一种新的分数阶记忆多项式预失真器

该文针对由记忆多项式设计的功率放大器预失真系统,提出了一种新的分数阶记忆多项式预失真器。提出预失真多项式是在常用记忆多项式基础上,通过去掉偶数阶项增加分数阶项以提高线性化性能。文中给出了分数阶记忆多项式的表达式,并给出了相应的系数估计算法。仿真分析表明,针对Wiener-Hammerstein和记忆多项式模型的功率放大器,在两种典型记忆多项式预失真的基础上可以分别得到10 dB和8 dB的带外谱抑制增益。相应的FPGA实现表明该预失真多项式总体硬件资源增加的代价并不高,易于在实际系统中应用。     

无记忆间接学习结构预失真器

为了提高通信系统中功率有效性和频谱利用率,在采用预失真技术克服功率放大器（PA）的非线性失真和采用多项式模型逼近功放模型的理论基础上,分析了多项式有效阶和输出功率回退（OBO）对预失真器补偿性能的影响,并进行仿真,提出预失真建模方向,对于提高功放效率,降低系统成本,推动节能减排具有一定的实际意义。     

广义改进型Hammerstein预失真器的实现方法及验证

射频功率放大器与生俱来的非线性是无线通信前端设计需要解决的核心问题之一。根据广义改进型Hammerstein功率放大器非线性模型,提出一种应用于射频功放线性化的新型数字预失真器——广义改进型Hammerstein(Generalized Augmented Hammerstein, GAH)预失真器,并给出了该预失真器的实现方法。另外,为了精确分析GAH 预失真器的性能,采用实际功放的输入输出数据进行仿真和实验。被测功放为中心频率1960 MHz,带宽40 MHz, 输出功率45 dBm的Doherty功放。仿真和实验证明：提出的数字预失真器不仅计算复杂度远低于记忆多项式（Memory Polynomial,MP）和分数阶记忆多项式（Fractional Memory Polynomial, FMP）预失真器,而且其线性化能力也强于AH、MP及FMP等预失真器。     

基于多项式与查找表的预失真技术研究

为补偿功率放大器固有的非线性,提出了一种新型的预失真器。该预失真器结合查找表和多项式两种常用的预失真方法实现,在查找表中存储分段低阶多项式系数,根据输入信号的幅度查表得到相应的多项式系数对输入信号进行预失真处理。仿真结果表明,该预失真器对互调失真（IMD）的改善优于多项式预失真器,能有效改善信号因功放非线性失真而导致的信号星座图扭曲及频谱再生,提高通信系统的性能。     

一种有效的基于宽带功率放大器强记忆效应特性的PMEC预失真方法

针对宽带功率放大器的强记忆效应特性,论文提出了一种新的预失真方法PMEC (Parallel MP-EMP-CIMT),该方法基于记忆多项式(MP),包络记忆多项式(EMP)及记忆时刻信号交叉项(CIMT)3个基函数构造预失真器。与传统混合记忆多项式(HME)方法相比,PMEC方法增加了记忆时刻信号间的交叉相乘项,此外,为了解决系统复杂度高的问题,对EMP子预失真器进行了简化并截断了CIMT子预失真器的高阶非线性项。实际测试结果表明,PMEC方法比MP方法和HME方法能带来更好的线性化效果,与MP方法相比,PMEC方法将输出信号的三阶邻信道功率比(ACPR)降低了1.07 dB/1.32 dB,预失真系数量节省了18.75%;与HME方法相比,PMEC方法利用79.59%的预失真系数将输出信号的三阶ACPR降低了0.2 dB/0.99 dB。     

功率放大器及预失真器模型的设计

传统多项式常用在功率放大器模型和预失真器模型的设计里。然而,随着多项式阶数逐次增加时,传统多项式模型表现出数据的不稳定性。详细介绍了一种用于功率放大器以及预失真器模型的正交多项式。从理论上讲,传统多项式与正交多项式模型是等效的,但实践表明,在有限精度范围内,这两种方法对数据进行了不同的处理。MATLAB仿真结果表明,正交多项式可以减轻数值不稳定的问题,建立高精度的功率放大器和预失真器模型,进而改善系统的线性化指标。     

基于多项式的功率放大器预失真技术

基于查询表(LUT)及基于多项式的基带数字自适应预失真技术,是目前功率放大器(PA)线性化技术中通常采用的两种方法.分析了两种方法的优、缺点,深入研究了基于多项式的预失真技术.从直接控制及间接控制结构两方面进行了性能的仿真分析,得出了预失真性能较好的多项式控制结构形式.     

基于非直接学习结构的记忆多项式预失真技术研究

针对记忆多项式数字预失真的问题,构造了一个记忆多项式预失真系统,通过非直接学习结构(ILA)实现系数估计,根据系统特性推导出改进LMS算法。以Matlab为平台,仿真结果表明这种记忆多项式预失真器能够较好地消除失真。     

基于多项式拟合的自适应预失真技术研究

为了克服功率放大器的非线性特性导致的带内失真和临道干扰对通信系统性能的影响,提出了一种基于多项式拟合的自适应预失真技术。该方法根据输入和输出的一些采样数据,依据某种算法或原则,用有限项多项式近似表示预失真器的非线性函数,能够很好的实现功放的线性化。通过对双音信号和16QAM基带信号进行仿真,该方法能够有效改善双音信号的三阶互调分量,降低16QAM调制信号通过放大器后星座图的畸变度,使通信系统的系统性能整体提高。     

一种用于TETRA系统的数字子带滤波预失真器

本文提出一种适用于TETRA数字集群系统的基于子带滤波技术的数字自适应预失真器。数字子带滤波预失真器将发射信号分为若干子带进行功放线性化处理,降低了预失真过程中运算速率的要求,增加自适应收敛速度。子带滤波技术同时解决了功放宽带化所带来的记忆性问题,扩展了数字预失真器的工作带宽。TETRA多载波发射信号的仿真结果说明,数字子带滤波预失真器对无记忆功放和有记忆功放均具有良好的线性化效果,明显扩大了功放的线性工作范围。      

Low Complexity Polynomial Expansion Multiuser Detector for CDMA Systems

The polynomial expansion (PE) multiuser detector can iteratively approximate the linear decorrelating and MMSE multiuser detectors. This is a very promising approach since the complexity of the PE detector is considerably less than that of the decorrelating and MMSE detectors. The concept of the PE multiuser detector is a weighted matrix polynomial for which optimal weighting has been suggested in the literature. Unfortunately, the optimal weights apply only to a specific correlation matrix. As soon as the correlation between the users changes (and hence also the correlation matrix), a new set of optimal weights has to be calculated. The calculation of these weights is computationally very intense. In this paper, an approach is presented where the weights are predefined and apply for all matrices. Furthermore, a normalization factor is needed to ensure convergence. It will be shown how this factor has to be chosen to obtain the optimal convergence speed. For the optimal normalization factor the minimum and maximum eigenvalues are needed. A low complexity and accurate method to estimate these eigenvalues is derived which can be applied to all correlation matrices and therefore to any code division multiple access (CDMA) scenario. Hence, the matrix-dependent optimal normalization factor can easily be calculated and ensures a good bit error rate (BER) performance, even if the correlation between the users changes quickly (e.g., in time-variant channels). Furthermore, it will be shown how to enhance the PE detector such that it has a high near-far resistance. Additionally, for the first time it can be proven that the approximation error of the proposed detector diminishes exponentially with the number of iterations. Finally, simulations verify the fast convergence of the proposed PE detector and its flexible usage in a variety of scenarios.     

Blind adaptive multiuser detector for nonlinearly modulated satellite mobile CDMA systems

This paper presents a novel blind adaptive noncoherent decorrelative multiuser detector for nonlinearly modulated satellite mobile Code Division Multiple Access （CDMA） systems. By using the known signature waveforms of the counterpart earth station in the blind adaptive multiuser detector, the system performance has been improved obviously. The computation results about the convergence properties of the new detector and the previous detectors demonstrate that the proposed multiuser detector has better performance than previous multiuser detectors for nonlinearly modulated CDMA systems.     

基于干扰空间的盲自适应多用户检测器

在现有盲自适应多用户检测技术基础上，本文提出一种更具有实际应用价值的基于干扰空间线性MMSE盲自适应多用户检测器及其相应的基于干扰自相关矩阵C1跟踪算法。数学分析和仿真结果表明：与现有盲自适应多用户检测器相比，该检测器具有更低的实现复杂度、更快的跟踪速度和更强的健壮性。     

Semiblind linear parallel interference cancellation multiuser detectors for DS-CDMA systems

Semiblind multiuser detection for the reverse link of a multicell code-division multiple-access (CDMA) system is considered. In such a system, although active users are present in the home cell and neighboring cells, the base station receiver only knows the signature information of the users in its own cell. Three new semiblind linear multiuser detectors are proposed based on parallel interference cancellation approach. Compared with some known semiblind detectors, the proposed detectors share a rather simple implementation structure and involve reduced latency for processing, which are of particular importance in a time-varying CDMA system. Numerical results are presented to compare the detection performance of the proposed detectors with that of some existing semiblind multiuser detectors.     

A near-optimal multiuser detector for DS-CDMA systems using semidefinite programming relaxation

A multiuser detector for direct-sequence code-division multiple-access systems based on semidefinite programming (SDP) is proposed. It is shown that maximum likelihood (ML) detection can be carried out by "relaxing" the associated integer programming problem to a dual SDP problem, which leads to a detector of polynomial complexity. Computer simulations that demonstrate that the proposed detector offers near-optimal performance with considerably reduced computational complexity compared with that of existing primal-SDP-relaxation based detectors are presented.     

Nonparametric multiuser detection in non-Gaussian channels

Existing multiuser detection techniques in wireless systems are based on the assumption that some information on the parameters of the probability density function (pdf) of ambient noise is available. Such information may not be available in all cases, particularly for non-Gaussian and impulsive noises, or may change depending on circumstances. In this paper, we present a technique for multiuser detection that does not require any a priori knowledge about the noise parameters. This method is based on using pseudo norms for linear nonparametric regression. Analytical and simulation results show that the proposed method offers an improved, or at least comparable, performance over existing robust techniques in the absence of any information on the nature of noise in the environment. The increased computational complexity is marginal compared to existing parametric detectors. In addition, the proposed nonparametric detector is portable in the sense that it does not need to be tuned for different noise models without any considerable degradation of performance. We also show that in non-Gaussian noise, the performance of blind adaptive nonparametric multiuser detectors is better than that of robust multiuser detectors.     

Robust multiuser detection in non-Gaussian channels

In many wireless systems where multiuser detection techniques may be applied, the ambient channel noise is known through experimental measurements to be decidedly non-Gaussian, due largely to impulsive phenomena. The performance of many multiuser detectors can degrade substantially in the presence of such impulsive ambient noise. We develop robust multiuser detection techniques for combating multiple-access interference and impulsive noise in CDMA communication systems. These techniques are based on the M-estimation method for robust regression. Analytical and simulation results show that the proposed robust techniques offer significant performance gain over linear multiuser detectors in impulsive noise, with little attendant increase in computational complexity. We also develop a subspace-based technique for blind adaptive implementation of the robust multiuser detectors, which requires only the signature waveform and the timing of the desired user in order to demodulate that user's signal. The robust multiuser detection technique and its blind adaptive version can be applied to both synchronous and asynchronous CDMA channels     

Asymptotic multiuser efficiencies for decision-directed multiuserdetectors

The asymptotic multiuser efficiencies (AMEs) are derived for various classes of decision-directed multiuser detectors, including multistage detectors, and decision-feedback detectors. Novel classes of soft-decision multistage detectors are proposed and analyzed. Each class is specified in part by a soft-decision nonlinearity, such as a symmetric quantizer or a linear clipper. Closed-form expressions for two-user AMEs are derived for soft-decision two-stage detectors and can be used as a design criterion to optimize the soft-decision nonlinearities. For a special case of two synchronous users, the soft-decision two-stage detector using an optimized linear clipper with either conventional or decorrelated tentative decisions is shown to achieve optimum AME. Upper and lower bounds on the AME are obtained for decision-feedback detectors using either conventional or decorrelated tentative decisions. It is demonstrated that decision-directed multiuser detectors with conventional tentative decisions have low near-far resistance compared to those with decorrelated tentative decisions     

Improved Robust Techniques for Multiuser Detection in Non-Gaussian Channels

In many physical channels where multiuser detection techniques are to be applied, the ambient channel noise is known through experimental measurements to be decidedly non-Gaussian, due largely to impulsive phenomena. This is due to the impulsive nature of man-made electromagnetic interference and a great deal of natural noise. This paper presents a robust multiuser detector for combating multiple access interference and impulsive noise in code division multiple access (CDMA) communication systems. A new M-estimator is proposed for "robustifying" the detector. The approach is corroborated with simulation results to evaluate the performance of the proposed robust multiuser detector compared with that of the linear decorrelating detector, and the Huber and the Hampel M-estimator based detectors. Simulation results show that the proposed detector with significant performance gain outperforms the linear decorrelating detector, and the Huber and the Hampel M-estimator based detectors. This paper also presents an improved robust blind multiuser detection technique based on a subspace approach, which requires only the signature waveform and the timing of the desired user to demodulate that user's signal. Finally, we show that the robust multiuser detection technique and its blind adaptive version can be applied to both synchronous and asynchronous CDMA channels.     

Minimum probability of error for asynchronous Gaussian multiple-access channels

Consider a Gaussian multiple-access channel shared byKusers who transmit asynchronously independent data streams by modulating a set of assigned signal waveforms. The uncoded probability of error achievable by optimum multiuser detectors is investigated. It is shown that theK-user maximum-likelihood sequence detector consists of a bank of single-user matched filters followed by a Viterbi algorithm whose complexity per binary decision isO(2^{K}). The upper bound analysis of this detector follows an approach based on the decomposition of error sequences. The issues of convergence and tightness of the bounds are examined, and it is shown that the minimum multiuser error probability is equivalent in the Iow-noise region to that of a single-user system with reduced power. These results show that the proposed multiuser detectors afford important performance gains over conventional single-user systems, in which the signal constellation carries the entire burden of complexity required to achieve a given performance level.