基于HPA特性曲线拟合的自适应预失真技术

提出了一种用于正交频分复用(OFDM)系统中补偿由大功率放大器引起的非线性失真的基带自适应预失真方法。自适应预失真器是基于对大功率放大器的非线性特性进行分段估计,由曲线拟合逐段取逆变换来训练大功率放大器的预失真器的非线性参数,以达到预是真补偿的目的。计算机仿真结果表明,该方法具有收敛速度快、需要动态存储器(RAM)少、补偿效果好等特点。     

宽带OFDM系统中的简化滤波查表预失真算法

为了解决宽带正交频分复用（orthogonal frequency division multiplexing, OFDM)系统中放大器有记忆非线性特性给系统带来的失真问题,提出了一种简化的滤波查表(simplified filter look up table, S FLUT)预失真方法。该方法由一个无记忆预失真器子系统串联一个自适应滤波器子系统构成,能有效解决放大器带来的失真问题,同时采用简化的自适应更新结构,可以弥补原滤波查表法反馈支路结构复杂、收敛精度低的缺点。     

基于正交模型辨识辅助的欠采样数字预失真方法

针对数字预失真技术在宽带通信系统中的具体实现受到模数转换器采样率制约的问题,提出一种新的欠采样数字预失真方法。首先在欠采样速率下对功放的正交模型进行离线辨识,接着根据一定的算法得到Nyquist采样率下的简化预失真器模型,并进行在线的自适应直接学习。该方法具有预失真器模型构造简单、欠采样实现高效的特点。理论分析和仿真结果表明,该方法有效降低了对模数转换器的采样率要求,优化了简化预失真器模型的线性化条件,更好地抑制了功放非线性引起的带内失真和频谱再生。     

考虑记忆交叉项的宽带功放行为建模方法

针对宽带功率放大器的强记忆效应,提出了一种前馈交叉记忆多项式模型。该模型由主信号对消和畸变注入两个环路构成。信号对消环路采用记忆多项式模型对带内动态线性记忆效应进行建模;畸变注入环路采用记忆时刻信号间的交叉记忆项对带外扩展频谱行为进行建模。为克服最小二乘法在模型辨识中带来的数值不稳定问题,采用共轭梯度的方法对模型的参数进行辨识。为消除噪声和测量误差对模型参数辨识带来的影响,采用ADS软件包络仿真的方法获取精确的功放输入输出信号复包络数据,并对该模型进行充分的性能分析和评估。实验结果表明,所提方法对宽带功放的非线性动态特性具有很好的逼近能力,特别是带外频谱扩展特性,较之常用的方法提升了近10 dB。     

基于传感器网络的标量量化器的设计

针对分布式编码在无线传感器网络研究中的重要性,着重研究了分布式编码中标量量化器的设计,分析设计最优标量量化器所存在的问题,提出了一种线性组合失真和速率的率失真数学模型。在此模型上,采用了一种改进的Lloyds迭代算法。通过仿真证明,此算法比传统的算法更能保证标量量化器的最优性或局部最优性。     

卫星信道中基于部分解耦的volterra均衡算法

对信道中大功率放大器产生的非线性特性实现快速有效地均衡是提高卫星通信系统性能关键技术之一。文中首先建立了基于volterra级数的卫星信道模型,并分析了信道对二维调制信号所产生的非线性影响;针对基于最小均方误差实现的volterra均衡器收敛速度慢这一问题,提出了基于复基带volterra模型的部分解耦均衡算法,该算法使均衡器线性权系数收敛于线性滤波器最优解,并用拉格朗日乘数法构造了新的代价函数,使均衡器的各阶权系数满足约束,以达到均衡器各阶权系数之间的解耦。仿真结果表明,新算法在保证稳态误差的条件下,其收敛所需迭代次数相对于全耦合的最小均方误差算法从16 000次减小到1 000次。     

基于小波变换的非线性信道判决反馈均衡算法

针对严重线性失真和轻度非线性失真的数字信道 ,在分析一种基于关联模型的非线性信道判决反馈均衡器的基础上 ,提出用正交小波表示非线性信道判决反馈均衡器并给出了自适应均衡算法。该算法的优点是将小波变换与关联模型相结合 ,利用小波变换的去相关能力在小波域中通过归一化的最小均方误差 (LMS)算法来提高收敛速度 ,计算量增加不多 ,易于实时实现。仿真结果表明 ,该算法具有良好的收敛性能     

线性插值基的数字预失真方法

随着射频功率放大器的发射功率不断提升,特别是Doherty功放的广泛应用,使得功放的非线性特性不断增强。为了满足高线性化的需求,数字预失真(digital pre distortion, DPD)技术要求达到更优的非线性校正效果。提出一种基于线性插值基的数字预失真方法,所提方法将线性插值基引入到数字预失真的行为建模中,达到优化的非线性校正效果。同时所提方法通过与查找表的实现方式结合,非常利于系统应用。仿真实验中采用20 MHz长期演进(long term evolution, LTE)信号进行实验,新方法较广义记忆多项式方法在临道泄露比指标上改善了近7 dBc以上。     

BICM-OFDM中基于ML算法的迭代信道估计

基于最大似然估计(ML),提出了一种新的联合译码的迭代信道估计算法。该算法利用比特交织编码调制(BICM)中迭代译码的硬判决信息,进行信道估计与译码之间的信息交换。在基于BICM的OFDM系统(BICM-OFDM)中,在短波宽带信道下的仿真结果表明,经过4次迭代,系统的误码率性能收敛。与传统ML算法相比,算法可有效的提高估计精度。     

一种基于分数采样的混合盲均衡算法仿真研究

在数字通信中,盲均衡是克服多径衰落信道导致的码间干扰的一种有效方法。超指数盲均衡算法的迭代算法收敛速度快,且便于跟踪时变信道。同时由于实际信道往往为非最小相位系统,此时线性均衡器性能不佳。因此针对严重频率衰落和非线性相位失真信道,提出了一种分数采样的混合盲均衡算法,并获得了较快的收敛速度和较小的剩余均方误差。仿真结果证明了该算法的有效性。     

Volterra series based predistortion for broadband RF power amplifiers with memory effects

RF power amplifiers(PAs)are usually considered as memoryless devices in most existing predistortion techniques.However,in broadband communication systems,such as WCDMA,the PA memory effects are significant,and memoryless predistortion cannot linearize the PAs effectively.After analyzing the PA memory effects,a novel predistortion method based on the simplified Volterra series is proposed to linearize broadband RF PAs with memory effects.The indirect learning architecture is adopted to design the predistortion scheme and the recursive least squares algorithm with forgetting factor is applied to identify the parameters of the predistorter.Simulation results show that the proposed predistortion method can compensate the nonlinear distortion and memory effects of broadband RF PAs effectively.     

Volterra series based predistortion for broadband RF poweramplifiers with memory effects

RF power amplifiers （PAs） are usually considered as memoryless devices in most existing predistortion techniques. However, in broadband communication systems, such as WCDMA, the PA memory effects are significant, and memoryless predistortion cannot linearize the PAs effectively. After analyzing the PA memory effects, a novel predistortion method based on the simplified Volterra series is proposed to linearize broadband RF PAs with memory effects. The indirect learning architecture is adopted to design the predistortion scheme and the reeursive least squares algorithm with forgetting factor is applied to identify the parameters of the predistorter. Simulation results show that the proposed predistortion method can compensate the nonlinear distortion and memory effects of broadband RF PAs effectively.     

Design of a memory polynomial predistorter for wideband envelope tracking amplifiers

Efficiency and linearity of the microwave power amplifier are critical elements for mobile communication systems. A memory polynomial baseband predistorter based on an indirect learning architecture is presented for improving the linearity of an envelope tracing (ET) amplifier with application to a wireless transmitter. To deal with large peak-to-average ratio (PAR) problem, a clipping procedure for the input signal is employed. Then the system performance is verified by simulation results. For a single carrier wideband code division multiple access (WCDMA) signal of 16-quadrature amplitude modulation (16-QAM), about 2% improvement of the error vector magnitude (EVM) is achieved at an average output power of 45.5 dBm and gain of 10.6 dB, with adjacent channel leakage ratio (ACLR) of -64.55 dBc at offset frequency of 5 MHz. Moreover, a three-carrier WCDMA signal and a third-generation (3G) long term evolution (LTE) signal are used as test signals to demonstrate the performance of the proposed linearization scheme under different bandwidth signals.     

Robust power amplifier predistorter by using memory polynomials

In memory polynomial predistorter design, the coefficient estimation algorithm based on normalized least mean square is sensitive to initialization parameters. A predistorter based on generalized normalized gradient descent algorithm is proposed. The merit of the GNGD algorithm is that its learning rate provides compensation for the independent assumptions in the derivation of NLMS, thus its stability is improved. Computer simulation shows that the proposed predistorter is very robust. It can overcome the sensitivity of initialization parameters and get a better linearization performance.     

基于MCMC的OFDM系统脉冲噪声检测与抑制方法

为解决正交频分复用系统(orthogonal frequency division multiplexing,OFDM)中存在脉冲噪声干扰降低系统链路可靠性的问题,提出基于马尔可夫蒙特卡罗(Markov chain Monte Carlo,MCMC)的turbo迭代均衡检测方法。首先给出OFDM系统发射机和接收机模型;然后分析给出未知变量的先验分布及其在已知接收信号条件下的条件分布,通过MCMC均衡器抽样估计得到信道和脉冲噪声的参数信息;最后给出turbo迭代结构的具体实现过程。仿真结果表明,在加性高斯白噪声(additive white Gaussian noise,AWGN)信道和多径信道中,该方法可以有效降低OFDM系统中脉冲噪声影响,提高系统可靠性