压缩感知在分段式双反馈预失真器的模型简化研究

针对预失真器中模型参数过多的问题,从压缩感知(compressed sensing, CS)的理论出发,提出了一种用于宽带射频功率放大器(power amplifier, PA)的预失真器模型简化方法。在稀疏度自适应匹配追踪(sparsity adaptive matching pursuit, SAMP)算法的基础上进行改进,提出了基于频域陷波的相关支集选择SAMP算法(RSS-FNSAMP)。该算法能够对PA行为模型进行简化,而后将其运用在提出的分段式双反馈DPD系统中,以补偿被带内残差所掩盖的带外失真,在增强了系统稳定性的同时降低了其复杂度,提升了DPD线性化效果。为了验证该方法,使用20 MHz LTE信号驱动一个35 dBm的F类功率放大器。实验结果表明,归一化均方误差(normalized mean squared error, NMSE)与ILA-SAMP、ILA-DOMP和分段式双反馈-DOMP相比提升了3～5 dB,相邻信道功率比(adjacent channel power radio, ACPR)改善了25 dBc,表明该方法能够在降低模型参数数目的同时,提升功放...     

动态压缩感知理论研究综述

动态压缩感知是静态传统压缩感知向动态信号的拓展,广泛应用于医学上的磁感应成像和目标追踪等领域。 由于工程 中的动态信号在某一转换基下具有随时间缓慢变化的稀疏特性,因而可以运用欠定的测量矩阵对其进行压缩。 动态压缩感知 理论主要包括动态信号的稀疏表示、动态压缩测量过程和动态信号的重构 3 个方面的研究内容。 全面综述动态压缩感知的基 本概念,归纳总结现有动态压缩感知理论中对动态信号的建模方法;对已有的动态信号重构算法进行了归类,并详述了各类算 法的计算思路;最后介绍了动态压缩感知的典型应用,并对动态压缩感知信号重构算法的研究前景进行了探讨。     

A new sparse design framework for broadband power amplifier behavioral modeling and digital predistortion

In this paper, we propose a new sparse framework for the design of the behavioral model and digital predistorter of a broadband power amplifier (PA). We start by formulating the Volterra kernel to multidimensional memory polynomial by considering the high‐order dynamic truncation of the Volterra model. Then we show how an estimate of the most significant coefficients may be obtained using a matching pursuit (MPT) algorithm by exploiting the sparsity of the model. After the indices of the nonzero coefficients are roughly estimated, the block exact Householder inverse QR‐decomposition‐based recursive least squares (HIQRD‐RLS) algorithm is utilized to estimate the sparse model complex coefficients. For broadband nonlinear PAs, the proposed approach is demonstrated to achieve the best performance among the well‐known traditional approaches in terms of in‐band and out‐of‐band specifications. The proposed approach is also validated by evaluating the digital predistortion (DPD) performance on a Class‐AB PA in terms of adjacent channel power ratio (ACPR). © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Power amplifier behavioral model adaptive pruning using conjugate gradient‐based greedy algorithm

Starting from the greedy theory, this paper presents a novel adaptive greedy scheme for the power amplifier (PA) behavioral model adaptive pruning. The proposed scheme incorporates the stochastic conjugate gradient (SCG) principle into the subspace pursuit (SP) greedy algorithm, which can considerably offer improved tracking capabilities and faster convergence compared to other anterior adaptive greedy algorithms. Compared to conventional nonsparse methods, simulation results show that the proposed scheme can efficiently reduce the model order and computational complexity but almost have the comparable model performance with the full model. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Zero‐attracting variable‐step‐size least mean square algorithms for adaptive sparse channel estimation

Recently, sparsity‐aware least mean square (LMS) algorithms have been proposed to improve the performance of the standard LMS algorithm for various sparse signals, such as the well‐known zero‐attracting LMS (ZA‐LMS) algorithm and its reweighted ZA‐LMS (RZA‐LMS) algorithm. To utilize the sparsity of the channels in wireless communication and one of the inherent advantages of the RZA‐LMS algorithm, we propose an adaptive reweighted zero‐attracting sigmoid functioned variable‐step‐size LMS (ARZA‐SVSS‐LMS) algorithm by the use of variable‐step‐size techniques and parameter adjustment method. As a result, the proposed ARZA‐SVSS‐LMS algorithm can achieve faster convergence speed and better steady‐state performance, which are verified in a sparse channel and compared with those of other popular LMS algorithms. The simulation results show that the proposed ARZA‐SVSS‐LMS algorithm outperforms the standard LMS algorithm and the previously proposed sparsity‐aware algorithms for dealing with sparse signals. Copyright © 2015 John Wiley & Sons, Ltd.     

Envelope tracking using transient waveform switching shaping supply modulation

A novel supply modulation scheme for envelope tracking for a power amplifier in a transmitter is proposed, which follows a control principle that is fundamentally different from the existing ones. Instead of regulating the supply modulator's output in accordance with a given reference signal, the system utilizes a look‐ahead window and synthesizes pulses for the supply modulator such that its output tracks the envelope of the radio frequency signal amplified by the power amplifier, while minimizing its switching rate. Simulation results for a 5 MHz Long Term Evolution signal with 16 quadrature amplitude modulation indicates that the proposed technique provides very high average efficiency (84%) while maintaining a very low ratio between the switching frequency and the envelope bandwidth. Copyright © 2013 John Wiley & Sons, Ltd.     

基于压缩感知的电力信号压缩与重构研究*

针对电力信号的采集和压缩问题,提出采用压缩感知理论对电力信号进行压缩采样和重构的方法,避免了传统的冗余采样。首先对采用压缩感知理论进行电能信号压缩采样的可行性进行了分析,并讨论了几种典型的压缩感知重构算法的具体实现方法和特性;然后采用这些算法,对一维稀疏信号和傅里叶变换基下稀疏的含有谐波和间谐波的电力信号进行重构实验。仿真结果表明,贪婪类压缩感知重构算法计算复杂度低、速度快,更适合一维电力信号的重构,其中SAMP算法可以在稀疏度未知的情况下,使用更少的采样值精确重构原始信号。     

Greedy approach to sparse multi‐path channel estimation using sensing dictionary

As most components of sparse multi‐path channel (SMPC) are zero, impulse response of SMPC can be recovered from a short training sequence. Although the ordinary orthogonal matching pursuit (OMP) algorithm provides a very fast implementation of SMPC estimation, it suffers from inter‐atom interference (IAI), especially in the case of SMPC with a large delay spread and a short training sequence. In this paper, an adaptive IAI mitigation method is proposed to improve the performance of SMPC estimation based on a general OMP algorithm. Unlike the ordinary OMP algorithm, a sensing dictionary is designed adaptively and posterior information is utilized efficiently to prevent false atoms from being selected due to serious IAI. Numeral experiments illustrate that the proposed general OMP algorithm based on adaptive IAI mitigation outperforms both the ordinary OMP algorithm and the general OMP algorithm based on non‐adaptive IAI mitigation. Copyright © 2011 John Wiley & Sons, Ltd.     

A novel strategy for inverse synthetic aperture radar imaging based on improved compressive sensing

In actual applications of inverse synthetic aperture radar (ISAR), continuous measurements may be impossible or the collection of data during some periods are not valid in a long coherent processing interval (CPI). Hence, it is significant to study the ISAR imaging strategy with a short CPI. Compressive sensing is a recently proposed technique that allows recovering an unknown sparse signal with overwhelming probability from very limited samples. However, the standard compressive sensing framework has been developed for real‐valued signals. One disadvantage of this method is that any prior phase information is not exploited, which may improve the reconstruction quality by applying some extra constraints. In this paper, a new strategy for ISAR imaging based on improved compressive sensing is proposed, which transforms the ISAR imaging problem into a joint optimization problem over the representation of the magnitude and phase of the complex‐valued scatter coefficient. Because of using phase information in the algorithm, the image quality is improved. Experimental results confirm the effectiveness of the proposed method. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

基于分布式压缩感知的双通道SAR GMTI

地面动目标检测(GMTI)是合成孔径雷达(SAR)的基本功能之一。多通道SAR系统相比于单通道SAR系统在动目标检测方面具有很多的优势,但是它的原始数据量也相应成倍的增长。本文提出一种基于分布式压缩感知(DCS)的双通道SAR GMTI数据压缩方案。该方案主要是利用动目标信号的稀疏性来进行数据压缩,因此在观测场景不稀疏的情况下也能使用。仿真和实测数据的处理结果均表明,该方案不仅能有效地降低双通道SAR GMTI的数据量,所得动目标图像的信杂噪比相对于传统的DPCA方法也有所提高。     

基于掩膜预处理的稀疏表示和压缩感知图像重建

近年来兴起的压缩感知（compressive sensing, or compressed sampling,CS）理论对信号稀疏性的要求,使信号的稀疏表示得到了前所未有的关注。考虑到现实信号往往是非稀疏性的,而压缩感知理论要求被测信号必须满足稀疏性或在某个规范正交基下满足稀疏性,因此信号的稀疏性表示变得十分重要。主要研究探索了二值掩膜预处理的稀疏表示方法。结合二值掩膜的算法去除人眼不敏感的DCT系数,在不影响图像主观质量的前提下提高测量系数的稀疏度。实验表明提出的预处理方法减少了CS的重建时间,并且提高了图像的重建质量。     

暂态和短时电能质量扰动信号压缩采样与重构方法

为解决传统的电能质量信号采集压缩方法所面临的采样率高、采样资源浪费及硬件实现成本高的问题,根据压缩传感理论首次提出了暂态和短时电能质量扰动信号的压缩采样与重构方法。该方法将电能质量信号由一维信号变换为二维信号,并根据图像可稀疏表示的原理,使用比Nyquist采样数据少60%以上的随机投影采样值重构原始信号,实现了对暂态和短时电能质量测量数据的压缩采样、采样数据空间稀疏基的选取和基于全变分最小化共轭梯度法的信号重构。针对几类常见单一扰动和含有多重扰动的校准源实测信号进行了算法的仿真分析和实验验证。结果表明,所提出的方法在采样率低于Nyquist采样率73%时,单一扰动的重构信号信噪比除暂态脉冲信号外均大于35dB,多重扰动的重构信号信噪比大于22d,满足电能质量分析的要求。     

基于压缩感知的稀疏阵列近景微波三维成像

近景微波成像技术在隐藏武器检测、生物医学成像、无损检测等领域具有广阔的应用前景.将压缩感知理论应用于近景微波成像系统,提出了基于稀疏阵列天线的三维成像几何及相应的回波模型,该几何通过高度向的稀疏阵列电子扫描、方位向的机械扫描及距离向发射宽带信号来实现三维分辨;文中将压缩感知理论应用于稀疏阵列三维成像,提出了基于压缩感知...     

Wide‐band aperture array using a four‐channel manifold‐type planar multiplexer and digital 2‐D IIR filterbank

Emerging wide‐band communications and spectrum‐sensing systems demand support for multiple electronically scanned beams while maintaining a frequency independent, constant far‐field beam width. Realizing existing phased‐array technology on a digital scale is computationally intensive. Moreover, digitizing wide‐band signals at Nyquist rate requires complex high‐speed analog‐to‐digital converters (ADCs), which is challenging for real developments driven by the current ADC technology. A low‐complexity alternative proposed in this paper is the use of radio‐frequency (RF) channelizers for spectrum division followed by sub‐sampling of the RF sub‐bands, which results in extensive reduction of the necessary ADC operative frequency. The RF‐channelized array signals are directionally filtered using 2‐D digital filterbanks. This mixed‐domain RF/digital aperture array allows sub‐sampling, without utilizing multi‐rate 2‐D systolic arrays, which are difficult to realize in practice. Simulated examples showing 14–19 dB of rejection of wide‐band interference and noise for a processed bandwidth of 1.6 GHz are demonstrated. The sampling rate is 400 MHz. The proposed VLSI hardware uses a single‐phase clock signal of 400 MHz. Prototype hardware realizations and measurement using 65‐nm Xilinx field‐programmable gate arrays, as well as Cadence RTL synthesis results including gate counts, area‐time complexity, and dynamic power consumption for a 45‐nm CMOS circuit operating at B _DC = 1.1 V, are presented. Copyright © 2016 John Wiley & Sons, Ltd.     

A new fast‐lock,low‐jitter,and all‐digital frequency synthesizer for DVB‐T receivers

Lock time and convergence time are the most important challenges in delay‐locked loops (DLLs). In this paper we cover French very high frequency band with a novel all‐digital fast‐lock DLL‐based frequency synthesizer. Because this new architecture uses a digital signal processing unit instead of using phase frequency detector, charge pump, and loop filter in conventional DLL, therefore, it shows better jitter performance, lock time, and convergence speed than previous related works. Optimization methods are used to make input and output signals of the proposed DLL in phase. The proposed architecture is designed to cover all channels of French very high frequency band by choosing number of delay cells in signal path. Simulation has been done for 22–27 delay cells, and f_REF = 16 MHz, which can produce output frequency in range of 176–216 MHz. Locking time is approximately 0.3 µs, which is equal to five clock cycles of reference clock. All of the simulation results show superiority of the proposed structure. Copyright © 2013 John Wiley & Sons, Ltd.     

稀疏频谱感知BigBand算法阈值选择研究

根据奈奎斯特采样定理,实时感知GHz数量级宽的频率,需要GHz以上的高速AD转换器.由于价格、功耗的限制,实际应用中较难实现.基于稀疏频谱感知的BigBand算法,针对环境中信号稀疏的情况下,通过多个50 MHz的AD转换器可以还原出0.9 GHz宽的频谱.本文针对稀疏频谱感知的BigBand算法中的阈值进行研究,通过对噪声的参数的统计特征进行理论分析,提出一种基于最先检测信号强度的概率密度的阈值设定方法,为稀疏频谱感知BigBand算法的实际应用提供了技术支撑.     

A fast second‐order signal separation algorithms with on‐line capabilities

In correlation‐based signal separation algorithms, the received mixed signals are fed to a de‐coupling system designed to minimize the output cross‐correlation functions. If minimizaion is perfect, each of the system's outputs carries only one signal independent of the others. In these algorithms, the computation burden of the output cross‐correlation functions normally slows down the separation algorithm. This paper, describes a computationally efficient method for off‐line pre‐computation of the needed cross‐correlation functions. Explicit formulas have been derived for the output cross‐correlation functions in terms of the received input signals and the de‐coupling system parameters. Then, it is shown that signal separation amounts to the least‐squares solution of a system of linear equations describing these output cross‐correlation functions, evaluated over a batch of lags. Next, a fast RLS‐type adaptive algorithm is devised for on‐line signal separation. In this respect, an algorithm is derived for updating the de‐coupling parameters as data comes in. This update is achieved recursively, along the negative of the steepest descent directions of an objective cost function describing the output cross‐correlation functions over a batch of lags, subject to equal output power constraints. Illustrative examples are given to demonstrate the effectiveness of the proposed algorithms. Copyright © 2002 John Wiley & Sons, Ltd.     

一种新的电能质量扰动信号压缩感知识别方法

针对现有电能质量扰动信号识别方法存在数据量大、准确率不高的不足,提出了一种基于压缩感知稀疏向量特征提取的电能质量扰动信号分类识别方法。该方法首先针对原始信号,利用压缩感知理论获取降维的测量信号,并基于?1范数正交匹配追踪算法获取稀疏向量。然后针对稀疏向量提取最大值、次大值、均方根、标准差、峭度和裕度因子等特征,作为神经网络的输入,实现电能质量扰动信号的分类识别。最后,针对六类典型电能质量扰动信号,开展仿真实验验证。仿真结果表明,现有识别方法需要处理的原始信号长度为1024,而所提方法特征提取时所处理的数据长度仅有30,从而大大减少了所需处理的数据量,并且由于实现了以非常少的数据量保存原有全部有用特征信息,因而更有利于提高识别准确率。通过与广泛采用的小波变换识别方法进行比较,所提方法的平均准确率高达98.71%,远远高于小波变换方法的92.86%。     

浮电位类型局部放电的高频传感特性的试验研究

为了了解局部放电类型对UHF传感方法灵敏度的影响,笔者采用10～80MHz、150～250MHz、300～800MHz3种频段的高频放大器对浮电位局部放电进行测量。试验选择了0.2、0.8、1.4mm3种浮电位放电间隙。随着放电间隙的增大,局部放电量增大,但300～800MHz频段检测信号的幅值减小。结果表明,UHF检测信号的幅值并不能准确反映局部放电的严重程度,建议采用多频段信号传感,根据多频段检测信号幅值的相对关系进行局部放电严重程度判别。     

An adaptive digital processor for power efficiency enhancement in hybrid supply modulators

A novel digital envelope modulator for envelope tracking radio frequency power amplifier is presented in this paper. The proposed modulator consists of a parallel combination of linear class AB and switching class D power amplifiers that are controlled digitally. In the previous analog architectures, the requirements needed for the AB operational amplifier such as high‐current driving capability, high bandwidth and large output swing is usually obtainable at high overall static power dissipation. The digitally controlled power opamp presented here not only provides the aforementioned requirements but also reduces power dissipation compared with previous work. Furthermore, the digital control of the modulator makes it adaptive to the input signal variations in comparison with conventional analog parallel hybrid envelope modulators. The digital processor of the modulator is evaluated with a 45‐nm complementary metal oxide semiconductor technology. The overall power consumption of the digital processor is around 142 mW at 1.5‐GHz clock frequency. As an application, the designed digital class AB is incorporated in a complete envelope modulator architecture. The overall efficiency of the modulator, including the digital processor power consumption, is around 82% at an average 32 dBm output power for a 5‐MHz input signal. Copyright © 2015 John Wiley & Sons, Ltd.