【作者】 吴丹；

【导师】 郭黎利；

【作者基本信息】 哈尔滨工程大学 ， 通信与信息系统， 2009， 硕士

【摘要】 正交频分复用(OFDM)技术作为一种特殊的多载波调制方案,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下一代宽带无线通信的核心技术之一。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。本论文以此为出发点,通过对OFDM信号主要特征分析,对基于FFT/IFFT实现方案的非合作OFDM信号的检测及识别技术,进行了一些有益的探索性研究,其主要研究内容简述如下：首先,论文分析了合作OFDM通信系统相关理论及数学模型,进而分析了OFDM信号时域、频域特征,为非合作条件下OFDM信号的特征提取提供理论依据。同时,论文从非合作接收角度,提出非合作OFDM信号侦收系统理论模型,并指出该模型下将展开研究的关键技术：OFDM信号存在性检测、调制方式识别及相关参数估计。然后,针对OFDM信号的时域包络统计特性,提出基于高阶累积量的OFDM调制盲识别算法。在带通多载波模式识别部分,主要利用OFDM信号时域包络渐近高斯性分布特点,对已有基于累积量的识别特征参量提取进行改进,有效的抑制了瑞利衰落及高斯噪声对接收端多载波模式识别性能的影响。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,能有效的抑制多径衰落所引起的功率衰减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,分析了所提出算法的高效识别性能。最后,针对OFDM信号的循环平稳特性,提出基于循环统计量的OFDM信号恒虚警检测及相关参数估计算法。文中结合数学建模,证明了OFDM信号的循环平稳特性,并进一步推导了OFDM信号二阶循环统计量及谱相关密度函数的表达式。结合仿真实验,验证了理论分析的正确性,为循环平稳分析理论应用于OFDM盲信号处理提供了有力依据。据此,提出一种基于循环频率检测的OFDM信号盲检测算法,该算法明确了理论检测门限,对OFDM信号的的盲检测做出了定量分析。并充分利用OFDM二阶循环统计量的结构特征：通过采用改进的自相关检测算法确定固定时延,将协方差估计矩阵由2N维降至2维,避免多维运算的复杂度。与此同时,实现对OFDM符号长度、有用符号时间、循环前缀长度、子载波间隔的盲估计。仿真实验表明,算法具有较强的的抑制加性干扰和乘性干扰的能力,适合于低信噪比下OFDM信号的可靠侦察及参数的有效估计。更多还原

【Abstract】 As a special scheme of MCM (Multi-carrier Modulation) systems, OFDM (Orthogonal Frequency Division Multiplexing) has been adopted or proposed as one of the core technologies for the next generation wireless communication due to its unique features of optimal spectrum efficiency and of the strong ability for anti-ISI (Inter-Symbol Interference). Meanwhile, the wide application of OFDM has brought a series missions and challenges in the field of information countermeasure or spectrum resource management. Hence, the key technologies study on reception of non-cooperative OFDM signals is of great significance.Regard this as the starting point, by analyzing the features of OFDM signal, a number of profitable exploratory works have been done to realize signal detection and modulation identification of non-cooperative OFDM signal relying on FFT/IFFT implementing scheme, the primary research contents are as follows:To begin with, related Theories and mathematical model of OFDM system are studied. Furthermore, features of OFDM signal in time and frequency domain are analyzed to provide theoretical basis for OFDM characters’extraction. Then, theoretical model for non-cooperative OFDM signal reception is proposed, it is pointed out that three key technologies are studies in these dissertation:OFDM signal detection, modulation identification and parameters estimation.Where-after, focusing on the envelope statistical behaviors of OFDM signal in time domain, a novel blind modulation identification algorithm using HOC (Higher Order Cumulants) is proposed. In pass-band recognition part, based on the asymptotic Gaussian distribution of OFDM signal, an improved distinctive traits extraction method is applied to distinguish OFDM from other single carrier modulations, which can counteract the impact of both Rayleigh fading and Gaussian noise on the receiving identification property. In base-band part, a blind modulation classification algorithm is derived from the statistical property of information symbols on each sub-carriers and equivalent parallel model of the OFDM system. The envelope features extracted on each sub-carriers using HOC can resistant the attenuation and phase rotation included by sub-channels. The high performances of the proposed algorithms are proved by simulations.Finally, focusing on the cyclostationarity behavior of OFDM signal, CFAR (Constant False Alarm Rate) test for OFDM presence and relevant parameters estimation algorithm are proposed. By mathematical modeling, it is proved that OFDM signal is cyclostationarity. Furthermore, the 2-th cyclic cumulants and spectral correlation density function of pass-band OFDM signal are derived in detail. Simulation results support the theoretical analysis perfectly, which provide convincing evidence of cyclostationarity theory used in the field of blind processing for OFDM signal. Hereby, a blind detection algorithm for OFDM signal based on cyclic frequency test is proposed, the algorithm clears the detection threshold and makes qualitative analysis for OFDM detection. Moreover, by adopting the improved auto-correlation detection method to confirm the fixed time-delay, Covariance matrix dimension is descended from 2N to 2, which avoids the complexity of multi-dimensional computation. Then, blind estimations of the symbol period, useful symbol duration, the length of cyclic prefix and the carrier frequency offset of OFDM can be obtained. Simulation results demonstrate the detection algorithm has strong ability to inhibit the add interference and multiply interference and it is suitable for OFDM reconnaissance and parameters estimation at a lower SNR.更多还原