报告信道传输错误环境下协作感知最优用户数分析

认知无线电网络中多个用户相互协作进行频谱感知能有效提高系统的感知性能,然而当各用户将本地感知信息经无线信道发送至中心控制器时,若因信道衰减等因素出现传输错误又会降低系统性能。该文针对这种网络环境,探索了参与协作的用户数目与系统感知性能的关系,并从授权/认知用户两个角度分别讨论协作感知最优用户数的计算方法。理论分析与仿真结果表明:网络中所有用户均参与协作不一定能获取最优性能;当选取具有较高感知信噪比条件的一定数目的用户进行协作反倒能实现最优,并且该最优用户数与网络的规模成正比,与报告信道传输错误概率成反比。      

基于中继协作的认知无线电性能研究

频谱感知是认知无线电技术的关键。协作频谱感知能够充分利用网络资源,提高网络中认知用户的检测概率,降低认知用户的虚警概率。基于两个认知用户之间的中继协作,研究了协作频谱感知的感知性能与吞吐量的折衷。仿真结果表明：中继协作的频谱感知方法能够使得在充分保证对授权用户不造成干扰即检测概率一定时,能够有效地降低认知用户感知授权用户的虚警概率,缩短＂弱＂认知用户获得最大吞吐量的最优感知时间,提高其最大吞吐量,并提高认知系统的最大吞吐量。     

随机共振在认知无线电频谱感知中应用的最新研究进展

频谱感知是认知无线电网络的一项关键技术.低信噪比(SNR)环境下频谱检测的性能会大幅降低,而随机共振(SR)能有效提高信号信噪比,所以将其应用到频谱感知中,能增强认知用户对主用户(PU)的检测性能.首先介绍了随机共振在认知无线电频谱感知中应用的最新研究进展,包括随机共振在本地感知中(如能量检测、协方差矩阵频谱感知、循环平稳特征检测)及协作感知中的应用,然后指出了随机共振在认知无线电频谱感知中还有待解决的问题,并提出了下一步的研究方向.     

基于能量和协方差的两步频谱感知

频谱感知是认知无线电中的一项关键技术,主要功能是能够快速准确检测出频谱中是否存在授权用户。频谱感知的能量检测算法简单,但在低信噪比情形下的检测性能不佳,而协方差算法在低信噪比环境下具有较好检测性能。针对上述情况提出了一种这两步相结合检测的算法,从而具有更准确的频谱感知性。仿真结果表明,两步检测算法在低信噪比情况下无需授权用户的先验信息,同时使算法的平均计算量相对于协方差算法有一定程度的降低,并能有效地提高频谱感知性能。     

基于解码转发的协作频谱感知技术

频谱感知技术中的单点检测设计复杂度低,采用技术成熟,易于实现,但是由于自身的局限性,面临着隐藏终端,感知灵敏度底等问题,而协作分集技术可以克服这些问题。基于解码转发(DF,DecodeAnd Forward)的协作频谱感知技术,利用了分集增益原理,提高了认知用户的单点检测概率,从而改善了整个无线电系统的性能。在瑞利衰落环境下对该检测方案进行分析,并通过与非协作检测的性能比较,说明了协作检测的优势。     

认知无线电网络的一种协作频谱感知方案

认知无线电技术能够让非授权用户利用已经分配给授权用户的频段.为了不对首要用户的工作造成干扰,认知用户需要对频谱进行不间断的监测来判断首要用户是否存在.因此,频谱的感知是认知无线电技术的关键.协作频谱感知能够充分的利用网络资源,提高网络中的认知用户的检测概率.文中笔者简单地介绍了一种协作频谱感知的方案.仿真结果表明,通过该方法能够提高网络中认知用户的检测概率,提高网络的检测灵敏度.     

认知无线电最优线性协作宽带频谱感知

本文提出了基于最优线性协作的宽带频谱感知方案。通过次级用户之间的协作,为认知网络的频谱感知提供分集,利用融合中心融合多个次级用户的宽带频谱感知数据来获取最优权重,并生成全局判决统计量,最终使用全局阈值完成最后的检测判决。由于所提出的两种协作宽带感知方案或需要精确地估计授权用户的信号强度和噪声方差,或感知性能不足,因而,还提出一种更易实现的方案。理论分析和仿真结果表明,本文所提出的协作感知方案可以有效地提高频谱感知性能,并且性能优于传统等增益合并方案。      

认知无线电中协作压缩频谱感知算法

针对宽带频谱认知无线电环境中,传统能量检测法在信噪比较低时,容易出现误检而使系统的检测性能下降的问题,文中提出了一种新型高性能的协作频谱感知算法,它是基于压缩理论的多节点频谱感知方法,各节点之间采用基于双判决门限的协作方式。仿真结果显示,双门限协作压缩频谱感知算法在低信噪比的情况下,检测性能明显优于传统能量检测法。     

基于最佳中继选择的协作频谱感知方案研究

 本文提出了一种基于最佳中继的多用户协作频谱感知方案,通过认知无线电网络中多用户间的相互协作,可以获得明显的空间分集增益,从而改善认知用户的检测性能．针对所提出的多用户协作感知方案,在瑞利衰落环境下分析了相应的系统检测概率,同时也理论推导了传统非协作方案的感知性能．根据检测概率的解析式,对非协作方案和多用户协作方案,进行了相应的数值实验和性能比较．与非协作感知方案相比,多用户协作方案能够显著提高主用户的检测概率．此外,随着候选中继用户数目增加,多用户协作方案对主用户检测概率的改善量越加明显．     

基于统计可信度的压缩感知协作频谱检测算法

压缩感知为认知无线电的宽频谱感知提供了一种新的方法和思路。基于压缩感知的原理,提出了一种多认知用户协作场景下基于用户统计可信度的协作频谱检测算法。该算法使用正交匹配协作追踪算法获得认知区域内的频谱占用情况,根据不同认知用户频谱检测的历史准确度综合判定用户感知结果的统计可信度。仿真结果表明,该算法在不同用户数、不同采样值、不同信噪比变化范围下其检测性能均优于传统算术平均方法,有效改善了检测性能。     

Spatiotemporal Sensing in Cognitive Radio Networks

Cognitive radio networks need to continuously monitor spectrum to detect the presence of the licensed users. In this paper, we have exploited spatial diversity in multiuser networks to improve the spectrum sensing capabilities of centralized cognitive radio (CR) networks. We develop a fixed and a variable relay sensing scheme. The fixed relay scheme employs a relay that has a fixed location to help the cognitive network base station detect the presence of the primary user. The variable relay sensing scheme employs cognitive users distributed at various locations as relays to sense data and to improve the detection capabilities. This effectively reduces the average detection time by exploiting spatial diversity inherent in multiuser networks. Finally, we study the network outage probabilities to compare the performances of the fixed and variable relay schemes.     

Reinforcement learning for cooperative sensing gain in cognitive radio ad hoc networks

Spectrum sensing is a fundamental function in cognitive radio networks for detecting the presence of primary users in licensed bands. The detection performance may be considerably compromised due to multipath fading and shadowing. To resolve this issue, cooperative sensing is an effective approach to combat channel impairments by cooperation of secondary users. This approach, however, incurs overhead such as delay for reporting local decisions and the increase of control traffic. In this paper, a reinforcement learning-based cooperative sensing (RLCS) method is proposed to address the cooperation overhead problem and improve cooperative gain in cognitive radio ad hoc networks. The proposed algorithm is proven to converge and capable of (1) finding the optimal set of cooperating neighbors with minimum control traffic, (2) minimizings the overall cooperative sensing delay, (3) selecting independent users for cooperation under correlated shadowing, and (4) excluding unreliable users and data from cooperation. Simulation results show that the RLCS method reduces the overhead of cooperative sensing while effectively improving the detection performance to combat correlated shadowing. Moreover, it adapts to environmental change and maintains comparable performance under the impact of primary user activity, user movement, user reliability, and control channel fading.     

协作频谱感知在认知网络中的应用

认知无线电能够灵敏感知周围环境的变化,通过频谱感知功能发现频谱空洞,使得认知无线电能够与周围通信环境相适应。在认知无线电网络中,认知用户（次用户）必须连续地监控频谱,检测主用户是否存在。如果主用户存在,次用户必须尽快地退出该频段,从而不影响主用户。在文中采用一种协作机制,即两用户进行协作频谱感知,从而提高主用户的检测率,减少了检测时间,并且得到捷变增益。我们用Matlab给出仿真结果。     

基于可靠次用户信息的协作频谱感知算法研究

对认知无线电系统最基本要求之一就是次用户必须有能力以高的精确率来确定主用户是否存在。而以前对认知无线电频谱感知的研究表明:在实际认知网络中次用户之间的相互协作可以提高其频谱检测性能。然而,对于协作频谱感知而言,随着协作次用户数目的增加,势必会增大用于传输本地检测结果到融合中心的专用控制信道带宽,从而增加系统开销。该文在控制信道带宽有限的约束条件下,提出一种通过考虑可靠次用户信息的协作频谱感知算法来进一步改善频谱检测的性能。该算法的基本思想:只有具有可靠的本地检测结果的次用户才发送自己的检测结果到融合中心,否则,该次用户不发送任何信息。同时,对提出的该算法在理论上进行了推导,通过仿真结果表明:在控制信道带宽受限的约束下,相比于传统的或门协作频谱感知算法,提出的算法能够大大改善对主用户的检测性能。     

多天线感知无线电中的协作频谱感知算法

不同于以往单天线感知用户的频谱感知研究,该文提出多天线情形下基于最优功率分配和协作分集的频谱感知算法。根据信道条件利用奇异值分解(SVD)在每根天线上进行功率注水,并考虑多天线情况下两用户网络协作频谱感知授权用户的判决检测过程,利用基于指数衰减的路径损耗模型,分析多天线感知网络的各态历经容量和检测授权用户的概率及时间。理论分析及仿真结果表明,多天线感知用户通过最优功率分配和协作频谱感知不仅使感知网络具有最大的各态历经容量,同时改善系统的检测性能。     

Cooperative relay to improve diversity in cognitive radio networks

Recent studies demonstrated that dynamic spectrum access can improve spectrum utilization significantly by allowing secondary unlicensed users to dynamically share the spectrum that is not used by the primary licensed users. Cognitive radio was proposed to promote the spectrum utilization by opportunistically exploiting the existence of spectrum ?holes.? Meanwhile, cooperative relay technology is regarded widely as a key technology for increasing transmission diversity gain in various types of wireless networks, including cognitive radio networks. In this article, we first give a brief overview of the envisioned applications of: cooperative relay technology to CRNs, cooperative transmission of primary traffic by secondary users, cooperative transmission between secondary nodes to improve spatial diversity, and cooperative relay between secondary nodes to improve spectrum diversity. As the latter is a new direction, in this article we focus on this scenario and investigate a simple wireless network, where a spectrum-rich node is selected as the relay node to improve the performance between the source and the destination. With the introduction of cooperative relay, many unique problems should be considered, especially the issue for relay selection and spectrum allocation. To demonstrate the feasibility and performance of cooperative relay for cognitive radio, a new MAC protocol was proposed and implemented in a universal software radio peripheral-based testbed. Experimental results show that the throughput of the whole system is greatly increased by exploiting the benefit of cooperative relay.     

Analysis and Optimization of Sensing Reliability for Relay-Based Dual-Stage Collaborative Spectrum Sensing in Cognitive Radio Networks

Aiming at multiuser cognitive radio networks in a harsh electromagnetic environment, cooperative spectrum sensing with single cooperation can hardly achieve to the desired detection performance. In this paper, a relay-based dual-stage collaborative spectrum sensing model (DCSS) that combines the distributed method with the centralized method is proposed. Furthermore, the optimality of the detection performance of DCSS is investigated in an efficient and feasible way. The optimal voting rule value and the optimal energy detection threshold are also derived by minimizing the detection error rate of the entire network. Finally, an efficient fast sensing algorithm for a large-scale cognitive radio network is deduced, which requires the minimal number, and not all, of cognitive radio users for DCSS while satisfying the target detection error rate bound. The simulated results indicate that when compared to the normal single cooperation method, the optimized DCSS method can reduce the number of cognitive radio user by 65 % while still meeting the detection error rate requirement of less than 1 %.     

Femtocell网络中基于双门限的两层协作频谱感知技术

在Femtocell和Macrocell构成的两层异构网络中,前人提出运用认知无线电的技术来解决网络中存在的干扰问题,但大多数研究主要集中在频谱资源的管理上,没有提出高效的频谱检测方法。本文结合认知无线电中频谱感知技术提出了基于双门限的两层协作频谱感知,检测出空洞的频谱资源分配给Femtocell用户使用,既能提高频谱资源的利用率,又能有效的抑制Femtocell与Macrocell之间的干扰。文中推导出了Femtocell用户基于双门限的两层频谱感知的检测概率和虚警概率,给出了Femtocell网络中感知信息两比特编码的融合准则和基于双门限的两层协作频谱感知的具体实施方法。仿真结果表明,所提算法能够有效提高Femtocell用户的频谱检测概率,通过对感知信息进行两比特编码,再将编码后的信息发送至融合中心进行融合,能够有效的提高整个系统的检测性能,抗噪声能力强。      

基于强化学习的合作频谱分配算法

为了解决认知无线电网络中的频谱分配问题,提出了一种基于用户体验质量的合作强化学习频谱分配算法,将认知网络中的次用户模拟为强化学习中的智能体,并在次用户间引入合作机制,新加入用户可以吸收借鉴其他用户的强化学习经验,能够以更快的速度获得最佳的频谱分配方案;并且在频谱分配过程中引入了主用户和次用户之间的价格博弈因素,允许主用...