一种新的OFDM定时与频偏联合同步算法*

OFDM技术在无线衰落信道中传输高速数据时具有突出的优势。提出了一种以PN序列为前导的快速低复杂度的帧定时和整数倍频偏联合同步算法。理论分析和仿真表明,这种算法在低信噪比和大频偏下具有良好的性能。     

A factor graph-based iterative detection of faster-than-Nyquist signaling in the presence of phase noise and carrier frequency offset

With the increasing demand for higher spectral efficiency in wireless communications, faster-than-Nyquist (FTN) signaling has been rediscovered to increase transmission rate without expanding signaling bandwidth. Most existing studies focus on low-complexity FTN receiver design by assuming perfect synchronization. In practice, however, phase noise (PHN) and carrier frequency offset (CFO) may degrade the performance of FTN detector significantly. In this paper, we develop iterative FTN detector in the presence of PHN and CFO in a factor graph framework. Wiener process is employed to model the time evolution of nonstationary channel phase. The colored noise imposed by sampling of FTN signaling is approximated by autoregressive model. Based on the factor graph constructed, messages are derived on the two subgraphs, i.e., PHN and CFO estimation subgraph and the FTN symbol detection subgraph. We propose two methods to update the messages between subgraphs, namely, Gaussian approximation via Kullback–Leibler divergence (KLD) minimization and the combined sum-product and variational message passing (SP-VMP), both of which enable low-complexity parametric message passing. The proposed SP-VMP algorithm can provide closed-form expressions for parameters updating. Moreover, conjugate gradient (CG) method is adopted to solve the maximum a posteriori probability (MAP) estimation of CFO with fast convergence speed. Simulation results show the superior performance of the proposed algorithm compared with the existing methods and verify the advantage of FTN signaling compared with the Nyquist counterpart.     

新的OFDM系统载波频偏盲估计算法

针对现有频偏估计算法复杂度高的问题,提出一种新的基于恒模信号的盲估计算法。假定信道变化缓慢,紧邻OFDM符号将产生相同信道响应,通过衡量它们之间的幅度差异,推导出一种目标函数,采用曲线拟合法对目标函数进行拟合并求得最小值时,即得到最接近真实值的CFO估计值。仿真结果表明,所提算法与现有PDE-F[1]算法和PDE-T[2]算法相比,提高了估计精度,降低了复杂度,尤其在窄带噪声和接收信号增益不断变化的环境下,该算法具有更好的适用性和稳定性。     

WiMAX技术中OFDMA上行链路载波频偏补偿算法研究*

在OFDMA上行链路中,由于多个用户的载波频率偏差（CFO）破坏了载波间的正交性,从而在基站接收端产生多用户间干扰（MUI）。针对这个问题提出了一种能够实现载波频偏补偿的低复杂度迭代信号处理算法。仿真结果表明,这种算法能有效消除MUI,改善了WiMAX上行链路的传输性能。     

新的基于粒子群优化的正交频分复用系统盲频偏估计算法

针对正交频分复用(OFDM)系统频偏估计问题,提出了一种基于粒子群优化(PSO)的盲频偏估计算法。首先,根据频偏估值重建的接收信号和实际接收到的信号误差最小原则构造了盲频偏估计的数学模型,并推导出了代价函数;然后,利用粒子群优化算法强大的随机并行全局搜索能力,通过最小化代价函数估计频偏。仿真比较了常系数、微分递减两种惯性权重策略PSO算法的频偏估计性能,并与最小输出方差、黄金分割盲频偏估计算法进行了比较分析。仿真结果表明,所提算法精度高,同一信噪比下较同类算法大约有一个数量级的提升,且不受调制类型和频偏估计范围(-0.5,0.5)的限制。     

MIMO-OFDM系统中接收窗函数的性能比较

窗函数已被广泛地应用于多输入多输出-正交频分复用系统的接收端,以降低系统对频率偏移的灵敏性,减小载波间干扰,改进接收机,提高系统性能。该文将矩形窗、升余弦窗、优于升余弦窗和二阶连续窗以时域加窗的方式应用于MIMO-OFDM系统接收机,并通过理论分析和计算机仿真就各窗函数对系统性能的影响进行了比较分析。     

A novel CFO estimator with joint bisection-searching and complexity-reduction technique for uplink MC-CDMA systems

This paper presents a simple scheme, which speeds the estimation of carrier frequency offset (CFO) as well as reducing the estimation complexity for multicarrier code-division multiple-access (MC-CDMA) uplink. Based on the concept of bisection method, the CFO is efficiently estimated by way of locating the peak value in the output power spectrum of the minimum output energy (MOE) detector. Complexity reduction results from the proposed data vector partition associated with an innovative data processing technique for the MOE detector. Simulation results show that the expected advantage of the proposed scheme can be achieved at the expense of a reasonable performance loss even in the presence of a large CFO.     

Magnitude bounds of generalized frequency response functions for nonlinear Volterra systems described by NARX model

In order to reveal the relationship between system time domain model parameters and system frequency response functions, new magnitude bounds of frequency response functions for nonlinear Volterra systems described by NARX model are established. The magnitude bound of the nth-order generalized frequency response function (GFRF) can be expressed as a simple n-degree polynomial function of the magnitude of the first order GFRF, whose coefficients are functions of the model parameters and frequency variables. Thus the system output spectrum can also be bounded by a polynomial function of the magnitude of the first order GFRF. These results demonstrate explicitly the analytical relationship between model parameters and system frequency response functions, and provide a significant insight into the magnitude based analysis and synthesis of nonlinear systems in the frequency domain.