一种级联两箱通用数字预失真器及其辨识算法

提出了一种由单形规范线性分段(SCPWL)函数与记忆多项式级联的数字预失真器,并给出了复数域两步最小二乘参数辨识算法。不同于以往一种预失真器适用一种功放模型的情况,所提的预失真算法利用SCPWL函数的分段特性以及记忆多项式的非线性记忆特性,在完成参数辨识的同时自动地调整结构,可适用于传统以及强非线性新型功放模型的线性化补偿。将所提预失真器分别应用于传统记忆多项式、两箱模型以及新型包络跟踪功放。经过计算机仿真,功放输出的幅频特性和频谱曲线表明所提预失真器能够有效地补偿多种功放的非线性特性。算法仿真比较结果也表明,针对包络跟踪功放,所提复数两步最小二乘算法的邻道泄漏比(ACLR)可改善约35 dB,性能优于最小均方(LMS)类算法约30 dB。     

基于IPLS的记忆功放数字预失真技术

针对现有方法普遍存在的预失真算法效率低、难以有效抑制记忆功放的互调失真等缺点,在传统预失真技术的基础上,提出了一种基于内点最小二乘(IPLS,Interior Point Least Squares)法的数字预失真技术。该方法利用内点最小二乘思想来解决预失真问题,避免了传统RLS算法中对其自相关矩阵的求逆运算,提高了数值的稳定性,降低了运算的复杂度,有效提高了运算的收敛速度和收敛精度。计算机仿真分析表明,该算法对互调失真的抑制有着非常好的效果。     

一种基于LS/SVD的基带预失真算法

自适应基带预失真技术是用于补偿高功率放大器非线性失真的一种有效技术。早期对预失真的研究大多局限于无记忆非线性,但对于OFDM等宽带应用,放大器的记忆效应明显。介绍了一种基于最小二乘奇异值分解(LS/SVD)的自适应算法来实现有记忆非线性功放的自适应基带预失真。仿真结果表明,该方案用于正交频分复用(OFDM)系统中能有效抑制带外频谱扩散,减小带内失真,实现有记忆非线性功率放大器的自适应预失真。     

宽带OFDM功放自适应数字预失真算法的研究与实现

针对宽带OFDM功放的线性化问题,本文提出了一种基于训练序列的递推最小二乘算法和最小均方算法的组合算法.并将其应用到基于多项式的数字预失真系统中以实现自适应数字预失真滤波器系数的估计和更新.本文首先介绍了整个数字预失真系统的组成架构;然后是自适应数字预失真算法的实现,使用MATLAB软件对其算法进行仿真验证;最后还组建了实验系统,进行了ACLR测试实验.仿真结果和测试结果均表明基于自适应数字顶失真算法的宽带线性化功放具有良好的性能,OFDM功放输出的线性度改善6dB.     

基于RLS算法的记忆多项式预失真技术分析

自适应数字基带预失真技术是功放线性化技术中很有前景的技术之一。为了能够使数字基带预失真系统快速收敛且便于工程应用,介绍了一种基于迭代最小二乘(RLS)算法的记忆多项式预失真技术,并论述了其基本原理和系统结构,最后从邻信道功率比(ACPR)、星座图以及误码率3个方面进行了仿真,结果表明基于该算法的预失真技术不仅可以克服传统LMS预失真算法收敛速度慢的缺点,而且便于结合QR分解等方法来硬件实现,预失真性能更优。     

无线通信中有记忆功率放大器的一种预失真方法

在WCDMA等宽带通信系统中,射频功率放大器记忆效应明显,传统的无记忆预失真技术无法达到理想的线性化效果.分析功放的记忆效应,并提出一种适合于有记忆射频功率放大器的顸失真方法.该方法首先基于记忆多项式构造预失真器,然后采用间接学习结构设计预失真系统,并运用限定记忆递推最小二乘算法更新预失真器参数,以跟踪放大器特性的变化.仿真结果表明,该方法能较好地补偿射频功放的非线性失真和记忆效应.     

基于二次样条函数的功放数字预失真算法

功放的非线性特性极易产生频谱扩展,这种扩展会对临近信道产生干扰。现在基于样条的预失真算法几乎都使用的三次样条,也就是样条的多项式函数阶数最多只有三次。文章提出了一种新的基于二次样条的功放数字预失真算法。二次样条函数的平滑特性可以很好地逼近功放的非线性模型,有效克服功放非线性效应对频谱产生的影响。仿真和实现的结果表明,这种新的算法性能既优于传统的基于最小均方的数字预失真算法,也优于现在一般的三次样条预失真算法。     

一种高效的用于RF功率放大器线性化的自适应预失真结构

分析了当前文献中主要的几种自适应预失真结构,发现这些自适应预失真结构均不利于高效最小二乘算法的直接应用,从而限制了预失真技术的自适应性能.提出了一种新的自适应预失真结构,可直接使用高效的最小二乘算法对预失真器进行自适应更新.仿真结果表明利用此结构可快速、高效地实现非线性RF功率放大器的线性化.     

适用于DLA结构的新型功率放大器数字预失真算法

数字预失真技术通过在功率放大器的前端级联数字预失真器来补偿功放的非线性失真,而直接学习结构(Direct Learning Architecture,DLA)作为一种广泛使用的自适应数字预失真算法结构,因其预失真性能优良,前景最为看好。传统DLA预失真算法需要求得功率放大器高精度模型,其结构复杂且计算量大。针对这一问题,文章引入功放的瞬时复增益(Instantaneous Complex Gain,ICG),提出了两种适用于DLA的新型功放预失真算法:ICG-LMS和ICGRLS,在确保线性化效果的同时,省略功放模型构建过程,大大简化了算法结构。仿真分析和实测结果表明,与传统适用于DLA的自适应预失真算法相比,两种新型预失真算法的运行时间分别减少35.8%和32.1%,而功放输出信号的邻道功率比与原始功放输出相比分别降低了14.8 dB和23.5 dB。     

数字预失真器模型参数辨识算法研究

数字基带预失真技术是补偿功放非线性的最有效方法之一,而自适应算法的选择很大程度上影响着系统的预失真性能。其中,最小均方误差(LMS)算法和递归最小二乘法(RLS)是最常用的自适应收敛算法,在综合分析两种算法优缺点的基础上,提出了一种基于正弦函数的归一化LMS(NLMS)算法和RLS算法的组合算法。仿真结果表明,该组合算法在达到与RLS同样预失真精度的前提下,可大大减小计算量。     

A Convergence-Free Predistortion Technique for Adaptive Linearisation of RF Power Amplifiers

Adaptive digital baseband predistortion is a well-known linearisation technique for removing intermodulation products that radio frequency power amplifiers (PAs) introduce. This paper proposes a new baseband predistortion method that is based on a non-iterative, fast adaptation algorithm without convergence restrictions. The response of the PA in a batch of training magnitude stimuli is used for the computation of the predistortion gain. The latter is directly extracted in rectangular form without prior transformations and AM/AM and AM/PM non-linearities sequential estimation. The influence of the gain table size and the imperfections of the modulator and demodulator in the method's performance are examined. Experimental measurements of an in-house prototype show a linearity improvement of about 25 dB.     

Frequency-Selective Predistortion Linearization of RF Power Amplifiers

This paper presents a frequency-selective RF vector predistortion linearization system for RF multicarrier power amplifiers (PAs) affected by strong differential memory effects. Differential memory effects can be revealed in two-tone experiment by the divergence for increasing tone-spacing of the vector Volterra coefficients associated with the lower and upper intermodulations tones. Using large-signal vector measurement with a large-signal network analyzer, a class-AB LDMOS RF PA is demonstrated to exhibit a strong differential memory effect for modulation bandwidth above 0.3 MHz. New frequency-selective RF and baseband predistortion linearization algorithms are proposed to separately address the linearization requirements of the interband and inband intermodulation products of both the lower and upper sidebands. Theoretical verification of the algorithms are demonstrated with Matlab simulations using a Volterra/Wiener PA model with memory effects. The baseband linearization algorithm is next implemented in a field-programmable gate array and experimentally investigated for the linearization of the class-AB LDMOS PA for two carrier wideband code-division multiple-access signals. The ability of the algorithm to selectively linearize the two interband and four inband intermodulation products is demonstrated. Adjacent channel leakage ratio of up to 45 dBc for inband and interband are demonstrated experimentally at twice the typical fractional bandwidth.     

G3-PLC系统压缩感知信道估计的LS-SAMP算法

为了提高G3-PLC系统可靠性,引入压缩感知(Compressed Sensing,CS)的信道估计方法,提出了一种基于最小二乘(Least Squares,LS)的稀疏度预测自适应匹配追踪(LS Based Prediction-Sparsity Adaptive Matching Pursuit,LS-SAMP)算法。该算法在稀疏度自适应匹配追踪(Sparsity Adaptive Matching Pursuit,SAMP)算法的基础上,采用了基于LS的稀疏度预测方法对信道稀疏度进行预估计,使算法可以快速逼近信道的真实稀疏度,提高算法运行效率;其次利用主成分分析方法对观测矩阵进行线性优化,降低观测矩阵相干度,提高算法的重构性能。实验结果表明,在误码率为10-3时,所提算法相对于LS算法的信道估计性能有1 dB的提升,且其运行效率比SAMP算法提升了31.23%,以更有效的方式提高了G3-PLC系统的可靠性。     

A least-squares/Newton method for digital predistortion of wideband signals

Power amplifiers (PAs) are essential in communication systems, but are inherently nonlinear. To achieve linearity with good efficiency, PA linearization is necessary. Digital baseband predistortion is a highly cost-effective way to linearize PAs, but most existing architectures assume that the PA has a memoryless nonlinearity. For wider bandwidth applications, such as wideband code-division multiple access, PA memory effects can no longer be ignored. Therefore, in order to achieve good linearization performance, the predistorter needs to also have memory structure. In this paper, we propose a new model for the wideband predistorter and a least-squares(LS)/Newton algorithm to estimate the model parameters. Performance of the LS/Newton algorithm is studied through computer simulations. Good linearization performance is achieved by using the new model in an experimental testbed.     

一种水下光通信中基于先验模型的预均衡方法

由于海水的散射特性,光在水下传输时会产生码间串扰(ISI)问题,传输环境较差时尤为严重。为解决该问题,文章将预均衡技术应用于基于直流偏置光正交频分复用(DCO-OFDM)调制的水下光通信系统中,并针对水下光的传输特性提出了一种基于先验信息的预均衡方法。在浑浊海港海水环境下与传统均衡算法进行了性能对比。仿真结果表明,在信噪比(SNR)较差的情况下,采用所提方法能够有效降低水下光通信系统的ISI,降低了误码可能性,提高了信道估计的可靠性。相比于最小二乘(LS)后均衡算法,误码率能下降约3.56 dB,相比于LS预均衡算法,误码率能下降约3.00 dB,相较于最小均方误差(MMSE)和最小均方(LMS)后均衡算法,误码率下降约1.85 dB。     

Neural-network-based adaptive baseband predistortion method for RF power amplifiers

An adaptive baseband predistortion method for RF power amplifier (PA) linearization is proposed and experimentally demonstrated. The predistortion component is implemented by a single-input dual-output multilayer perceptron (MLP). Both amplitude-to-amplitude and amplitude-to-phase distortion products are compensated by backpropagation training of the neural network including the response of the PA. Effects of modulator and demodulator imperfections on system performance are examined. Measurements on a system prototype reveal a significant linearity improvement that reaches 25 dB.     

基于改进型径向基函数神经网络的功放线性化

提出了一种基于改进型径向基函数神经网络(MRBFNN)的数字预失真线性化模型,用于更为精确地矫正宽带射频功率放大器的动态非线性。该神经网络模型的输入层使用传统的延时抽头以补偿功放的线性记忆效应,同时对每个抽头进行级数展开用于补偿功放的非线性记忆效应,从而更好地抑制功放的动态非线性失真。文中使用WCDMA 三载波信号对一个460MHz 的Doherty 功率放大器进行数字预失真线性化实验。实验结果表明,与传统数字预失真线性化模型相比,基于改进型径向基神经网络的数字预失真线性化模型能更好地抑制宽带功放动态非线性引起的带外频谱再生,其三阶互调(IMD3)失真最多可以抑制23dB,大大提高了功放的线性度,验证了所提出的数字预失真线性化模型的有效性。     

Adaptive polynomial predistorters for M‐QAM transmission using non‐linear power amplifiers

In this paper, adaptive baseband polynomial predistortion techniques are introduced to counter‐balance the AM/AM and AM/PM non‐linear effects of the transmit power amplifier. The proposed polynomial predistortion scheme is based on polar coordinate representation. Both LMS and RLS concepts are used to derive the adaptive algorithms. An enhanced LMS‐based algorithm with fast convergence and low complexity is proposed. For very fast convergence, a cascaded RLS‐based adaptive polynomial predistorter structure is introduced. The performance of the proposed schemes in terms of intermodulation distortion, spectral regrowth, and convergence rate are examined. The obtained results show that the polynomial predistortion schemes can be used in M‐QAM transmitters with power amplifiers operating near saturation to achieve a highest power efficiency. Copyright © 2006 John Wiley & Sons, Ltd.     

An adaptive predistorter for a power amplifier based on adjacentchannel emissions [mobile communications]

A slowly adapting predistorter is presented. The approach is to minimize the transmitter output power in spectral regions occupied only by intermodulation (IM) products. In this way, only a spot power measurement is required. This technique relies on the principle that the power amplifier's characteristics vary slowly with time. By monitoring the out-of-band power one can obtain an estimate for the distortion introduced by the power amplifier. Adaptation is accomplished by iterative adjustment of the predistorter parameters to minimize the IM power. For a polynomial predistorter, the authors analytically demonstrate that the IM power is a quadratic function of the coefficients. A variety of algorithms therefore apply. The authors present an analog static predistortion linearization circuit that uses the envelope of the baseband signal to generate the nonlinear functional used in predistorting the input signal. The improvement obtained with an amplitude-modulated input signal was 15 dB in the third- and 5 dB in the fifth-order intermodulation products. The IM improvement could be maintained with the use of a robust direct search algorithm