Adaptive linearly constrained minimum variance beamforming for multiuser cooperative relaying using the kalman filter

In this paper, we consider a wireless communication scenario with multiple source-destination pairs communicating through several cooperative amplify-and-forward relay terminals. The relays are equipped with multiple antennas that receive the source signals and transmit them to the destination nodes. We develop two iterative relay beamforming algorithms that can be applied in real-time. In both algorithms, the relay beamforming matrices are jointly designed by minimizing the received power at all the destination nodes while preserving the desired signal at each destination. The first algorithm requires the existence of a local processing center that computes the beamforming coefficients of all the relays. In the second algorithm, each relay can compute its beamforming coefficients locally with the help of some common information that is broadcasted from the other relays. This is achieved at the expense of enforcing the desired signal preservation constraints non-cooperatively. We provide two extensions of the proposed algorithms that allow the relays to control their transmission power and to modify the quality of service provided to different sources. Simulation results are presented validating the ability of the proposed algorithms to perform their beamforming tasks efficiently and to track rapid changes in the operating environment.     

An alternative approach to linearly constrained adaptive beamforming

A beamforming structure is presented which can be used to implement a wide variety of linearly constrained adaptive array processors. The structure is designed for use with arrays which have been time-delay steered such that the desired signal of interest appears approximately in phase at the steered outputs. One major advantage of the new structure is the constraints can be implemented using simple hardware differencing amplifiers. The structure is shown to incorporate algorithms which have been suggested previously for use in adaptive beamforming as well as to include new approaches. It is also particularly useful for studying the effects of steering errors on array performance. Numerical examples illustrating the performance of the structure are presented.     

一种改进的约束正交化自适应波束形成算法

在约束正交化算法的基础上,提出一种改进的约束正交化算法,该算法利用可得到的较多的快拍数来提高波束形成的稳健性。理论分析和仿真结果表明:对运动干扰,改进的约束正交化算法具有比约束正交化算法更好的稳定性,其性能接近约束正交投影算法,但计算量较约束正交投影算法小得多。从仿真结果可看出:改进的约束正交化算法对运动和静态干扰同样具有良好的稳健性。     

A fast least-squares algorithm for linearly constrained adaptivefiltering

An extension of the field of fast least-squares techniques is presented. It is shown that the adaptation gain, which is updated with a number of operations proportional to the number of transversal filter coefficients, can be used to update the coefficients of a linearly constrained adaptive filter. An algorithm that is robust to round-off errors is derived. It is general and flexible. It can handle multiple constraints and multichannel signals. Its performance is illustrated by simulations and compared with the classical LMS-based Frost (1972) algorithm     

A complex algorithm for linearly constrained adaptive arrays

A linearly constrained least mean squares (lms) algorithm for complex signals is derived to minimize noise power in the array output. The original algorithm for real signals isW(k + 1) = P[W(k) - mu y(k)X(k)] + F. The complex form is shown to beW(k + 1) = P[W(k) - mu y(k)bar{X}(k)] + F, where the bar abovebar{X}denotes complex conjugate.W, y, X, andFare complex.Pandmuare real.     

An algorithm for linearly constrained adaptive array processing

A constrained least mean-squares algorithm has been derived which is capable of adjusting an array of sensors in real time to respond to a signal coming from a desired direction while discriminating against noises coming from other directions. Analysis and computer simulations confirm that the algorithm is able to iteratively adapt variable weights on the taps of the sensor array to minimize noise power in the array output. A set of linear equality constraints on the weights maintains a chosen frequency characteristic for the array in the direction of interest. The array problem would be a classical constrained least-mean-squares problem except that the signal and noise statistics are assumed unknown a priori. A geometrical presentation shows that the algorithm is able to maintain the constraints and prevent the accumulation of quantization errors in a digital implementation.     

Adaptive beamforming using the constrained Kalman filter

From the viewpoint of achieving rapid convergence, application of a Kalman filter to an adaptive array is considered. Compared with the Frost's (1972) constrained least-mean-square algorithm, the constrained Kalman algorithm for adaptive beamforming is proposed to overcome the problem of signal distortion along the look direction which occurs in the unconstrained Kalman beamformer of Baird (1974). A constraint on the array response along the look direction is added to the measurement equation of the Kalman filter. The weight vector of the constrained Kalman beamformer is derived and shown to converge to that of the minimum-variance distortionless-response beamformer. The convergence rate of the proposed algorithm is also analyzed. Compared to Baird's algorithm and the sidelobe canceller with one-step Kalman predictor, simulation results show the effectiveness of the proposed algorithm     

A fast null steering algorithm for linearly constrained adaptivearrays

A fast null steering algorithm for adaptive arrays with a look direction constraint is investigated. In this algorithm, the least mean square (LMS) algorithm is used to adaptively adjust the positions of the array response zeros one after another in a time-multiplexed manner to track unknown jammers. To ensure that the look direction response and the other zeros remain unchanged when a particular null is being updated, the element signals are suitably transformed before the LMS updating. Despite this signal transformation, the new algorithm has almost the same implementation complexity as when the LMS algorithm is employed directly, as only one zero is being adaptively updated at any instant. However, with each null being independently steered, the convergence behavior of the new algorithm is significantly faster and is almost independent of the external noise environment     

CDMA系统中一种反向链路自适应波束成形算法

在已有波束成形算法基础上,针对码分多址(CDMA)系统反向链路,给出相应智能天线信号模型及性能分析;并基于最大功率输出准则,采用幂法迭代计算,提出一种适合于高速环境的自适应波束成形算法.与原有一些算法相比,该算法仅计算解扩后信号的最大特征矢量,有效地降低了计算量,且性能稳定;可很好地应用于高速车载多径环境.计算机仿真结果表明在相同衰落情况下所提算法性能可接近于性能较好的码滤波法,但复杂度远低于后者,从而实现了以低的计算复杂度获得较好的系统性能.     

稀疏自适应Volterra滤波的QRD-RLS算法

求解非线性问题时,非线性Volterra滤波的性能明显优于线性滤波;稀疏结构Voherra滤波器有效降低了Volterra滤波的工程应用复杂度;本文针对稀疏Volterra滤波,改进了基于QR分解的RLS算法,在更换滤波器抽头的时候保留了先前的数据信息,从而加速当前抽头的收敛,加快了滤波器核矢量的更新和替换.仿真结果表明改进的QRD-RKS算法具有快速自适应能力;一同验证了稀疏Volterra滤波的有效性.     

基于分数低阶统计量的线性约束恒模盲自适应波束形成方法

为解决传统恒模波束形成算法在受冲击噪声污染的无线环境中的性能退化问题,本文提出基于分数低阶统计量的线性约束恒模盲自适应波束形成方法,并从理论上分析了算法收敛条件。仿真实验表明,在稳定分布噪声下,新方法具有比传统恒模波束形成方法更好的韧性,而且比线性约束最小平均P范数波束形成方法具有更高的输出信干噪比,即使在强脉冲干扰环境下新方法仍具有较好的信号恢复能力。     

Constrained Hung-Turner adaptive beam-forming algorithm withadditional robustness to wideband and moving jammers

We present a new modification of the Hung-Turner (HT) adaptive beam-forming algorithm, providing additional robustness of a narrowband adaptive array in wideband and moving-jammer scenarios. The robustness is achieved by involving the derivative constraints toward the jammer directions in the conventional Hung-Turner (1983) algorithm. The important advantage of the constraints used is that they do not require any a priori information about jammer directions. The computer simulations with wideband and moving jammers show that the proposed algorithm provides the significant improvement of the adaptive array performance as compared with the conventional HT algorithm. At the same time, for a moderate order of derivative constraints, the new algorithm has a computational efficiency, comparable with the conventional HT algorithm     

基于波束形成算法的PFDA干扰抑制

针对二维面阵频率分集阵列(PFDA)雷达在抑制与目标角度维接近、距离维可分的干扰过程中,经典波束形成算法在导向矢量失配时出现的主瓣畸变问题,在交叉正弦二维面阵频率分集阵列结构的基础上,通过采用可变加载约束的最速下降线性约束最小方差准则,求解导向矢量失配时的修正权矢量,在估计导向矢量存在2°指向误差时仍可实现对阵列方向图波束主瓣的有效纠偏和保形。仿真验证了该方法的有效性。     

A linearly constrained constant modulus approach to blind adaptivemultiuser interference suppression

This article presents a linearly constrained constant modulus approach for the blind suppression of multiuser interferences in direct-sequence code division multiple access systems. The method performs the same as minimum mean square error receivers and outperforms existing blind approaches because it only requires a rough estimate of the desired user code and timing     

求解约束优化问题的自适应精英捕鱼算法

在对捕鱼算法迭代过程进行研究和分析的基础上,针对将该算法用于求解约束优化问题时存在收敛速度慢、求解精度不高等缺点,提出了一种自适应精英捕鱼算法。该算法通过采用自适应撒网半径设置策略和精英个体保留策略来改善和提高算法搜索性能。最后,通过使用三个经典的工程设计问题实例对算法进行性能测试。实验结果表明,改进算法在收敛速度、求解精度和稳定性方面均有明显提高。因此,使用自适应精英捕鱼算法来求解约束优化问题是有效且可行的。     

Adaptive beamforming algorithm based on eigen-space method for smart antennas

This paper presents an adaptive beamforming technique based on the eigen-space method for computing the optimal weight vector that does not degrade the receiving performance even in wide angle spread circumstances. By exploiting the diversity gain, which is available in the signal environments of the wide angle spread, the proposed technique rather enhances the performance as the angle spread increases. It is also confirmed in this paper that performance of the proposed technique is almost identical to that of which has been obtained through the exact solution of the eigen-space method.     

基于天线阵列的一种预处理LCLSCM多用户检测算法

给出了一种天线阵列信号的预处理方法,并将线性受限条件和判决反馈用于最小二乘,提出了一种基于天线阵列的预处理线性受限判决反馈最小二乘恒模多用户检测算法,称为PLC-DFB-LSCMA算法,并与判决反馈最小二乘恒模算法(DFB-LSCMA)及传统的最小二乘恒模算法(LSCMA)进行了仿真比较,仿真结果表明,PLC-DFB-LSCMA算法的信干比性能及误码性能仍优于后二者。     

The performance of hybrid adaptive beamforming algorithm forjammers suppression

Adaptive array processing is of growing importance in the fields of communications, radar, and sonar, where the designer almost invariably faces the problem of interference suppression. In general, under some situations, the conventional Frost's (1972) beamforming algorithm may have some problems associated with performance degradation in multiple jammers environment. It causes the convergence time to be essentially dependent on the jammer powers ratio. A new hybrid adaptive beamforming algorithm is derived in the transformed domain for multiple jammers suppression. Here, three popular orthonormal transformations-i.e., discrete Hartley, discrete cosine, and discrete Fourier transforms-are considered. Overall performance improvement, in terms of convergence rate and the computational requirement, is investigated. From the simulation results, we observed that the new presented beamforming algorithm is more robust than the conventional Frost's beamforming algorithm in terms of jammers suppression and the convergence rate     

An improved adaptive constrained constant modulus reduced-rank algorithm with sparse updates for beamforming

In this work, we propose an adaptive set-membership (SM) reduced-rank filtering algorithm using the constrained constant modulus criterion for beamforming. We develop a stochastic gradient type algorithm based on the concept of SM techniques for adaptive beamforming. The filter weights are updated only if the bounded constraint cannot be satisfied. We also propose a scheme of time-varying bound and incorporate parameter dependence to characterize the environment for improving the tracking performance. A detailed analysis of the proposed algorithm in terms of computational complexity and stability is carried out. Simulation results verify the analytical results and show that the proposed adaptive SM reduced-rank beamforming algorithms with a dynamic bound achieve superior performance to previously reported methods at a reduced update rate.     

基于改进互耦系数估计算法的自适应波束形成

阵列信号在实际应用中,常常会面临噪声的干扰,低信噪比(signal noise ratio, SNR)时波束形成器性能会急剧下降.针对该问题,提出一种基于改进互耦系数估计的抗互耦算法的自适应波束形成,即研究信号在不同输入SNR以及不同干扰波达方向(direction of arrival,DOA)估计误差下的互耦系数估计误差;并通过误差分析修正原算法不同SNR下参与估计信号的数目.改进算法改进了导向矢量和期望信号,提高了低SNR下互耦系数估计的准确度,对比分析验证了其在低SNR情况下有更强的抗干扰能力,对互耦现象有着更好的稳健性.