基于高阶循环累积量的OFDM子载波盲估计

该文针对通信对抗和OFDM信号解调的实际应用,提出一种利用高阶循环累积量估计OFDM信号子载波的方法。由于高阶循环累积量能有效抑制平稳噪声和非平稳高斯噪声,通过理论分析可证明在上述噪声背景下,子载波采用2/4PSK调制的OFDM信号的特定四阶循环累积量仅在子载波处存在,因此可以通过检测此循环频率实现子载波的估计。该算法还可推广到采用星形QAM和高阶PSK调制的OFDM信号。仿真实验验证了该算法的有效性。     

一种基于ITD和高阶累积量的OFDM识别算法

针对正交频分复用(OFDM)与单载波调制识别,提出了一种基于固有时间尺度分析(ITD)和高阶累积量的识别方法。通过ITD分解待识别信号,提取固有旋转分量的瞬时幅度,利用其复信号幅值高阶累积量区分OFDM和单载波信号,并利用改进和提出的特征参数识别单载波信号。通过MATLAB仿真表明在信噪比不小于5dB的情况下,OFDM信号的识别准确率达99%。     

基于高阶统计量的OFDM子载波调制识别算法北大核心

针对OFDM(正交频分复用)信号子载波调制方式识别的问题,提出了一种将高阶矩和高阶累积量相结合的联合识别算法。该算法首先运用基于高阶矩的特征量把MPSK(多进制相移键控)调制(M=2、4)、64QAM(六阶正交幅度调制)和16QAM(四阶正交幅度调制)区分开,然后再利用基于高阶累积量的特征量区分BPSK(二进制相移键控)调制和QPSK(四相相移键控)调制。从理论上进行了推导与分析,该算法对多径衰落与噪声干扰不敏感。计算机仿真结果表明,所提算法在多径信道条件下具有良好的识别性能。     

基于循环自相关的OFDM调制识别方法

针对通信信号的调制识别问题,首先根据通信信号的循环平稳性,提出一种基于循环自相关的OFDM信号和单载波信号的调制识别算法,然后将小波多分辨分析理论与调制信号的瞬时特征以及高阶累积量相结合,提出一种基于小波分解的单载波信号识别方法,在此基础上采用分层结构的神经网络分类器对OFDM,2ASK,4ASK,2PSK,4PSK,8PSK,16QAM这7种调制信号进行识别。仿真结果表明该方法具有良好的分类性能,且对噪声不敏感。     

基于高阶累积量的OFDM子载波盲识别探讨

正交频分复用（OFDM）技术作为一种特殊的多载波调制技术,以其高效的频谱利用率、较强的抗码间干扰能力等优点成为第四代宽带技术的核心技术之一。同时,OFDM的广泛应用也为信息对抗、无线频谱资源管理等领域带来了一系列新的任务与挑战。因此,对非合作OFDM信号侦收技术的研究,意义深远。 由于OFDM调制方式的特殊性,在完成宽带多载波与单载波信号分类之后,接收系统有必要对OFDM信号的子载波类型进行进一步判断。文中采用基于高阶累积量的子信道调制盲识别算法作为技术路线,通过提取特征向量实现对子信道调制方式的盲识别。 在基带OFDM信号子载波调制类型识别部分,结合OFDM系统的等效标量模型,利用每个子载波上符号序列的统计特性,提取序列的高阶累积量作为识别分类特征构造算法,能够有效地抑制多径衰落所引起的功率衰减以及相位旋转对子载波调制类型识别性能的影响,结合仿真实验,我们分析了所提出算法的高效识别性能。     

基于高阶累积量的OFDM子载波盲识别探讨

正交频分复用（OFDM）技术作为一种特殊的多载波调制技术,以其高效的频谱利用率、较强的抗码间干扰能力等优点成为第四代宽带技术的核心技术之一。同时,OFDM的广泛应用也为信息对抗、无线频谱资源管理等领域带来了一系列新的任务与挑战。因此,对非合作OFDM信号侦收技术的研究,意义深远。
　　由于OFDM调制方式的特殊性,在完成宽带多载波与单载波信号分类之后,接收系统有必要对OFDM信号的子载波类型进行进一步判断。文中采用基于高阶累积量的子信道调制盲识别算法作为技术路线,通过提取特征向量实现对子信道调制方式的盲识别。
　　在基带OFDM信号子载波调制类型识别部分,结合OFDM系统的等效标量模型,利用每个子载波上符号序列的统计特性,提取序列的高阶累积量作为识别分类特征构造算法,能够有效地抑制多径衰落所引起的功率衰减以及相位旋转对子载波调制类型识别性能的影响,结合仿真实验,我们分析了所提出算法的高效识别性能。     

基于高阶累积量和循环谱的信号调制方式混合识别算法

为了识别当前通信系统所采用的主要调制方式,该文结合高阶累积量和循环谱的特点,采用混合识别算法,同时应用智能决策算法(神经网络)对信号进行识别。该算法基于四阶和六阶高阶累积量构造出一个新的特征参数,将数字调制信号分为{BPSK, 2ASK}, {QPSK}, {2FSK, 4FSK}, {MSK}和{16QAM, 64QAM}5类。然后利用高阶累积量的其它特征参数以及循环谱特征对{OFDM}, {16QAM, 64QAM}, {2ASK, BPSK}及{2FSK, 4FSK}进行识别。为便于工程实现,该文采用半实物仿真以及LabVIEW和MATLAB混合编程来验证算法。仿真结果证明,该算法能够在较低信噪比下实现对{OFDM, BPSK, QPSK, 2ASK, 2FSK, 4FSK, MSK, 16QAM, 64QAM}等多种信号的分类,在信噪比高于 5 dB时,调制方式识别率可达94%以上,由此证明了该方法的有效性。     

频率选择性衰落信道下OFDM子载波数盲估计

提出了一种在频率选择性衰落信道下的基于高阶循环累积量的OFDM信号子载波数盲估计方法,扩展了该方法的适用范围,并进行了理论推导和试验仿真。结果表明OFDM信号的特定高阶循环累积量仅在子载波位置存在,通过检测循环频率的个数可以估计出子载波数。高阶累积量具有良好的抗噪性能,在低信噪比下具有良好的估计性能。     

突发自适应调制信号的调制识别算法研究

针对突发自适应调制信号中的PSK和QAM调制方式识别问题,本文提出了一种能够识别BPSK、QPSK、8PSK以及16QAM、32QAM、64QAM、128QAM、256QAM八种信号类型的盲识别算法。该算法首先对信号的循环平稳性进行了分析和讨论,给出了利用循环高阶累积量的特征实现信号识别分类的理论依据。然后,提出了三种基于循环累积量的特征分别实现了QAM和PSK类间识别、MPSK类内识别以及方形QAM与十字形QAM的识别。最后通过对MQAM信号的瞬时幅度分布特性的深入研究和分析,提出了一种基于瞬时包络平方的方差的特征实现了QAM的类内识别。该算法选择了二叉树支持向量机作为识别分类器,并设计了一种新的识别流程完成了对上述信号调制方式的识别。该算法无需精确同步,对载波相位具有较好的鲁棒性,并能够对中频信号进行识别。仿真实验表明,该算法能够实现在较低信噪比条件下突发信号的识别。      

一种改进的基于支持向量机的OFDM识别算法

针对OFDM信号与单载波信号调制识别,提出了一种基于高阶累积量特征的改进方法.通过分析复信号幅值的归一化四阶累积量特性,以及信号的瞬时频率和功率谱特征,改进和提出新的特征参数,采用支持向量机分类器,实现了AWGN信道下包括OFDM在内的9种信号的制式自动识别.该方法具有特征参数易于提取、抗噪性好、识别准确率高的优点.利用MATLAB仿真证明在信噪比不小于7dB的情况下,OFDM信号的识别准确率达99%.     

OFDM信号的盲侦察技术分析

正交频分复用传输系统,以其可对抗频率选择性衰落,高频谱利用率等优点,得到了广泛的应用。论述了正交频分复用(OFDM)信号非协作接收中的某些关键算法,研究了基于循环前缀的符号同步算法及最大联合似然估计(ML)算法、基于高阶累量的OFDM信号调制样式识别算法,解决了OFDM信号和常规通信信号之间的类间信号识别问题。仿真结果进一步说明了该方法的有效性。     

子波长粒度光信号传输的频域均衡设计和性能分析

针对弹性光网络(EON)的应用,提出了一种基于电域子载波复用的子波长粒度光信号传 输技术,具有高灵活性、细 粒度、高效率等特点。同时,电域数字信号处理技术的使用,支持对不同的子波长粒度信号 进行独立的调 制方式、传输速率等灵活配置。为了适应子波长粒度光信号在EON中的传输要求 ,还提出了一 种基于线性频率啁啾导频信号的信道估计和频域均衡(FDE)的方法,重点研究和分析了基于 导频的FDE和基 于训练序列的时域均衡(TDE)的性能对比,以及不同的FDE算法的性能对比。仿真结 果表明,基于线性频率 啁啾导频信号的迫零FDE算法,不仅能有效进行色散补偿,改善系统传输性能,而 且具有低算法复杂 度的优势。同时,为了满足了子波长粒度EON对频隙和路由配置的灵活性需求, 通过仿真详 细研究子波长粒度光信号的数目、传输距离和调制阶数等对传输性能的影响。仿真结果表 明,基于线性 频率啁啾导频信号的信道估计和FDE的方法,在不同的光网络配置下均具有良好的 适应性,是实现灵 活可调的光收发机和子波长信号动态重构的关键技术之一。     

Optical Systems With High-Order DPSK and Star QAM Modulation Based on Interferometric Direct Detection

Increased interest in novel modulation formats for optical transmission has come up in recent years. Receivers with interferometric direct detection can be used to detect arbitrary modulation formats with differentially encoded phases as differential phase-shift keying (DPSK) and differentially phase-encoded star-shaped quadrature amplitude modulation (Star QAM). In this paper, two novel 16-ary modulation formats, which are the 16 DPSK and the Star 16 QAM (ASK-8 DPSK), are characterized for optical transmission for the first time. To be able to identify clear performance tendencies for high-order optical modulation, the novel formats are compared to a wide range of already investigated formats by conducting comprehensive calculations in a uniform simulation environment. The influence of different transmitter structures and decision schemes is considered, and all the systems are characterized with respect to the optical signal-to-noise ratio requirements, dispersion tolerance, and self-phase-modulation (SPM) performance for nonreturn-to-zero (NRZ) and RZ pulse shapes. Moreover, an inherent problem of Star QAM transmission concerning SPM is illustrated, and compensation techniques are examined. The results give a substantial insight into the properties of high-order optical modulation formats.     

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.     

Carrier frequency offsets estimation for distributed MIMO system based on SOMP method

By utilizing the half invariant property of high-order cyclic cumulants,the equation of signals and its high-order cyclic cumulants was rederivated first.Then simultaneous orthogonal matching pursuit (SOMP) method was used to jointly reconstruct multiple receiving signals’ high-order cyclic cumulants.At last,according to the fourfold relationship between carrier frequency offsets and cyclic frequencies of main non-zeros high-order cyclic cumulants,multiple transmitting signals’ carrier frequency offsets were obtained.Comparing with existing algorithms,the correlation between receiving signals is fully used by the proposed algorithm,the carrier frequency offset estimation performance at low signal to noise is improved and the pilots numbers are reduced.     

Modulation recognition of communication signals based on high order cumulants and support vector machine

Using high order cumulants as signal eigenvalues, signals of different modulation formats can be recognized with support vector machine (SVM). Since high order cumulants of different modulation signals are different from each other, fourth and sixth orders of cumulants were chosen and only four eigenvalues were constructed in the recognition in this paper, thus signals of different modulation format and signals of different modulation order with the same format were recognized in low signal-to-noise ratio (SNR). It was shown that the key of recognition of modulation format is how to choose proper high order cumulants as eigenvalues. So that acceptable accuracy of recognition could be obtained in low SNR. During the recognition process, one-to-one classification of LibSVM was used to simplify the usual binary separation process. An efficiency modulation recognition method was put forward with high recognition rate and less complexity.