频谱环境;在不同位置次级用户有不同接入机会的异构频谱环境中,并不能最大化频谱利用率。为此,该文首先定义了吞吐量降,并提出在异构频谱环境下采用吞吐量降作为一种新的感知度量。吞吐量降是指由于次级用户占用授权频谱而导致主用户吞吐量下降的百分比。在衡量次级用户对主用户的影响时,它综合了主次用户的碰撞概率和干扰强度两个因素;其次,研究了以吞吐量降为约束的次级用户吞吐量优化问题。最后,数值仿真证实了该方案比目前几种传统方案的频谱利用率显著提高。     

动态频谱接入中基于最小贝叶斯风险的稳健频谱预测

针对频谱感知错误累积造成频谱预测性能恶化问题,该文提出一种基于最小贝叶斯风险的稳健频谱预测策略。分布拟合检验表明频谱预测输出服从正态分布,定义频谱预测输出的贝叶斯风险函数,证明使贝叶斯风险函数最小的频谱预测输出判决门限将使频谱预测的均方误差最小,求得了使贝叶斯风险最小的最优判决门限,构建稳健频谱预测策略。仿真结果表明,与固定判决门限的神经网络频谱预测相比,稳健频谱预测策略改进了频谱感知错误下的频谱预测性能,改善了非授权用户的动态频谱接入性能。     

一种非理想感知条件下的双门限机会频谱接入策略

为了有效提高认知网络中次用户的吞吐率性能,提出了一种应用于非理想感知条件下的双门限机会频谱接入策略。该策略能在次用户对信道占用情况感知非理想的条件下,综合考虑次用户的信道质量和非准确的信道占用信息,使次用户在信道感知为空闲和占用时分别以不同的信道质量门限选择接入信道,从而最大程度地利用信道质量较好的传输机会,提高次用户的吞吐率性能。结合本策略,建立了以次用户的有效吞吐率最大化为目标、以对主用户的干扰程度为约束条件的优化问题,并在次用户对信道感知存在误差的条件下给出了最优门限的设计方法。仿真结果表明,所提出的双门限机会频谱接入策略能够在非理想感知条件下显著提高次用户的有效吞吐率。     

等比缩减的机会频谱接入

重复使用一定的TV频段是机会频谱接入的一个典型应用。在认知无线电机会频谱接入中,为了最大化信道的利用,授权用户与认知用户相互协作共同利用信道。文章将授权用户对信道的占用过程模拟为连续时间马尔可夫过程。认知用户在限制其对授权用户的干扰影响条件下,利用等比缩减的策略对信道进行感知,提出一个最优频谱接入策略,提高频谱的利用率。     

分段LFM调制随机波形反侦察设计

频谱感知通过搜索空间中的空闲频段或干扰较少的频段,为未授权用户提供频谱接入的机会,是认知雷达中的一项关键技术。众所周知,协作感知可以提高频谱感知的精度,但是往往需要设置专门的控制信道来汇报协作节点的本地感知结果。这种汇报方式不利于节约信道资源。为了解决这一难题,提出了一种直接利用感知信道进行感知结果汇报的协作感知机制。该机制通过本地感知和协作感知的自适应切换及汇报节点的自适应功率控制,不仅提高了频谱感知的精度,而且节约了汇报信道资源。最后,通过仿真实验验证了该机制的有效性。文中提出的协作感知机制对认知雷达系统的设计具有重要的理论和实践意义。     

合作频谱感知吞吐量和感知时间关系的研究

频谱感知是认知无线电的关键技术之一,能量检测是频谱感知的常用方法.为了用最少的频谱感知时间得到最大的系统吞吐量,文中研究了在合作频谱感知情况下两者的关系.通过仿真得到,合作频谱感知可以增加系统的吞吐量,减少频谱感知时间,同时用户的数量以及帧长对增加系统吞吐量和减少感知时间均产生一定的影响.     

基于监督学习的协作宽带压缩频谱检测方案

宽带压缩频谱检测存在信号稀疏度未知和次用户检测开销过大的问题.因此,本文提出一种高效的协作宽带压缩频谱检测方案.首先,推导了一种基于学习的稀疏度自适应预测模型.其次,设计了一种宽带频谱筛选算法.最后,提出一种协作宽带压缩频谱检测方案.仿真结果表明,自适应预测模型的拟合效果优于现有预测模型,并且所提检测方案也有效地降低了次用户采样率和频谱重构时延.     

Dynamic control approaches of spectrum sensing in multi-band cognitive radio networks

In this paper,the dynamic control approaches for spectrum sensing are proposed,based on the theory that prediction is synonymous with data compression in computational learning. Firstly,a spectrum sensing sequence prediction scheme is proposed to reduce the spectrum sensing time and improve the throughput of secondary users. We use Ziv-Lempel data compression algorithm to design the prediction scheme,where spectrum band usage history is utilized. In addition,an iterative algorithm to find out the optimal number of spectrum bands allowed to sense is proposed,with the aim of maximizing the expected net reward of each secondary user in each time slot. Finally,extensive simulation results are shown to demonstrate the effectiveness of the proposed dynamic control approaches of spectrum sensing.     

授权用户信号随机到达时基于双门限的多用户合作频谱感知方法

针对认知无线电系统中可能出现的授权用户信号随机到达时的频谱感知问题,提出了一种基于双门限的多用户合作频谱感知方法.首先在本地判决时采用高低双门限的方式,如果判决量大于高门限就判1,小于低门限判0,在两个门限之间就把判决量直接发送给融合中心,融合中心将直接收到的判决量进行软判决合并,软判决的结果再与其他硬判决的结果进行"OR原则"的硬判决合并,从而得到最终的判决结果.仿真表明所提方法的性能比传统"OR原则"硬判决合并方案要好,仅仅略逊于传统等增益软判决合并方案,但是能大量节省认知网络中的传输比特数.     

基于可信度的半双工协同频谱检测

提出了基于可信度的半双工协同频谱检测方案.该方案利用贝叶斯方法来确定协同用户的可信度,分别就具有单协同用户和多协同用户的半双工协同频谱检测进行了研究,分析了可信度对协同频谱检测的影响.分析和仿真结果表明,本文策略不但能提高检测概率、降低检测时间,还能排除故障用户对检测性能的影响、减少恶意用户的干扰.     

Spectrum sensing scheduling for group spectrum sharing in cognitive radio networks

This paper addresses the issues on spectrum sharing in a cognitive radio network consisting of a primary user and a group of cognitive users. Each cognitive user may occupy a non‐overlapped sub‐band of the primary spectrum, but it needs to perform spectrum sensing independently before accessing the sub‐band. To reduce the complexity of spectrum sensing and thus energy consumption, this paper proposes a scheduled spectrum sensing scheme. First, we consider a single spectrum sensing scenario where only one cognitive user is elected to perform spectrum sensing, and then it broadcasts its sensing results to the other cognitive users. The scheduled spectrum sensing scheme works in both network‐centric and user‐centric ways. Next, the scheduled spectrum sensing scheme is further generalized to work in a multiple spectrum sensing scenario. The results show the effectiveness of the proposed schemes compared with the traditional schemes where all cognitive users may perform spectrum sensing at the same time. Copyright © 2010 John Wiley & Sons, Ltd.     

Maximizing the lifetime of energy‐constrained cooperative spectrum sensing sensor network

Adding the cognitive capability to wireless sensor networks allows the sensors to monitor the spectrum and identify the spectrum holes to operate in different frequencies according to the radio environment which result in better spectrum utilization. Spectrum sensing is a main component in any cognitive radio network. In this paper, we propose a new cooperative sensing scheme based on energy detection for cognitive sensor networks which is constrained by the energy limitation of the wireless sensor elements. The proposed scheme minimizes the sensing energy for individual sensor and carefully selects the suitable participant sensors in each cooperative sensing process. This results in maximizing the lifetime of energy‐constrained wireless sensor networks. The proposed scheme also takes into consideration the constraints on the detection accuracy. The simulation results show that the proposed scheme prolonged the lifetime of the cognitive network, makes efficient usage of available spectrum by secondary users, and satisfy the target detection performance.     

基于POMDP的认知无线电自适应频谱感知算法

针对如何建立适合毫秒级频谱空洞场景的频谱感知机制这一问题,推导出最佳次级用户单次数据传输时间长度,解决了数据传输量最大化的问题;其次提出一种基于部分可观测马尔科夫决策过程（POMDP,partially observable Markov decision process）的自适应频谱感知算法,解决了快速接入毫秒级频谱空洞的问题。该算法根据上一决策时段的信念向量和感知结果自适应确定在当前决策时段内进行频谱感知或数据传输行为。仿真结果表明,该自适应频谱感知算法能够有效控制次级用户和主用户的冲突概率并增加频谱利用率。     

Joint sensing and transmission for cognitive amplify‐and‐forward two‐way relay networks

In this paper, we propose a cognitive transmission scheme for Amplify‐and‐Forward (AF) two‐way relay networks (TWRNs) and investigate its joint sensing and transmission performance. Specifically, we derive the overall false alarm probability, the overall detection probability, the outage probability of the cognitive TWRN over Rayleigh fading channels. Furthermore, based on these probabilities, the spectrum hole utilization efficiency of the cognitive TWRN is defined and evaluated. It is shown that smaller individual or overall false alarm probability can result in less outage probability and thus larger spectrum hole utilization efficiency for cognitive TWRN, and however produce more interference to the primary users. Interestingly, it is found that given data rate, more transmission power for the cognitive TWRN does not necessarily obtain higher spectrum hole utilization efficiency. Moreover, our results show that a maximum spectrum hole utilization efficiency can be achieved through an optimal allocation of the time slots between the spectrum sensing and data transmission phases. Finally, simulation results are provided to corroborate our proposed studies. Copyright © 2016 John Wiley & Sons, Ltd.     

Optimized channel prediction and auction-based channel allocation for personal cognitive networks

Cognitive networks are stands out as intelligent technology which evolved to enhance spectrum utilization. Secondary users are allowed to utilize the primary user's frequency bands on idling times. Identifying the idle licensed spectrum is achieved through spectrum sensing. The spectrum holes should be explored such that a suitable spectrum can be selected and allocated to the secondary users. Existing spectrum sensing and selection schemes have limitations due to interferences. Thus, an optimization algorithm based on bio-inspired improved weed optimization was presented in this research work for enhanced channel utilization. The optimization model explores the channel characteristics and reduces the primary network interferences through its optimal solution. Further, Markov greedy-based auction scheme was presented for channel allocation. Considering the channel capacity, delay, and switching rates the allocation is performed to enhance the overall system performance. Simulation analysis demonstrates the superior performance of the proposed model over existing techniques like particle swarm optimization and genetic algorithm.     

模拟人群信任和决策机制的协作频谱感知方法

通过模拟人群内部的信任和决策机制,针对多用户的频谱协作感知一致性问题,提出了一种分布式算法。该算法首先通过网络的历次协作过程预测出各感知用户的动态可信值,据此产生用户的相对可信值,并结合决策机制使得用户之间进行数据交互,随着数据的可信、迭代交互,所有用户状态将趋于一致,最后通过判定算法得出最终结果。算法充分考虑了实际环境中各用户频带感知能力的不平衡性,而且各次级用户只需要进行少量局部数据交换即可实现协作感知,与传统的OR-rule、1-out-of-N rule以及普通迭代法有较大区别。对3种数据篡改攻击进行了分析,并在预测算法的基础上提出了相应的安全策略。理论分析与仿真结果表明,新算法在准确性和安全性上均优于传统合作频谱感知算法,能显著提高频谱感知准确率,同时兼具较强的防攻击能力。