基于LMS算法的智能天线自适应波束形成研究

自适应波束形成是智能天线的核心技术,其主要思想是利用自适应算法调整阵列的权向量,将各阵元接收到的信号进行加权求和,把天线阵列形成的波束"导向"到一个方向上,使期望用户信号方向得到最大的增益,并相应地使干扰信号方向得到较低的增益,从而提高系统的性能。本文对智能天线中的自适应波束形成进行研究,运用MATLAB软件对固定步长和变步长LMS算法进行计算机仿真实验。仿真结果表明,基于LMS算法的自适应波束形成器能够形成符合要求的波束图,变步长的LMS算法均方误差收敛效果较好,收敛速度更快,具有较强的实用性。     

基站阵列接收方案的一种盲自适应算法

本文主要叙述了一种基站阵列接收方案中的盲自适应算法。在此算法中,我们使用一般的信息位作为训练信号来实现智能天线权值的更新。本方法的贡献在于,和导频位辅助LMS—DRMTA算法一样比传统的LS—DRMTA算法大大降低了运算量,同时该算法比导频位辅助LMS—DRMTA算法获得了更好的误码率、系统容量以及更好的波束图。     

智能天线数字波束形成的LMS-DRMTCMA算法

本文提出一种适用于TD-SCDMA智能天线系统数字波束形成的LMS(最小均方)解扩重扩多目标恒模阵列(LMS-DRMTCMA)算法。该算法通过将Z.Rong等提出的LS解扩重扩多目标恒模阵列(LS-DRMTCMA)参考信号形成方法应用到LMS算法,并将TD-SCDMA标准提供的训练序列用于加速算法的收敛,使运算量远低于LS-DRMTCMA算法,明显低于导频LMS解扩重扩多目标阵列(LMS-DRMTA)算法。LMS-DRMTCMA算法还适用于激活用户数远大于天线阵元数的移动通信系统。仿真实验表明,LMS-DRMTCMA算法比LS-DRMTCMA算法和导频LMS-DRMTA算法具有更低的误码率,适合在极低信噪比环境中工作。LMS-DRMTCMA算法具有运算量低、易于实时实现的特点。     

一种应用于OFDM系统的波束形成方法

根据OFDM信号的特点,在深入分析使用训练序列和导频符号进行波束形成这2类算法的基础上,提出一种适用于无线局域网分组传输情况下的波束形成方法,此方法结合了上述2类算法的优点,同时使用训练序列和导频符号在时域进行波束形成。在瑞利衰落信道下的计算机仿真结果表明,该算法有较好的性能。     

智能天线自适应波束形成算法的研究

智能天线的自适应算法通过迭代运算获取用于波束形成的最优权值矢量时,是否具有较快的收敛速度和较小的稳态误差成为决定波束形成性能的主要因素。据此提出在传统的LMS算法中引入变步长和变换域的思想,采用改进的自：适应算法用于波束形成。MATLAB仿真结果表明,该算法具有较快的收敛速度和较小的稳态误差,波束形成的性能更优。     

基于LMS算法的天线波束方向图仿真研究

最小均方（LMS）算法是一种常用的天线波束形成算法。本文首先对LMS算法的一般原理进行了研究,然后对LMS算法进行了改进,将固定步长改为变步长,最后应用Matlab对算法进行了仿真。仿真结果表明改进的LMS算法具有良好的效果,收敛速度比经典LMS算法更快,对天线性能有一定的提高。     

一种稳定的变步长块LMS自适应算法

针对LMS自适应滤波算法在输入信号高度相关时.收敛速度下降导致性能下降,本文从基本的块LMS算法开始,简要介绍了块LMS算法的实现方法,在此基础上重点分析了在变步长块LMS算法中,影响步长因子的要素.提出了一种新的变步长因子迭代算法(SVBLMS),该迭代算法充分考虑输入信号和误差信号对变步长因子的影响.并且迭代的结构简单,计算量小.通过Matlab仿真.仿真结果表明.该迭代算法较其它块LMS算法有更快的收敛速度,更稳定的收敛过程.当输入为有色信号或输入噪声较大时,本算法都能保持良好的性能.     

顽健自适应波束形成算法

针对方向向量偏差会导致最小均方(LMS)算法的性能急剧下降这一问题,提出了一种基于可变对角载入的顽健自适应波束形成算法.采用最陡下降法对信号方向向量进行优化求解,并在每次迭代过程中更新对角载入值,进而求出最优的权重向量,避免了矩阵求逆运算和特征值分解运算,大大降低了计算复杂度.通过建立步长与输入信号的关系得到可变的步长因子,克服了收敛速度和稳态误差之间的矛盾.该算法收敛速度快,抗扰动性强,对信号方向向量偏差具有很强的顽健性,从而改善了阵列输出的信干噪比,使其更接近最优值.理论分析和仿真结果表明与传统自适应波束形成算法相比,所提顽健算法具有更好的性能.     

一种变步长LMS波束形成算法性能研究

智能天线的自适应算法通过迭代运算获取波束形成的最优权值矢量时,收敛速度和稳态误差是衡量一个算法是否优良的关键因素。它们的好坏直接影响着系统波束形成的性能。系统地分析了传统的最小均方（LMs）算法的收敛速度以及稳态误差的性能,在此基础上提出了一种新的变步长LMS算法,将此算法应用于波束形成,并用Matlab软件进行仿真。仿真结果表明,改进后的算法较传统LMS具有较快的收敛速度和较小的稳态误差。     

自适应频移滤波器的优化设计与实现

本文利用信号的循环平稳性研究分离频谱重叠信号的频移滤波器。通过对循环平稳性和频谱相关性的分析,设计了一种频移滤波器,并采用变步长LMS（Least Mean Square）自适应算法计算多个频移分量的最优权值系数。仿真结果表明,该算法可有效分离频谱重叠信号,效果远好于传统滤波器。最后,在DSP平台上实现了设计的频移滤波器。     

智能天线中导频符号辅助的载波频偏估计

首先定量分析了智能天线的阵元和导频符号数目增减对频偏估计性能的影响;然后借助于自适应阵加权结构,提出了一种存在共信道干扰(CCI)时,导频辅助估计频偏的新算法,该方法的自适应权只是中间变量,所以并不需要系统真正采用自适应结构,也不需要已知天线阵列流形.计算机仿真表明,该算法可以充分地利用多阵元和导频符号,有效抑制了CCI,使频偏估计性能接近于克莱美-罗界.     

平衰落信道下ML和MAP信道估计与导频符号长度的关系性能比较

信道估计是无线通信系统必须加以解决的关键技术之一，采用导频符号辅助的方法进行信道估计是目前各类无线通信系统常用的方法。本文针对平衰落信道提出了最大似然(ML)算法和最大后验概率(MAP)估计算法，给出了ML估计和MAP估计之间的关系，仿真了MAP估计和ML估计的方差与导频符号长度的关系，提出当导频符号长度的取值超过20个符号长度时，MAP信道估计明显优于ML信道估计。     

A FADE-COMPENSATION TECHNIQUE FOR DIGITAL LAND MOBILE SATELLITE SYSTEMS

This paper proposes a novel fade-compensation algorithm using a pilot symbol-aided technique for digital and mobile satellite systems. In a conventional pilot symbol-aided system, a pilot symbol from a known pseudorandom-symbol sequence is inserted periodically into the data-symbol sequence in the transmitter. At the receiver, these pilot symbols are extracted from the received signal and used to estimate the signal distortion introduced in the fading channel. The resultant estimate is then used to correct the fading effects in the received data symbols. In this paper, a novel fade-compensation technique that uses both the pilot symbols and the data symbols is proposed. A series of computer-simulation tests has been carried out to assess the effectiveness of the technique on the bit-error-rate (BER) performances of an uncoded 16-ary phase-shift keyed (16PSK) and an uncoded 16-ary quadrature-amplitude modulated (16QAM) signal over the land mobile satellite channels. The results have shown that substantial improvements in the BER performances of the systems can be obtained, compared to those using only the pilot symbols.     

自适应系统中导频设计方案的研究

该文的目的是在导频辅助的自适应编码调制系统中,实现导频资源的优化配置,并研究新的设计方案对自适应系统性能的影响。利用衰落信道的二阶统计特性,以及信道的采样定理原理,推导出用以确定导频符号间隔的新算法,并由此定义了导频间隔的局部量和全局量,最终证明由新的导频间隔定义算法得到的局部量具有自适应特性,并且全局量是导频间隔的一个更紧更有效的上界。     

Detection of OFDM Signals in Fast-Varying Channels With Low-Density Pilot Symbols

In fast-varying channels, an orthogonal frequency-division multiplexing system needs to insert denser pilot symbols among transmitted symbols in tracking the variation of a channel. However, using denser pilot symbols reduces transmission throughput. In this paper, we propose a pseudopilot algorithm for data detection in fast-varying channels without increasing the pilot density. Our algorithm is based on a regressional model-based least-squares-fitting approach. Within a block of received symbols, we select some data symbols and regard them as pseudopilot symbols. The receiver considers all the possible patterns of the pseudopilots and associates each of them with a data sequence and a corresponding metric. The associated data sequence, whose metric is minimum, is selected as the detected data sequence. Our algorithm is not based on a decision-directed or decision-feedback architecture because the pseudopilots do not come from any detected symbols. The proposed algorithm needs to search all the possible patterns of the pseudopilots, and the complexity may increase with the number of pseudopilots and constellation size. To reduce the number of search, we further propose two modified approaches. The simulation results show that the performance of the proposed algorithms could approach a bit-error probability lower bound that is obtained by letting the receiver know the true values of the pseudopilots. Compared with the linear interpolation method, the proposed algorithm shows obvious improvement in fast-varying channels. The proposed modified approaches could also effectively reduce the number of search while maintaining the performance. We also give the complexity analysis of the proposed algorithm and an approach to determine the degree of the regression polynomial.     

一种基于分散导频块的频偏估计新算法

针对短突发信号解调的需要,提出了一种基于分散导频块的频偏估计新算法。区别于以往基于连续导频的频偏估计算法,该算法除利用了导频本身已知信息外,还充分利用了导频的位置信息。在相同的帧效率下,相比于基于连续导频的频偏估计算法,该算法可以获得更好的估计性能。理论分析和仿真结果都表明,该算法在其无偏估计范围内估计性能达到了相应帧结构下的克拉美罗界。     

WCDMA上行链路中的一种有效的RAKE接收方案

在WCDMA系统上行链路中，提出把智能天线与RAKE接收机相结合，利用上行链路的帧结构特征，将各时隙的导频符号的扩频序列作为阵列处理部分的LMS自适应算法更新阵元权矢量的参考信号，来解决CDMA系统反向信道的容量受限问题。仿真实验结果表明该方法能显著提高系统的容量，且简单易行。     

Time-Varying and Frequency-Selective Channel Estimation with Unequally Spaced Pilot Symbols

In this paper, an accurate and computationally efficient algorithm is proposed for estimating time-varying and frequency-selective fading channel with unequally spaced pilot symbols. By employing the time-varying coefficient polynomial interpolation method, it is proved that the time-varying channel impulse response can be estimated by the product of a constant matrix and the fading information at pilot symbol positions. Furthermore, a least square off-line training algorithm is presented to optimally calculate the constant matrix, taking into consideration of the statistics of channel fading and noise. The new algorithm can also be applied for estimating flat fading channel with equally spaced pilot symbols as a special case. Simulation results indicate that our new channel estimation algorithm leads to small mean square error for fading estimation and provides bit error rate performance close to that of the perfect channel estimation.     

Pilot-Assisted and Blind Joint Data Detection and Channel Estimation in Partial-Time Jamming

We consider a communication scenario in which a message is received in the presence of partial-time Gaussian jamming and additive white Gaussian noise. We consider a quasi-static channel, in which the amplitude and phase are constant over each packet transmission. The receiver does not know the amplitude and phase of the incoming signal, which symbols are jammed, or even the statistics of the jammer, such as the jamming power and jamming probability. In this scenario, the receiver must accurately estimate the parameters of the channel and the jamming to achieve good performance. We apply the expectation-maximization (EM) algorithm to iteratively approximate the maximum-likelihood (ML) estimator for all of the parameters. We find that the overall performance of the EM algorithm is very sensitive to the initial estimates, so we propose a new initial estimator that offers good performance. The EM algorithm approach requires pilot symbols to resolve a phase ambiguity. Thus, we also present a blind estimation algorithm to avoid the reduction in overall code rate from the use of pilot symbols     

Artificial Neural Network Channel Estimation Based on Levenberg-Marquardt for OFDM Systems

The many advantages responsible for the widespread application of orthogonal frequency division multiplexing (OFDM) systems are limited by the multipath fading. In OFDM systems, channel estimation is carried out by transmitting pilot symbols generally. In this paper, we propose an artificial neural network (ANN) channel estimation technique based on levenberg-marquardt training algorithm as an alternative to pilot based channel estimation technique for OFDM systems over Rayleigh fading channels. In proposed technique, there are no pilot symbols which added to OFDM. Therefore, this technique is more bandwidth efficient compared to pilot-based channel estimation techniques. Also, this technique is making full use of the learning property of neural network. By using this feature, there is no need of any matrix computation and the proposed technique is less complex than the pilot based techniques. Simulation results show that ANN based channel estimator gives better results compared to the pilot based channel estimator for OFDM systems over Rayleigh fading channel.