基于LabVIEW的软件无线电调制制式的自动识别

在软件无线电的基础上,用软件LabVIEW的方式实现通信信号非实时的自动识别。调制制式的自动识别是非合作通信系统接收机设计的重要研究课题。利用特征参数研究了软件无线电中常用调制制式信号的自动识别,并基于决策树识别方案,对叠加了高斯白噪声的通信信号用LabVIEW编制了自动识别模块,仿真结果表明该算法具有较为理想的识别效果。     

一种FSK反正切差分解调方法

针对频移键控在通信系统应用中其调制解调技术在一定程度上直接影响通信系统的性能,提出了一种FSK数字解调方法,称作反正切差分解调.该方法基于正交反正切算法,正交信号直接相除消除了幅度调制成分.新的方法适用于窄带和宽带的FSK信号并适合于数字接收机.仿真结果表明,该技术能有效解调FSK信号,并适合于多种制式的FSK信号.     

多天线超宽带通信中的一种盲接收机

针对多天线冲激无线电超宽带通信系统,提出了一种盲的线性接收机。在不需要信道信息的情况下,可以利用经过预编码的空时分组码给接收信号带来的特定结构,直接得到接收机系数,从而恢复出发送符号。仿真表明,随着用于估计的数据块的增加,盲接收机的性能逐渐接近于相关接收。     

基于信道化架构的宽带I/Q不平衡校准技术

零中频接收机凭借其架构简单、易于集成等特点已被广泛应用于通信系统和雷达系统,为未来雷达通信一体化技术发展奠定了基础。然而,零中频接收机存在I/Q不平衡问题,这不仅会造成通信星座图的偏移,还会引入雷达虚假目标。现有宽带I/Q补偿方法的精度不高,且都集中于后处理,无法做到实时。因此,本文首先建立了宽带I/Q不平衡模型,并提出了一种融合信道化架构和盲估计补偿算法的宽带I/Q失衡校准技术。该技术利用信道化架构将宽带信号划分为窄带信号,并利用盲估计算法对带有镜像信号的子信道进行在线补偿。实验表明,该方法在获得高精度补偿参数的同时,完成了对宽带I/Q失衡的实时补偿。镜像抑制比达到55 dB。     

基于小波分析的调制识别技术研究

通信信号的调制制式自动识别是信号智能化分析及处理中的关键问题。该项技术目前正广泛应用于军事、民用、商业和气象等众多领域。针对非稳定、大信噪比变化的通信信号,运用小波分析技术进行了有效的特征提取和分类,能够实现通信信号基本调制制式的自动识别,并且使识别正确率得到了明显提高。     

一种高灵敏度TD-LTE 通信接收机设计

TD-LTE接入方式、可变大带宽等新技术的运用,对测试仪表接收端性能提出了很高的要求,特别是如何在大带宽下提高接收灵敏度成为设计重点和难点。基于本振馈通抵消技术,设计了一种高灵敏度TD-LTE通信接收机,降低了本振信号馈通,避免了本振馈通引起的杂散、噪声等问题,从而提升了接收机的灵敏度和动态范围。对接收机的测试和理论对比表明,该接收机具有结构简单、易仿真、高指标等特点,可以推广到各种通信制式的测试设备、基站等产品中,具有广泛应用前景。     

TD-LTE基站接收机中镜像抑制滤波器的研究和设计

在TD-LTE基站中,接收机对射频信号中镜像频率的抑制十分重要,在很大程度上是衡量基站接收机性能优越性的重要指标。为了消除TD-LTE基站接收机中的镜像频率,需要在混频器前设计一个抗镜像滤波器。该文提出一种超高频(3GHz~30GHz)LC型镜像抑制滤波器,通过其独特的结构设计来满足TD-LTE基站接收机镜像频率的抑制要求,具有良好的一致性。可以推广到多种通信制式的测试设备、基站等产品中,具有广泛的应用前景。     

同频同调制信号的瑞利信道系统仿真设计

为了解决通信系统仿真模型的不完备性,利用Matlab的组件Simulink搭建了一套模拟信号的传输、接收、分离的接收机通信仿真模型。该模型以同频同调制信号为信源,选取多径瑞利衰落信道模拟仿真实际接收机的工作流程,并且包括信源模块、调制解调模块、信道模块、模拟接收模块、采样滤波模块、信号分离模块等。此外,系统测试了瑞利信道的路径增益对信号盲分离的影响,仿真结果表明信道增益越大,信号越集中,分离效果也相对较好。因此,该仿真系统可以与硬件系统原型相结合,为测试信号提供功能验证,为实际接收机系统运行环境提供参考建议。     

软件无线电在反潜技术中的研究

针对通信领域近些年广泛研究和应用的软件无线电技术,为了实现反潜水声信号处理机的数字化,结合浮标接收信号和通信的特点,提出软件无线电应用在声纳接收机中的假设,并给出软件无线电技术在反潜接收机中应用的相关技术。该技术特点是实现信号处理的数字化,降低误差,提高处理效率。     

基于峭度的盲分离在通信信号盲侦察中的应用

为实现复杂多信号环境下的通信信号侦察,采用一种新的盲侦察技术,即运用盲源分离算法,在没有任何先验知识的情况下分离出源信号,然后对分离的各个信号进行后续处理。提出一种改进的基于峭度的盲分离算法,可以自适应地确定激活函数。将其应用在通信信号盲侦察中,可以实现对任意源信号进行盲分离,而不管它是超高斯还是亚高斯信号。选择超高斯和亚高斯混合通信信号进行了仿真实验,结果验证了该算法的有效性。     

Combined multiuser signal classification and blind equalization

A multiuser automatic modulation classifier (MAMC) is an important signal processing component of a multiantenna cognitive radio (CR) receiver that helps the radio in identifying modulation format employed by multiple users in a frequency band simultaneously. In a typical wireless communication, transmitted signals are subjected to multipath fading and interference from other users. Multipath fading not only affects symbol detection performance but also affects the performance of the automatic modulation classifier. A multi input multi output (MIMO) blind equalizer is another important component of a multiantenna CR receiver that improves symbol detection performance by reducing inter symbol interference and inter user interference. In a CR scenario it is preferable to consider the performance of the AMC also while adapting the parameters of the blind equalizer. In this paper we propose MIMO blind equalizers that improves the performance of both multiuser symbol detection and cumulants based MAMC. Computer simulations are provided to illustrate this concept and the proposed algorithm.     

PARAFAC-based unified tensor modeling for wireless communication systems with application to blind multiuser equalization

In some antenna array-based wireless communication systems the received signal is multidimensional and can be treated as a tensor (3D array) instead of a matrix (2D array). In this paper, we make use of a generalized tensor decomposition known as constrained Block-PARAFAC and propose a tensor (3D) model for the signal received by three types of wireless communication systems. The considered wireless communication systems are multiuser systems subject to frequency-selective multipath and employing multiple receiver antennas together with (i) oversampling or (ii) direct-sequence spreading or (iii) multicarrier modulation. The proposed modeling approach aims at unifying the received signal model of these systems into a single PARAFAC model. We show that the proposed model has a constrained structure, where model constraints and associated dimensions depend on each particular system. The proposed constrained Block-PARAFAC model is demonstrated by expanding the tensor using Kronecker products of canonical vectors. As an application of this model to tensor signal processing, a new tensor-based receiver is proposed for blind multiuser equalization, which combines PARAFAC-based modeling with a subspace method. Simulation results are presented to illustrate the performance of the proposed blind receiver.     

基于多端特征融合模型的MIMO-OFDM系统盲调制识别

自动调制分类（Automatic Modulation Classification, AMC）在认知无线电中起着提高频谱利用率的重要作用,然而,现有的大多数工作都集中在单输入单输出系统中的单载波通信。针对当前非协作通信中多输入多输出正交频分多路复用（Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing, MIMO-OFDM）系统子载波的盲调制识别问题,本文提出了一种基于多端特征融合模型的盲调制识别方法。首先,利用特征矩阵的联合近似对角化算法（Joint Approximate Diagonalization of Eigenvalue Matrix, JADE）从接收端的混合信号中恢复发送信号。然后,提取恢复信号的循环谱剖面和同向正交分量作为浅层特征。最后,搭建多端特征融合模型,利用一维卷积网络（One-Dimensional Convolutional Neural Network, 1D-CNN）与通道注意力模块（Channel Attention Module, CAM）的串联模型完成对浅层特征的提取和映射,并使用测试样本对所提出的调制识别算法进行仿真验证。仿真结果表明,本文方法在不需要先验信息的情况下对MIMO-OFDM系统的调制方式可以进行有效识别,在信噪比为4 dB时的识别精度可达到90%。      

基于循环频率特征的单信道混合通信信号的调制识别

单信道多个时频重叠的混合通信信号盲分离具有广泛的应用价值,是近年来通信信号处理研究领域的一个热点和难点,而单信道多个混叠通信信号的调制识别和信号个数的估计是实现单信道多个混叠通信信号盲分离的基础。该文通过分析数字调制信号的二阶和四阶循环累积量的循环频率特性和结构特征,提出一种基于循环频率特征的单信道混合通信信号调制识别的方法和实现算法,其主要特点是不需要已知混合信号的个数、功率、载频、符号率及定时等先验信息,对一些典型的数字调制信号(如BPSK, QPSK, OQPSK, MSK等)的随机混合,能够有效地辨识接收信号中所包含的信号个数以及每个调制信号的调制方式。利用计算机仿真实验,考察了不同条件下算法的性能,表明了其可行性和有效性。     

Non-cooperative signal modulation recognition algorithm based on joint feature parameter extraction

Aiming at the problem that in the current electromagnetic environment,the modulation method is complicated,the frequency-consuming equipment increases,the spectrum is congested,and the electromagnetic environment interference increases,the algorithm of OFDM signal detection and subcarrier identification in the background of non-cooperative communication were deeply studied.Using the different distribution states of OFDM signals and single carrier signals in the time domain,a joint characteristic parameter was proposed to solve the existence problem of OFDM in the received signal.For the phase shift and frequency offset problems caused by the channel transmission to the signal,by using the periodic stability the blind parameter estimation was performed to obtain the signal prior information.On the basis of the obtained signal prior information,a multi-level classification and recognition method for non-cooperative OFDM signal sub-carrier signals was proposed.Therefore,a model based on non-cooperative communication system OFDM signal detection and subcarrier modulation identification was designed,and finally modulation identification of unknown signals was completed.Simulation experiments show that in non-cooperative communication systems,OFDM signals and single-carrier signals can be accurately identified,and ideal modulation recognition effects can be achieved on empty subcarriers,QPSK,and 16QAM in the receiver OFDM signal subcarriers,overcoming the channel transmission band The problems of phase shift and frequency offset have improved the accuracy of modulation mode identification.     

A Backdrop Case Study of AI-Drones in Indian Demographic Characteristics Emphasizing the Role of AI in Global Cities Digitalization

The automatic identification of the modulation format of a detected signal is a major task of an intelligent receiver in both military and civilian applications. It is well known that the maximum likelihood (ML) classifier requires a priori knowledge of the incoming signal and channel (including amplitude, timing information, noise power, and the roll-off factor of the pulse-shaping filter). To relax this requirement, we introduce a novel estimator to estimate the parameters required by the ML classifier which is blind to the modulation scheme of the received signal, and this gives rise to a new blind modulation classifier for digital amplitude-phase modulated signals. While the proposed classifier is completely blind, the simulation results show that the performance of this classifier is very close to the optimal non-blind classifier.

     

Combined Coding and Training for Unknown ISI Channels

Combined Coding and Training for Unknown ISI Channels The traditional method of sending a training signal to identify a channel, followed by data, may be viewed as a simple code for the unknown channel. Results in blind sequence detection suggest that performance similar to this traditional approach can be obtained without training. However, for short packets and/or time-recursive algorithms, significant error floors exist due to the presence of sequences that are indistinguishable without knowledge of the channel. In this paper, we reconsider training signal design in light of recent results in blind sequence detection. Specifically, we consider the tradeoff between the complexity of receiver processing and the amount of training overhead required. More generally, we design training codes which combine modulation and training. In order to design these codes, we find an expression for the pairwise error probability of the joint maximum-likelihood (JML) channel and sequence estimator. This expression motivates a pairwise distance for the JML receiver based on principal angles between the range spaces of data matrices. The general code-design problem (generalized sphere packing) is formulated as the clique problem associated with an unweighted, undirected graph. We provide optimal and heuristic algorithms for this clique problem. For both long and short packets, we demonstrate that significant improvements are possible by jointly considering the design of the training, modulation, and receiver processing.     

Codierte Modulation in modernen Übertragungssystemen

Modern communication systems offer high speed and reliable data transmission services. The quality of these services is achieved by combining coded multi-level modulation techniques and modern digital signal processing (Viterbi-decoding) in the receiver. In this paper we first present an introduction to Trellis Coded Modulation (TCM) and then some new results on unversal techniques adapted for the AWGN-channel as well as for the fading channel. It is shown that TCM is well suited for communication channels with time variant characteristics (e.g. mobile communication channels), especially when our new codes are applied.     

Direct Blind Adaptive MOE Receiver for PAM Modulated Time-Hopping UWB System Over Frequency-Selective Fading Channel

Ultra wideband impulse radio systems have attracted great attention for their promised applications in high-speed short-range indoor wireless communication systems. Among the various modulation and multiple access schemes, this paper deals with time-hopping (TH) antipodal pulse amplitude modulation operating in the presence of a multipath fading downlink channel. We first employ a constrained optimization technique to design a batch mode blind (without exploiting training sequences and undesired users’ time-hopping (TH) codes) mobile station receiver. To reduce the computational complexity, we propose a blind adaptive receiver that is based on the criterion of maximizing the receiver’s minimum possible output energy. The algorithm jointly and iteratively optimizes the weight vector and channel impulse response to improve system performance. Simulation results show that the proposed adaptive receiver converges to the optimum batch mode receiver. Moreover, the algorithms are shown to be robust to multi-user interference and near-far problems.     

Blind equalization algorithms for dual-mode CAP-QAM reception

We propose a dual-mode receiver capable of blindly demodulating both carrierless amplitude modulation/phase modulation (CAP) and quadrature amplitude modulation (QAM) line codes. Our work is motivated by some emerging broad-band access standards which require a receiver that can first blindly start up, then blindly distinguish between CAP and QAM, and finally decode the signal. The “brute force” solution to this problem would be to implement CAP and QAM receivers in parallel. However, we propose a single novel receiver based on a single equalizer that accommodates both line codes, yielding significant computational savings. We describe the receiver architecture, blind start-up methods, and line code identification algorithms, as well as computer simulations and a laboratory experiment to verify the theoretical receiver behavior