多径信道下MIMO系统发送天线数估计

为了解决认知无线电或信号截获中多径信道下MIMO系统发送天线数估计问题,首先分析了现有模型在多径信道下失效的原因,将MIMO多径信道模型等效变换出一种虚拟信道矩阵,从而建立多径信道下MIMO系统发送天线数估计模型;然后,利用随机矩阵理论中协方差矩阵最小特征值分布的相关研究结果,证明了时不变瑞利信道的协方差矩阵最小特征值收敛于第二类Tracy-Widom分布,分析了该特点对发送天线数估计的影响,并提出一种改进的RMT估计算法来估计多径信道下MIMO系统发送天线数.最后对改进算法进行了仿真验证,结果表明在低信噪比和小数据条件下,改进算法的估计性能相比RMT算法有较大提升.     

认知无线网络中基于Cholesky分解的统计协方差频谱检测算法

针对认知无线网络中协方差检测算法均通过渐进方法得到性能参数的缺点,提出了改进的cholesky的协方差盲检测算法,利用RMT(random matrix theory)理论,推导了非渐进条件下该算法性能参数的数学表达式。所提算法无需PU信号的先验信息和信道条件信息,对不确定噪声具有很强的适应能力。理论分析和仿真证明,性能参数表达式正确,所提算法相对于其他协方差盲检测算法,性能有了一定的提升。     

基于随机矩阵理论的频谱感知技术研究综述

认知无线电技术,可以提高频谱资源的利用率,应用前景广阔,极有可能引发无线通信领域的又一次重大变革。但频谱感知作为认知无线电技术的首要环节,其性能还远不能满足实际需要。研究出一种真正能够实际应用的高性能频谱感知方法已经成为一个亟待解决的问题。近年来,与无线通信领域密切相关的新理论——随机矩阵理论（RMT）,在频谱感知领域得到了进一步的应用,实现了高性能频谱感知。且RMT最新研究成果——非渐近随机矩阵理论（Non-Asymptotic RMT）有望将这项高性能感知技术真正推向实际应用。因此,基于随机矩阵理论的频谱感知技术具有重要的研究价值。本文总结RMT在认知无线电频谱感知领域的发展历程、介绍其基本原理、归纳其主要特点,并展望进一步研究的方向。      

基于随机矩阵理论的非重构宽带压缩频谱感知方法

该文采用随机矩阵理论(RMT)直接对压缩采样得到的观测数据进行分析,设计出了一种基于广义似然比检验(GLRT)的非重构宽带压缩频谱感知新算法。该算法无需任何先验知识就能对宽带频谱中的每个子带进行盲检测。此外,为了减轻次用户(SU)在数据获取和频谱感知过程中的通信开销,该文提出一种基于传感器节点(SN)辅助感知的合作频谱感知架构。理论分析和仿真结果均表明,与传统基于信号重构的GLRT感知算法以及Roy最大根检测(RLRT)算法相比,该算法不仅具有计算复杂度低、开销小、感知性能稳定等诸多优点;而且只需较少的SN就能获得较好的检测性能。     

基于矢量奇异值分解的DOA估计方法及其改进

对相干信号的波达方向（DOA）估计是空间超分辨谱估计的热点。在均匀线性阵列模型下,特征矢量奇异值分解法（ESVD）能够很好的对相干信号进行DOA估计,但是当相干信号和非相关信号同时存在时,ESVD并不能对全部信号进行DOA的估计。本文通过对ESVD算法的理论分析后,选取经过加权处理的特征向量来构造新矩阵,再利用奇异值分解得到信号的噪声和信号子空间,从而进行DOA估计。理论分析和计算机仿真表明该改进算法(MESVD)解决了ESVD算法在相干信号和不相关信号同时存在不能正确进行DOA估计的问题,估计精度与空间平滑算法（FBSS）相当。     

压缩传感技术及其应用

本文综述了一种新的信号处理方法—压缩传感（Compressive Sensing ,CS）,它是针对稀疏或者可压缩信号,在采样的同时即可对信号数据进行适当压缩的新理论。近年来,压缩传感理论成为信号采样及图像处理领域最新、最热点的问题之一。它主要包括三个方面：稀疏表示矩阵,非相干测量矩阵以及重建算法。本文介绍了压缩传感理论的模型,以及压缩传感的主要重建算法,并将实现方法进行了分析与比较。文章最后列举出了压缩传感的主要应用领域。     

认知无线电中基于SVD分解的频谱感知新算法

为了解决认知无线电中能量检测法在低信噪比下检测概率低的问题,本文提出了一种基于SVD分解的频谱感知算法。首先利用接收信号构造Hankel矩阵,通过SVD分解,将矩阵分离成信号空间与噪声空间,再将较小的奇异值置零,然后重构矩阵,从而提高接收信号的信噪比（SNR）。其次,将SVD系统输出信号功率对噪声功率进行归一化,把降低噪声功率转化成提高主用户信号功率。最后进行能量检测,以此来提高检测概率。理论分析和计算机仿真表明,在相同条件下,基于SVD分解的频谱感知算法与传统的能量检测法相比,检测概率显著提高;要达到相同的检测概率,对信噪比的要求也显著降低。      

基于随机矩阵理论的DET合作频谱感知算法

针对认知无线电系统中的频谱感知问题,该文采用随机矩阵理论(Random Matrix Theory, RMT)对多认知用户(Secondary User, SU)接收信号采样协方差矩阵的最大特征值的分布特性进行了分析和研究,提出了一种新的基于双特征值判决门限(Double Eigenvalue Threshold, DET)的合作频谱感知算法。由该算法感知性能的理论分析可知:DET合作感知算法无需主用户(Primary User, PU)发射机信号的先验知识,也不需要预先知道信道背景噪声功率。仿真结果表明,与传统的频谱感知方法相比,该方法只需较少的认知用户就能获得较高的感知性能,并且对噪声的不确定性具有较强的鲁棒性。     

基于压缩感知的分数阶Fourier 域LFM 信号检测

提出一种新的基于压缩感知CS（Compressed Sensing）理论的LFM 信号检测算法。利用LFM 信号在分数阶 Fourier 变换（Fractional Fourier Transform,FrFT）域稀疏的特点,构造FrFT 矩阵作为LFM 信号的稀疏变换基,通过少量待检测 LFM 信号的随机投影,求解信号在FrFT 域的系数向量,然后对该系数向量进行检测判决,进而达到对感兴趣信号检测的目 的。理论分析和仿真实验表明,随机投影点数低至奈奎斯特采样点数的1/10、信噪比低至-8 dB 时,该算法对感兴趣的LFM 信号检测的成功率可达到95%以上,并且对强窄带干扰不敏感;与波形一致算法相比,该算法在相同信噪比条件下,可以获得 更高的信号检测概率。     

基于矩阵理论的微弱通信信号数据融合算法研究

通信试验中的背景信号日益复杂,微弱通信信号的数据融合是通信试验中信号检测的关键技术之一。针对试验中对微弱通信信号检测难度大的问题,提出了一种基于矩阵理论的通信信号数据融合算法,对算法的性能进行了仿真,仿真结果表明,基于矩阵理论融合算法能明显提高同信噪比条件下的微弱信号的检测概率。     

A Multipath Detection Scheme for CDMA Systems With Space–Time Spreading

Space-time spreading (STS) is an appealing open-loop transmit diversity scheme, which has recently been included into the cdma2000 standard. It has been shown that the performance of the STS scheme is highly sensitive to fading coefficient estimation errors, particularly when the channel is highly time dispersive. In practical systems, channel estimation is normally performed after the multipath components are resolved, which suggests that improving multipath detection reduces such estimation errors. Motivated by this, we address, in this paper, the problem of multipath detection in STS-based code division multiple access (CDMA) systems. We first extend the conventional energy-based multipath detection scheme (EMDS) to cope with the spatial channel structure. We derive approximate expressions for the probability of detection and probability of false alarm. It is shown that the errors produced by the conventional scheme in detecting the potential multipath components severely impact the performance of the receiver. To improve upon the EMDS, we introduce and analyze an improved multipath detection scheme (IMDS) based on the estimation of the interference power in the individual resolved multipath components. The efficacy of the proposed scheme stems from the fact that the interference in each potential path is estimated and subtracted before that path is detected. We also present a simple and realizable version of the proposed IMDS detection scheme. Our results show that the proposed scheme not only improves the bit-error-rate performance significantly but also utilizes the pilot power much more efficiently.     

Cooperative MIMO spectrum sensing based on random matrix theory

Random Matrix Theory (RMT) is a valuable tool for describing the asymptotic behavior of multiple systems, especially for large matrices. In this paper, using asymptotic random matrix theory, a new cooperative Multiple-Input Multiple-Output (MIMO) scheme for spectrum sensing is proposed, which shows how asymptotic free property of random matrices and the property of Wishart distribution can be used to assist spectrum sensing for Cognitive Radios (CRs). Simulations over Rayleigh fading and AWGN channels demonstrate the proposed scheme has better detection performance compared with the energy detection techniques even in the case of a small sample of observations.     

无线宽带通信系统的上行带宽资源分配方案

提出了一种适用于宽带无线通信系统的上行无线带宽资源分配方案。在详细描述算法的基础上，建立了对应的仿真系统对算法进行验证。该方案较好地解决了多业务并发时的上行带宽分配问题。兼顾了不同实时业务对时延和带宽的不同需求，与传统技术相比较，提高了带宽利用率，并减少了协议开销和传输时延。     

Matrix Coded Modulation: A New Non-coherent MIMO Scheme

This paper describes a new space-time coding scheme for non-coherent multi-antenna Multi-Input Multi-Output (MIMO) systems. This new MIMO scheme merges error-correcting and space-time coding functions by transmitting invertible matrices, so this scheme has been called “Matrix Coded Modulation” or “MCM”. Coherent systems require Channel State Information (CSI) at the transmitters and/or at the receivers, and their performances strongly depend on the channel estimation. For example, in systems using Orthogonal Frequency Division Multiplexing, the channel estimation requires the insertion of pilot-symbols in the transmitted frame which implies a spectral efficiency loss of the global system that increase with the number of transmit antennas. The existing non-coherent schemes such as the Differential Space-Time Modulation leads to performance degradation compared to coherent systems in which perfect CSI is assumed. Decoding in the MCM scheme is performed iteratively, based on a specified detection criteria. In the proposed MCM scheme, decoding can be achieved with or without CSI at the receiving antennas. As the space-time coding function is merged with the error-correcting code, the euclidean distances distribution between modulated signals based on the detection criteria is strongly linked to the Hamming weights distribution of the channel error-correcting code used in the MCM scheme. Moreover, a low-complexity decoding algorithm is described and compared to the existing differential schemes.     

Matrix Coded Modulation: A New Non-coherent MIMO Scheme

This paper describes a new space-time coding scheme for non-coherent multi-antenna multi-input multi-output (MIMO) systems. This new MIMO scheme merges error-correcting and space-time coding functions by transmitting invertible matrices, so this scheme has been called “Matrix Coded Modulation” or “MCM”. Coherent systems require channel state information (CSI) at the transmitters and/or at the receivers, and their performances strongly depend on the channel estimation. For example, in systems using Orthogonal frequency division multiplexing, the channel estimation requires the insertion of pilot-symbols in the transmitted frame which implies a spectral efficiency loss of the global system that increase with the number of transmit antennas. The existing non-coherent schemes such as the differential space-time modulation leads to performance degradation compared to coherent systems in which perfect CSI is assumed. Decoding in the MCM scheme is performed iteratively, based on a specified detection criteria. In the proposed MCM scheme, decoding can be achieved with or without CSI at the receiving antennas. As the space-time coding function is merged with the error-correcting code, the euclidean distances distribution between modulated signals based on the detection criteria is strongly linked to the Hamming weights distribution of the channel error-correcting code used in the MCM scheme. Moreover, a low-complexity decoding algorithm is described and compared to the existing differential schemes.     

一种改进的MC-CDMA系统ORC技术

基于对频率非选择性Rayleigh衰落信道中采用ORC(orthogonality restoring combining)技术的MC-CDMA系统误码率下边界的分析,提出了忽略最弱子载波(信道衰减系数最小的子载波)的改进ORC检测方案。仿真结果表明,该方案比传统ORC在性能上有很大提高,比较接近MMSEC技术;如果忽略过多的弱子载波反而会影响用户间扩频码的正交性,引起系统性能恶化。改进方案具有随子载波数线性增长的运算复杂度,是一种比较实用的MC-CDMA系统检测技术。     

Access protocol performance for on-board processing business satellite systems

This paper presents protocols for use in efficient accessing of multi-service business satellite systems. A new reservation TDMA scheme with free slots contention is proposed as being particularly suitable. The new access protocol is simulated using a numerical Petri-net model and results are given for variations in numbers of earth-stations, traffic mixes, balanced-to-unbalanced traffic, reservation scheme and free slots contention. Finally an analytical derivation is presented for the protocol performance which agrees well with simulation.     

MIMO系统中格点减少检测算法的探讨

相对于传统的单天线系统,M IMO(多输入多输出)技术能够大大提高频谱的利用率,因而被认为是新一代移动通信系统的关键技术。格点减少算法从一个全新的角度解决了多输出信号的检测问题,具有良好的发展前景。文中简要介绍了格点减少算法的数学原理,详细介绍了格点减少算法在M IMO信号检测中的应用,并在分析其性能和计算复杂度的基础上,比较了格点减少算法与其他检测算法的差异。     

基于自适应滑动窗的模糊场景行人快速检测

智能场景监控是公共安全领域研究的热点.然而当前公共场所监控视频大都比较模糊,如何能够在模糊场景下快速检测行人目标是一个亟待解决的问题.通过引入一个自适应尺寸的行人检测窗,以特定策略滑动扫描前景二值图像,并根据一系列行人轮廓判别条件获取行人目标,实现了对模糊监控场景的实时行人检测与人数统计.实验结果表明,与传统算法相比,该算法可以有效快速地检测出指定区域内的行人目标.     

V-BLAST的并行译码

移动通信系统研究的热点之一是提高系统容量.因此,空时码技术因其可在衰落环境下提供高质量的信号,进而提高系统容量而在无线通信中得到了广泛的研究.最近几年,对空时码中的一个重要分支——垂直-贝尔实验室分层空时码(V-BLAST)的研究已经有很多.然而,传统的V-BLAST算法由于需要进行大量的线性迫零和串行符号删除等运算,时延很大.而且发射天线数越多,时延也就越大.针对上述问题,本文提出了一种新的基于线性迫零和并行符号删除的检测算法.其优点是时延小且结构简单.对于新的译码方案我们在COSSAP中平坦瑞利信道下进行了仿真,仿真结果显示了基于并行符号删除的新方案的误码率(BER)性能.