RF Power Amplifier Behavioral Modeling Based on Takenaka–Malmquist–Volterra Series

In this paper, a Takenaka–Malmquist–Volterra (TMV) model structure is employed to improve the approximations in the low-pass equivalent behavioral modeling of radio frequency (RF) power amplifiers (PAs). The Takenaka–Malmquist basis generalizes the orthonormal basis functions previously used in this context. In addition, it allows each nonlinearity order in the expanded Volterra model to be parameterized by multiple complex poles (dynamics). The state-space realizations for the TMV models are introduced. The pole sets for the TMV model and also for the previous Laguerre–Volterra (LV) and Kautz–Volterra (KV) models are obtained using a constrained nonlinear optimization approach. Based on experimental data measured on a GaN HEMT class AB RF PA excited by a WCDMA signal, it is observed that the TMV model reduces the normalized mean-square error and the adjacent channel error power ratio for the upper adjacent channel (upper ACEPR) by 1.6 dB when it is compared to the previous LV and KV models under the same computational complexity.     

A New Digital Predictive Predistorter for Behavioral Power Amplifier Linearization

This letter presents a new digital adaptive predistorter (PD) for power amplifier (PA) linearization based on a nonlinear auto-regressive moving average (NARMA) structure. The distinctive characteristic of this PD is its straightforward deduction from the NARMA PA model, without the need of using an indirect learning approach to identify the PD function. The PD itself presents a NARMA structure, and hence it can be quickly implemented by means of lookup tables. Single and multicarrier modulated signals collected from a three-stage LDMOS class AB PA, with a maximum output power of 48-dBm CW have been used to validate the linearity performance of this new predictive predistorter     

基于模糊逻辑的射频功放建模

提出了一种基于模糊逻辑的射频功放行为模型的建模方法.利用了模糊逻辑的万能逼近能力,对射频功放电路外部端口动态特性进行了准确的建模,并将模型计算得到的稳态输出电压,功率压缩特性和增益压缩特性曲线与ADS软件仿真结果进行了比较,取得了较好的效果,证明建模方法的有效性.     

非线性射频功率放大器行为模型的分析与比较

为了设计和优化高线性功率放大器和通信子系统,系统级仿真中,构建功率放大器精确的行为模型是必要的.这篇文章阐述了功率放大器行为模犁的概念与类犁,详细给出了各种行为模型的算法,分析和比较了这些行为模型的适用情况和性能,同时提出了两种改进模型.通过分析和比较得出:当指定输入信号的类型、带宽和工作频率时,根据模型性能及其复杂度,能够选择一种合适的行为模型来表示功率放大器的特性;最后给出了射频功率放人器行为模型选择的原则.     

Comparison of the Behavioral Modelings for RF Power Amplifier With Memory Effects

In this letter, three different kinds behavioral models are introduced to analyze the performance of power amplifiers (PAs) with strong memory. Among these models, the non-uniform delay memory polynomial model is compared with the traditional memory polynomial model for analyzing effect of sparse delays, and the enhanced memory polynomial model for evaluating nonlinear memory effect. Finally, a WiMAX Doherty-structure LDMOS PA is measured and three models are extracted from measured output of the PA. The result proves that the model complexity can be greatly reduced with non-uniform delays and the model precision improved with nonlinear memory model.      

基于神经网络的功率放大器预失真建模

提出一种神经网络结合分离信号对功率放大器预失真建模的方法。将输入/输出信号的线性与非线性部分分开处理,利用神经网络良好的逼近能力,采用LM算法,拟合出功率放大器特性曲线,进而建立预失真模型,使非线性功率放大器的输入/输出曲线整体呈线性化。在保证输出幅度限制和输出功率最大化的前提下,与未作信号分离的神经网络建模方法、多项式建模方法以及Saleh函数模型方法相比较,发现信号分离神经网络建模方法能得到较小的归一化均方误差和误差矢量幅度。仿真结果表明,采用信号分离神经网络对功率放大器及其预失真建模,整体线性化误差较小、精度高、效果更佳。     

基于时间功率混合分段模型的磁共振功放非线性建模

为了能够对磁共振功放的强分叉非线性进行精确建模,提出一种时间功率混合分段模型。时间功率混合分段模型是针对磁共振功放的激励为辛格脉冲信号时的精确非线性模型。所提出的模型基于辛格脉冲信号的特点进行时域和幅度域分段,从而能够对磁共振功放的分叉非线性进行精确建模。采用辛格脉冲信号作为测试信号,测试信号的占空比为5%,设计输出峰值为18 kW 的1.5 T 磁共振功放(工作频率63.89 MHz)作为测试功放进行模型的有效性验证。实测磁共振功放和模型的AM/AM 和AM/PM 曲线的比较结果表明,时间功率混合分段模型能够对磁共振功放的分叉非线性进行精确建模。同时,所提出模型的归一化均方误差(NMSE)比记忆多项式、广义记忆多项式模型和时分多项式模型分别提高10.7 dB, 10.3 dB 和14.7 dB。     

基于QR—RLS脉动阵列的非线性功放建模

在宽带通信系统中,功率放大器表现出明显的记忆效应,无记忆模型无法准确描述其输入输出特性.采用Hammerstein模型预测实际宽带发射机的记忆效应,并用脉动阵列的QR-RLS算法实现了快速高效的参数提取,不仅具有良好数值稳定性、减小了运算量和数据存储空间,而且易于在FPGA中实现.     

基于PSO_BP神经网络的射频功放行为模型

神经网络具有模拟任意非线性系统的优势。考虑到射频功放的非线性和记忆效应,在BP神经网络模型的基础上,提出一种基于PSO的BP神经网络射频功放行为模型。利用飞思卡尔(Freescale)半导体晶体管MRF6S21140器件模型及设计的电路,从ADS中导出输入输出数据,对模型进行了仿真实现,得出输出电压幅度的拟合曲线以及均方根误差,并与BP神经网络模型进行比较。仿真结果表明,所提模型具有较高的精度和较好的逼近能力,可以精确模拟功率放大器的特性,对系统仿真的构建具有重要的应用价值。     

可重构功放的新颖NARX神经网络逆向建模研究

针对使用CAD软件设计射频微波电路繁琐且耗时长等缺点,提出一种新颖的带外部输入的非线性自回归(NARX)神经网络逆向建模方法。此方法采用具有激励函数的NARX 神经网络(DAFNN)为模型以提高网络的泛化能力,利用支持向量机(SVM)替代模型的前馈部分完成数据分类,解决设计中的多解问题。然后应用于可以覆盖多个频段的可重构功率放大器中,实验表明,该方法在精度方面分别优于直接逆向建模方法和自适应浊逆向建模方法99.86%和81.32%,计算速度方面优于直接逆向建模方法31.72%,可以降低射频微波可重构功率放大器的设计复杂度、缩短其设计时间。     

Heuristic Algorithms for Constructing Binary Constant Weight Codes

Constant weight binary codes are used in a number of applications. Constructions based on mathematical structure are known for many codes. However, heuristic constructions unrelated to any mathematical structure can become of greater importance when the parameters of the code are larger. This paper considers the problem of finding constant weight codes with the maximum number of codewords from a purely algorithmic perspective. A set of heuristic and metaheuristic methods is presented and developed into a variable neighborhood search framework. The proposed method is applied to 383 previously studied cases with lengths between 29 and 63. For these cases it generates 153 new codes, with significantly increased numbers of codewords in comparison with existing constructions. For 10 of these new codes the number of codewords meets a known upper bound, and so these 10 codes are optimal. As well as the ability to generate new best codes, the approach has the advantage that it is a single method capable of addressing many sets of parameters in a uniform way.     

异步I/O连接算法的峰值功率建模

峰值功率是影响数据中心能效的一个重要因素.本文提出一种功率感知数据库系统中连接算法的峰值功率估算方法,非运行时峰值功率的估算的挑战在于没有运行时的系统信息作为模型的输入.为克服估算困难,提出使用CPU密集度作为CPU功耗指示量,理论上分析了异步I/O连接算法在峰值功率发生阶段的特性,通过模拟连接算法峰值功率发生阶段算法行为来估算该阶段最大CPU密集度,通过CPU密集度与CPU功率的内在联系建立异步I/O连接算法的峰值功率预测模型.实验对数据库系统中采用异步I/O机制的四个连接算法时模型准确性进行了验证,结果表明所提预测方法具有较好的预测准确性,平均相对误差低于7%.     

基于编码—解码模型的D类功率放大器行为建模

D类功率放大器具有优异的传输效率,属于开关类功放,其输出信号存在较大的非线性失真。对D类功率放大器进行行为建模时要同时考虑其非线性和记忆特性。文中将小波变换引入到编码—解码神经网络模型中,提出了小波编码—解码神经网络模型。使用基于门限循环单元的编码—解码模型和小波编码—解码模型进行D类功率放大器的行为建模。实验结果表明,文中提出的D类功率放大器行为模型相比于传统的Voterra-Laguerre模型而言,在信号的时域和频域都具有更高的精度。     

基于MC FQRD RLS算法的功放建模方法

在地面广播电视传输系统中,为了提高效率,功率放大器通常工作在非线性区.由此引入的非线性,必须进行校正.如果能够得到功率放大器的非线性模型,校正工作就能取得很好的效果.提出了一种基于多通道快速QR分解RLS算法的建模方法.传统的QRD RLS算法具有收敛速度快和数值稳定的优点.但其缺点是算法的计算量很大,对硬件资源的需求...     

双分支Hammerstein-Wiener射频功放行为建模及预失真

提出一种新的双分支Hammerstein-Wiener模型,对功放进行非线性行为建模及数字预失真研究.利用飞思卡尔半导体公司的MRF7S21170晶体管进行功放电路设计,从ADS中导出输入输出数据进行模型验证和预失真分析.仿真结果表明,该模型性能优于Hammerstein,Wiener和记忆多项式模型,具有较高的精度,能够精确模拟功率放大器的特性,经过数字预失真后,能抑制功放非线性引起的带内失真和频谱再生,对功放线性化技术的发展具有重要的应用价值.     

Approximation and Heuristic Algorithms for Minimum-Delay Application-Layer Multicast Trees

In this paper we investigate the problem of finding minimum-delay application-layer multicast trees, such as the trees constructed in overlay networks. It is accepted that shortest path trees are not a good solution for the problem since such trees can have nodes with very large degree, termed high-load nodes. The load on these nodes makes them a bottleneck in the distribution tree, due to computation load and access link bandwidth constraints. Many previous solutions limited the maximum degree of the nodes by introducing arbitrary constraints. In this work, we show how to directly map the node load to the delay penalty at the application host, and create a new model that captures the trade offs between the desire to select shortest path trees and the need to constrain the load on the hosts. In this model the problem is shown to be NP-hard. We therefore present an approximation algorithm and an alternative heuristic algorithm. Our heuristic algorithm is shown by simulations to be scalable for large group sizes, and produces results that are very close to optimal     

Dynamic Behavioral Modeling of Power Amplifiers Using ANFIS-Based Hammerstein

This letter presents a novel structure for the dynamic behavioral modeling of radio frequency power amplifiers (RF PAs) with ANFIS-based Hammerstein model for memory effects. The model is an adaptive neuro-fuzzy inference system (ANFIS) followed by a finite impulse response (FIR) filter. A hybrid learning algorithm is adopted to identify the parameters of the ANFIS. The parameters of the FIR filter are estimated by a straightforward least-squares method. The input and output signals of the PA excited with a three-carrier WCDMA signal were sampled for the model identification and validation in a test bench. Experimental results in the frequency and the time domains show that the proposed model was able to give an accurate approximation to characterize the wideband RF PAs.     

C312-1型大功率LDMOS功率管外壳

<正>LDMOS功率管在雷达、无线通讯基站、无线广播发射塔等电子系统中具有广泛的应用,而该类器件对外壳的散热和可靠性有很高的要求。南京电子器件研究所最近研制成一种用于封装300 W LDMOS功率管的高可靠外壳—C312-1型多层陶瓷外壳,具有比较优异的性能。该外壳由金属底板、陶瓷框架和陶瓷盖板组成,器件采用金锡封帽工     

基于射频功放非线性建模的欺骗干扰识别

针对欺骗干扰信号在时域、频域、空域与真实信号重叠,导致识别欺骗干扰的难度较大,假定真实发射机与欺骗干扰机射频前端器件除功放模块外均工作于理想状态,提出了一种基于射频功放建模的欺骗干扰识别方法。首先,利用Hammerstein模型对射频功放进行非线性建模,以模型参数作为提取的特征向量;其次,基于统计检测理论识别欺骗干扰;最后通过实验验证了方法的有效性,并与基于信号双谱特征的识别方法进行性能对比。实验结果表明,基于射频功放建模的欺骗干扰识别方法能够有效地识别欺骗干扰,且优于基于信号双谱特征的识别方法。