基于循环平稳的多天线渐进最优χ2检测算法

为了提高基于循环平稳感知方法的检测性能,减少深衰落对感知性能的影响,提出了一种基于多天线合并方案的频谱感知算法,即将循环自相关函数和循环谱密度函数进行一种改进的最大增益比合并,并通过渐进最优χ2检测法得出检验统计量。该种算法可以在感知信号和噪声幅值信息未知的情况下对信号的有无进行检测。为了验证提出方法的正确性,以BPSK信号为例对提出的算法进行仿真检验,仿真结果表明多天线感知算法的性能优于单天线感知,减少了深衰落对接收信号的影响。     

认知无线电及其原始用户检测

认知无线电系统必须能够及时检测到原始用户的工作状态以避免形成相互干扰,论文主要讨论用于频谱感知的信号检测理论。大部分人工合成的信号都可以看成是循环平稳随机过程,利用谱相关函数可以有效地检测这些信号,文中主要考虑用循环谱密度监测原始用户的可行性。此外,文章还对认知无线电中的协作检测法做了分析。     

认知系统中多天线协作频谱感知方案

针对认知无线电的核心问题——频谱感知,采用性能好的协作频谱感知,这里研究了认知无线电系统中一种多天线协作频谱感知方案,此方案中的噪声信号和主用户的信号均认为是独立复高斯随机信号。同时,次用户将检测到的信号通过波束成形后传向融合中心,而优化函数为发射功率受限的条件下,最大化全局的检测概率。理论推导和方针结果表明,所提出的方案有效地提高了检查概率,充分发挥了空间分集和多用户分集的优势,普遍提高了系统的感知概率。     

D-S证据理论在认知无线电中的应用

针对认知无线电（CR）中协作频谱感知时信息不确定性带来严重的性能影响,在协作开销允许的情况下,人们渴望得到感知增益很高的协作感知方案。由于D-S证据理论在决策系统中处理不确定性信息时能获得令人满意的性能,使得其在认知无线电中的应用会起很重要作用。一种基于D-S证据理论的协作频谱感知新方案被提出和发展。该方案能有效地提高...     

IEEE 802.22授权频带多周期循环检测性能分析

认知无线电使用动态频率接入,应具备自动检测无线电频谱空洞功能。基于多周期循环检测算法,研究了IEEE802.22WRAN授权用户频带的特征感知方案。其基本思想是利用周期平稳信号的自相关函数以及协方差函数特性,计算自相关值的协方差,比较估计值与门限值,判决原信号是否具有循环平稳性,从而识别出各种信号类型。仿真利用两类授权用户信号特点进行精细感知,并着重分析了循环周期长度和延时等参数对检测性能的影响。结果表明增加计算自相关函数时的循环周期长度或采样点数,降低延时,都有利于信号检测,从而验证了该算法的优良性。     

一种多天线智能谱感知方法研究

频谱感知和多天线分集合并技术是目前无线通信研究的热点.为了在复杂的信道衰落环境下实施有效的检测,融合多种检测方法是目前频谱感知技术的发展趋势.提出了一种基于匹配滤波器检测、能量检测和循环平稳检测的多天线合并智能频谱感知算法.通过建立高斯信道下二元假设检验模型,得出了总检测概率的封闭表达式.各种条件下的检测概率和检测时间的接收机工作特性(Receiver Operating Characteristic,ROC)实验结果表明所提算法优于单天线的性能,有效地利用了分集技术并减小了信号瞬时波动,保证在衰落信道条件下也能得到较高的检测概率.这对发展新型频谱感知技术,促进认知无线电技术应用具有重要意义.     

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.     

一种改进的认知无线电循环功率谱特征检测算法

通过对认知无线电频谱检测技术的研究,结合通信信号普遍存在的循环平稳特性,本文首先较为详细地阐述了循环功率谱的基本概念,随后提出了可应用于认知无线电频谱检测的基于二阶循环平稳特性的循环功率谱特征检测算法,并依据认知无线电的实际需求对检测算法进行了修正.在此基础上,以现代通信系统较为常用的QPSK调制信号进行了检测算法的仿真,并根据仿真结果对算法的有效检测性能进行了详细的分析,实际应用也验证了检测算法的可行性.     

基于循环平稳特征的频谱检测

频谱检测是实现认知无线电的前提。从认知无线电的核心功能出发,分析了循环平稳特征检测抗噪方面的性能以及影响其检测性能的主要因素,通过理论推导和仿真验证了噪声对检测性能的影响,提出了一种基于小波变换的频谱检测方案。该方案通过小波变换将接收到的信号进行主信号与噪声分离,并对信号进行重构,提高了频谱检测的性能。仿真结果表明,在低信噪比情况下,采用基于小波变换的频谱检测方法,无论是系统的频谱检测虚警率还是频谱检测漏检率都有了显著的降低。     

基于最大最小特征值之差的频谱感知技术研究

频谱感知技术是认知无线电系统的关键技术之一,该文基于阵列天线理论,利用并分析接收信号相关矩阵,并以其最大与最小特征值之差作为检验统计量,进而判断主用户是否存在,实现频谱感知。理论分析和仿真结果均表明,此方法的感知性能明显优于能量检测算法,并且有效地解决了噪声不确定度对检测性能的影响。     

Robust Nonparametric Cyclic Correlation-Based Spectrum Sensing for Cognitive Radio

Cognitive radios sense the radio spectrum in order to find underutilized spectrum and then exploit it in an agile manner. Spectrum sensing has to be performed reliably in challenging propagation environments characterized by shadowing and fading effects as well as heavy-tailed noise distributions. In this paper, a robust computationally efficient nonparametric cyclic correlation estimator based on the multivariate (spatial) sign function is proposed. Nonparametric statistics provide additional robustness against heavy-tailed noise and when the noise statistics are not fully known. Asymptotic distribution of the spatial sign cyclic correlation estimator under the null hypothesis is established. Tests using constraint on false alarm rate are derived based on the estimated spatial sign cyclic correlation for single-user and collaborative spectrum sensing by multiple secondary users. Theoretical justification for detecting cyclostationary signals using the spatial sign cyclic correlation is provided. A sequential detection scheme for reducing the average detection time is proposed. Simulation experiments and theoretical results comparing the proposed method with cyclostationary spectrum sensing methods employing the conventional cyclic correlation estimator are presented. Simulations demonstrate the reliable and highly robust performance of the proposed nonparametric spectrum sensing method in both Gaussian and non-Gaussian noise environments.     

Cyclostationarity-Based Decision Reporting Scheme for Cooperative Spectrum Sensing

Cooperative spectrum sensing has emerged as a promising solution to the hidden terminal problem in cognitive radio networks (CRNs). It could significantly promote the sensing capability of CRNs by exploiting space diversity gains in a fading environment. However, owing to the decision reporting overhead, there exists a tradeoff between the system throughput and performance of cooperative spectrum sensing. In this paper, we propose a cyclostationarity-based decision reporting scheme for cooperative spectrum sensing in CRNs with cyclic delay diversity orthogonal frequency division multiplexing (CDD-OFDM). Decision information would be embedded into the CDD-OFDM signals in terms of cyclostationary signatures and shared among cognitive radio (CR) users along with data transmissions. As a result, satisfied system throughput could be achieved without additional spectral or temporal resources consumption when the number of cooperative users increases. Numerical results are presented to show the system throughput enhancement.     

基于证据折扣优化DSmT的协同频谱感知器

协同频谱感知器通过充分利用多个认知无线电用户的空间分集增益,对抗单用户深度衰落和阴影效应问题,降低了感知系统对本地感知用户的灵敏度要求,减少由于单用户检测不确定性带来的系统误判。利用D-S方法进行协同频谱感知,通过在本地提取置信指派,再上传至融合中心进行证据推理与判决,占用较窄的控制信道带宽,达到优于传统方法的检测性能,如“或”、“与”和“最优融合”感知方法。但低信噪用户带来的冲突数据会限制D-S方法性能,使其信噪鲁棒性较差。本文首先定义感知用户基本置信指派函数,基于DSmT提出证据折扣优化 DSmT协同频谱感知器。该感知器根据不同认知用户数据的可靠性,对其置信指派函数进行折扣,加强高可靠性数据对融合结果的贡献,降低不可靠数据对融合结果的干扰,有效解决冲突数据下的协同频谱感知信息融合问题。仿真结果表明,证据折扣优化DSmT协同频谱感知器具有良好的检测性能和信噪比鲁棒性。      

Experimental detection of mobile satellite transmissions with cyclostationary features

One of the important functions of cognitive radio (CR) technology is spectrum sensing. The implementation of an efficient spectrum sensing function can be quite challenging because of various factors such as multi‐path fading, low signal‐to‐noise ratio of the radio communication services to be detected and the requirement to detect and analyze the signal in a short time. As a consequence, it is important to quantitatively assess the performance of spectrum sensing techniques in various scenarios. This paper investigates different digital signal processing techniques for spectrum sensing in the context of mobile satellite transmissions: power sensing, cyclostationary sensing, efficient cyclostationary sensing based on FFT accumulation method and strip spectral correlation algorithm. This paper presents experimental results on the cyclostationary properties of GSM Thuraya mobile satellite communications in various conditions both for the uplink and downlink channels. The receiver operating characteristics are computed, and the results are presented for different algorithms and different positions of the satellite terminals. The experimental results show that the cyclostationary‐feature‐based detection can be robust compared to energy‐based technique for low signal‐to‐noise ratio levels. Copyright © 2014 John Wiley & Sons, Ltd.     

Maritime cognitive radio spectrum sensing based on multi-antenna cyclostationary feature detection

ABSTRACT

With the development of the maritime transportation industry, the number of ships is increasing and the ships are becoming more intelligent. Due to the rapid development of maritime communication, the demand for communication spectrum is increasing. Therefore, the maritime cognitive radio (CR) system is an effective solution. Because of the multipath fading caused by sea surface and atmosphere has a more serious influence on communication signals, which increases the instability of the signal reception, the spectrum sensing technology in maritime cognitive radio is more challenging than the spectrum sensing on land. In order to solve this problem, a cyclostationary detection algorithm for multiple antennas in fading model is proposed. A maximum ratio combining algorithm based on optimal weight correlation value (OWCV-MRC) is proposed for the diversity gain and system performance degradation caused by diversity technology on multipath fading channels. The algorithm uses the correlation values of the attenuation gains on the two different branches as the weighting coefficients of each branch, thus improving the coefficient matrix in the maximum ratio combining (MRC) algorithm. The simulation results show that the proposed algorithm can effectively detect the target signal in the fading channel with ultra-low signal to noise ratio (SNR).     

Collaborative Cyclostationary Spectrum Sensing for Cognitive Radio Systems

This paper proposes an energy efficient collaborative cyclostationary spectrum sensing approach for cognitive radio systems. An existing statistical hypothesis test for the presence of cyclostationarity is extended to multiple cyclic frequencies and its asymptotic distributions are established. Collaborative test statistics are proposed for the fusion of local test statistics of the secondary users, and a censoring technique in which only informative test statistics are transmitted to the fusion center (FC) during the collaborative detection is further proposed for improving energy efficiency in mobile applications. Moreover, a technique for numerical approximation of the asymptotic distribution of the censored FC test statistic is proposed. The proposed tests are nonparametric in the sense that no assumptions on data or noise distributions are required. In addition, the tests allow dichotomizing between the desired signal and interference. Simulation experiments are provided that show the benefits of the proposed cyclostationary approach compared to energy detection, the importance of collaboration among spatially displaced secondary users for overcoming shadowing and fading effects, as well as the reliable performance of the proposed algorithms even in very low signal-to-noise ratio (SNR) regimes and under strict communication rate constraints for collaboration overhead.     

Cyclostationary Signatures in Practical Cognitive Radio Applications

We define a cyclostationary signature as a feature which may be intentionally embedded in a digital communications signal, detected through cyclostationary analysis and used as a unique identifier. The purpose of this paper is to demonstrate how cyclostationary signatures can be exploited to overcome a number of the challenges associated with network coordination in emerging cognitive radio applications and spectrum sharing regimes. In particular we show their uses for signal detection, network identification and rendezvous and discuss these in the context of dynamic spectrum access. We present a theoretical discussion followed by application-oriented examples of the cyclostationary signatures used in practical cognitive radio and dynamic spectrum usage scenarios. We focus on orthogonal frequency division multiplexing (OFDM) based systems and present an analysis of a transceiver implementation employing these techniques developed on a cognitive radio test platform.