一种基于自适应阵列天线的波束赋形算法

自适应阵列天线中的数字波束赋形(DBF)技术是智能天线数字信号处理部分的核心.提出了一种可用于自适应阵列波束赋形的SMI-LMS算法--由SMI(采样协方差矩阵求逆)算法决定LMS(最小均方)算法的初始权向量.该算法充分结合了SMI算法收敛速度快和LMS算法稳态误差小的优点,能在较强干扰环境下,确保权向量的快速收敛和跟踪速度.与传统的LMS算法相比,SMI-LMS算法具有良好的收敛性能、较快的跟踪速度和较小的输出误差,并可以有效改善自适应方向图的副瓣性能.仿真结果验证了该结论.     

MIMO DFE equalization for multitone DS/SS systems over multipathchannels

The combination of multitone modulation with direct sequence spectrum spreading (DS/SS) has been introduced in the past. The performance of a correlation receiver has been evaluated for a multipath channel and in the presence of an additional multiple access interference. We analyze the problem of decision feedback equalization (DFE) for such a system. In order to understand the potential of the system with equalization, we first study the steady-state behavior of the equalizer for a minimum mean square error (MMSE) criterion. The investigation is carried out for a receiver made of a bank of filters matched to both the symbol shape and the channel, and for a two path channel. Assuming transmission of binary phase shift keying (BPSK) symbols, an exact expression of the bit error probability is obtained in the form of an integral. Then adaptive least mean square (LMS) and recursive least square (RLS) structures are derived. The performance of the adaptive RLS algorithm is demonstrated by means of computer simulations     

Optimization of Recursive Least Square-Based Adaptive Linear Equalizer for ZigBee Transceiver

An efficient technique to compensate for the channel detrimental effects in ZigBee systems is introduced in this paper. The proposed methodology relies on adding a recursive least square (RLS) based adaptive linear equalizer (ALE) to the physical layer of the receiver side. The performance of the RLS based ALE is investigated inside the ZigBee system under different multipath fading situations: Rician and Rayleigh. Moreover, the paper proposes a methodology for deciding the RLS based ALE’s design parameters. The design procedure depends on solving multiple objectives optimizing function based on genetic algorithms (GAs). The ALE’s parameters are chosen, such that the system experiences minimum bit error rate (BER) with fast convergence response. For design verification purposes, the ZigBee transceiver is modeled in MATLAB Simulink and tested under different fading and signal to noise ratios. In addition, the performance of the RLS adaptation algorithm is compared with the least mean square (LMS) one. The results show that the RLS based ALE provides better ZigBee performance with less BER and fast adaptation response.     

智能天线在多径信道中的性能仿真与分析

首先讨论了自适应阵列天线算法原理，然后通过对采用LMS算法的智能天线在多径信道中抗多径干扰性能的仿真，进一步分析了多径干扰对智能天线性能的影响。结果表明，智能天线阵列的抗多径干扰性能受信号空间分布、信号幅度等因素的影响。     

Performance of adaptive MC-CDMA detectors in rapidly fading Rayleigh channels

Multicarrier code-division multiple access (MC-CDMA) combines multicarrier transmission with direct sequence spread spectrum. Different approaches have been adopted which do not assume a perfectly known channel. We examine the forward-link performance of decision-directed adaptive detection schemes, with and without explicit channel estimation, for MC-CDMA systems operating in fast fading channels. We analyze theoretically the impact of channel estimation errors by first considering a simpler system employing a threshold orthogonality restoring combining (TORC) detector with a Kalman channel estimator. We show that the performance deteriorates significantly as the channel fading rate increases and that the fading rate affects the selection of system parameters. We examine the performance of more realistic schemes based on the minimum mean square error (MMSE) criterion using least mean square (LMS) and recursive least square (RLS) adaptation. We present a discussion which compares the decision-directed and pilot-aided approaches and explores the tradeoffs between channel estimation overhead and performance. We find that there is a fading rate range where each method provides a good tradeoff between performance and overhead. We conclude that the MMSE per carrier decision-directed detector with RLS estimation combines good performance in low to moderate fading rates, robustness in parameter variations, and relatively low complexity and overhead. For higher fading rates, however, only pilot-symbol-aided detectors are appropriate.     

An adaptive correlator receiver for direct-sequence spread-spectrumcommunication

This paper presents a novel receiver for direct sequence spread-spectrum signals over channels containing interference and multipath. The receiver employs an adaptive correlator that jointly detects the transmitted data, removes interference, and compensates for multipath. The optimum correlation vector is derived by determining the Wiener vector that minimizes the mean squared error (MSE) between the transmitted data bit and the correlator output. For an additive white Gaussian noise (AWGN) channel, the optimal correlation vector is the spreading sequence used by the transmitter. For interference and multipath channels, the optimal correlation vector will suppress the interference and combine the multipath while optimizing the detection of the transmitted data bit. The paper presents analytical and simulation results which illustrate the bit-error rate (BER) performance of the receiver in multipath and narrowband interference. Additionally, simulation results are presented illustrating the convergence performance of the receiver when the tap weights are adjusted using either the least mean square (LMS) or recursive least squares (RLS) adaptive algorithms     

采用归一化最小均方误差准则的LM-BP算法

传统神经网络通常以最小均方误差(LMS)或最小二乘（RLS）为收敛准则,而在自适应均衡等一些应用中,使用归一化最小均方误差（NLMS）准则可以使神经网络性能更加优越。本文在NLMS准则基础上,提出了一种以Levenberg-Marquardt（LM）训练的神经网络收敛算法。通过将神经网络的误差函数归一化,然后采用LM算法作为训练算法,实现了神经网络的快速收敛。理论分析和实验仿真表明,与采用最速下降法的NLMS准则和采用LM算法的LMS准则相比,本文算法收敛速度快,归一化均方误差更小,应用于神经网络水印系统中实现了水印信息的盲提取,能更好的抵抗噪声、低通滤波和重量化等攻击,性能平均提高了4%。      

Adaptive Filtering Techniques using Cyclic Prefix in OFDM Systems for Multipath Fading Channel Prediction

This paper presents adaptive channel prediction techniques for wireless orthogonal frequency division multiplexing (OFDM) systems using cyclic prefix (CP). The CP not only combats intersymbol interference, but also precludes requirement of additional training symbols. The proposed adaptive algorithms exploit the channel state information contained in CP of received OFDM symbol, under the time-invariant and time-variant wireless multipath Rayleigh fading channels. For channel prediction, the convergence and tracking characteristics of conventional recursive least squares (RLS) algorithm, numeric variable forgetting factor RLS (NVFF-RLS) algorithm, Kalman filtering (KF) algorithm and reduced Kalman least mean squares (RK-LMS) algorithm are compared. The simulation results are presented to demonstrate that KF algorithm is the best available technique as compared to RK-LMS, RLS and NVFF-RLS algorithms by providing low mean square channel prediction error. But RK-LMS and NVFF-RLS algorithms exhibit lower computational complexity than KF algorithm. Under typical conditions, the tracking performance of RK-LMS is comparable to RLS algorithm. However, RK-LMS algorithm fails to perform well in convergence mode. For time-variant multipath fading channel prediction, the presented NVFF-RLS algorithm supersedes RLS algorithm in the channel tracking mode under moderately high fade rate conditions. However, under appropriate parameter setting in \(2\times 1\) space–time block-coded OFDM system, NVFF-RLS algorithm bestows enhanced channel tracking performance than RLS algorithm under static as well as dynamic environment, which leads to significant reduction in symbol error rate.     

Adaptive Beamformers for High-Speed Mobile Communication

In this work, we propose a fast conjugate gradient method (CGM) for beamforming, after thoroughly analyzing the performances of the least mean square (LMS), the recursive least square (RLS), and the sample matrix inversion (SMI) adaptive beamforming algorithms. Various experiments are carried out to analyze the performances of each beamformer in detail. The proposed conjugate gradient method does not use the Eigen spread of the signal correlation matrix as in the case of the LMS and the RLS methods. It computes antenna array weights orthogonally for each iteration. Hence the convergence rate and the null depths of the proposed method are much better than the LMS, the SMI the RLS and the classical CGM. Also, the simulation results confirm that this method has a speed improvement of about 60% over the classical conjugate gradient method. This aspect significantly reduces the processor burden and saves a lot of power during the beamforming process. Hence the proposed method is superior compared to the LMS, the RLS, the SMI, and classical CGM and most suitable for high-speed mobile communication.

     

Performance analysis of coded space‐time adaptive detection in DS/CDMA systems over Rayleigh fading channels

In this paper, we study the use of channel coding in a direct‐sequence code‐division multiple‐access (DS‐CDMA) system that employs space‐time adaptive minimum‐mean square‐error (MMSE) interference suppression over Rayleigh fading channels. It is shown that the employment of adaptive antenna arrays at the receiver can assist in attenuating multiuser interference and at the same time speeds‐up the convergence rate of the adaptive receiver. In this work, we assess the accuracy of the theoretical results developed for the uncoded and convolutionally coded space‐time multiuser detector when applied to the adaptive case. It is found that the use of antenna arrays brings the receiver performance very close to its multiuser counterpart. Using performance error bounds, we show that a user‐capacity gain of approximately 200% can easily be achieved for the space‐time adaptive detector when used with a rate 1/2 convolutional code (CC) and a practical channel interleaver. This capacity gain is only 10% less than the gain achieved for the more complicated multiuser‐based receiver. Finally, we perform a comparison between convolutional and turbo coding where we find that the latter outperforms the former at all practical bit‐error rates (BER). Copyright © 2006 John Wiley & Sons, Ltd.     

Adaptive DFE Multiuser Receiver for CDMA Systems using Two-Step LMS-Type Algorithm: An Equalization Approach

This paper presents an adaptive decision feedback equalizer (DFE) based multiuser receiver for code division multiple access (CDMA) systems over smoothly time-varying multipath fading channels using the two-step LMS-type algorithm. The frequency-selective fading channel is modeled as a tapped-delay-line filter with smoothly time-varying Rayleigh-distributed tap coefficients. The receiver uses an adaptive minimum mean square error (MMSE) multiuser channel estimator based on the reduced Kalman least mean square (RK-LMS) algorithm to predict these tap coefficients (Kohli and Mehra, Wireless Personal Communication 46:507–521, 2008). We propose the design of adaptive MMSE feedforward and feedback filters by using the estimated channel response. Unlike the previously available Kalman filtering algorithm based approach (Chen and Chen, IEEE Transactions on Signal Processing 49:1523–1532, 2001), the incorporation of RK-LMS algorithm reduces the computational complexity of multiuser receiver. The computer simulation results are presented to show the substantial improvement in its bit error rate performance over the conventional LMS algorithm based receiver. It can be inferred that the proposed multiuser receiver proves to be robust against the nonstationarity introduced due to channel variations, and it is also beneficial for the multiuser interference cancellation and data detection in CDMA systems.     

A Stabilized Multichannel Fast RLS Algorithm for Adaptive Transmultiplexer Receivers

The transmultiplexer (TMUX) system has been studied for its application to multicarrier communications. The channel impairments including noise, interference, and distortion draw the need for adaptive reconstruction at the TMUX receiver. Among possible adaptive methods, the recursive least squares (RLS) algorithm is appealing for its good convergence rate and steady state performance. However, higher computational complexity due to the matrix operation is the drawback of utilizing RLS. A fast RLS algorithm used for adaptive signal reconstruction in the TMUX system is developed in this paper. By using the polyphase decomposition method, the adaptive receiver in the TMUX system can be formulated as a multichannel filtering problem, and the fast algorithm is obtained through the block Toeplitz matrix structure of received signals. In addition to the reduction of complexity, simulation results show that the adaptive TMUX receiver has a convergence rate close to that of the standard RLS algorithm and the performance approaches the minimum mean square error solution.     

Adaptive space-time feedforward/feedback detection for high datarate CDMA in frequency-selective fading

We investigate linear and nonlinear space-time minimum mean-square-error (MMSE) multiuser detectors for high data rate wireless code-division multiple-access (CDMA) networks. The centralized reverse-link detectors comprise a space-time feedforward filter and a multiuser feedback filter which processes the previously detected symbols of all in-sector users. The feedforward filter processes chip-rate samples from a bank of chip-matched filters which operate on the baseband outputs from an array of antennas. We present an adaptive multiuser recursive least squares (RLS) algorithm which determines the MMSE adjusted filter coefficients with less complexity than individual adaptation for each user. We calculate the outage probabilities and isolate the effects of antenna, diversity, and interference suppression gains for linear and nonlinear filtering and for CDMA systems with varying levels of system control (e.g., timing control, code assignment, cell layout). For eight users transmitting uncoded 2-Mb/s quadrature phase-shift keying with a spreading gain of eight chips per symbol over a fading channel with a multipath delay spread of 1.25 μs, the performance of a three-antenna feedforward/feedback detector was within 1 dB (in signal-to-noise ratio per antenna) of ideal detection in the absence of interference. By training for 10% of a 5-ms frame, RLS adaptation enabled the same detector to suffer less than a 0.5-dB penalty due to the combined effects of imperfect coefficients and error propagation. The advantage of nonlinear feedforward/feedback detection over linear feedforward detection was shown to be significantly larger for a CDMA system with enhanced system control     

A new combination of adaptive channel estimation methods and TORC equalizer in MC‐CDMA systems

Adaptive systems identification has been widely studied, but most studies have focused on the convergence of these methods. Applications of equalization systems have also received much attention. This paper presents a new combination of adaptive Broadband Radio Access Networks (BRAN) channel identification algorithms for multicarrier code division multiple access (MC‐CDMA) systems downlink equalization. In fifth‐generation (5G) wireless communications, MC‐CDMA is expected to support the associated networks. The BRAN E channel parameters, representing an outdoor scenario normalized for MC‐CDMA systems, are identified using a recursive least mean pth power algorithm with logarithmic transformation (RlogLMP). For validity and test aim, this algorithm is compared with the existing recursive least square (RLS) and least mean square (LMS) algorithms. Moreover, we use the estimated coefficients in the adaptive equalization problem. We give a review of the threshold orthogonality restoring combining (TORC) equalizer, which is coupled with the presented algorithms to counteract channel fading, as evaluated by the bit error rate (BER). Our performance results show that the RlogLMP algorithm can estimate the measured BRAN E channel with good efficiency for various values of the signal‐to‐noise ratio (SNR), as compared with the classical algorithms RLS and LMS. In adaptive equalization problems, the achieved results demonstrate that two thresholds ρ_TH in the TORC equalizer minimize the performance degradation, in terms of the BER, of the MC‐CDMA system under multipath channel fading with very good accuracy, especially if the coefficients are estimated with the specific case of the power p in the RlogLMP algorithm.     

基于遗传优化的天线阵元LMS改进算法

最小均方（LMS）算法是自适应阵列天线中得以广泛应用的阵列天线加权算法。提出了一种基于遗传优化的LMS改进算法,该基于遗传优化的最小均方（GA—LMS）算法充分结合了遗传算法的并行处理和全局搜索的优点。实验结果表明,与传统的LMS算法相比,GA—LMS算法具有良好的收敛性能,并可更好地抑制干扰信号,有效改善自适应阵列天...     

Improved least mean square algorithm based in satellite multi-beamforming

High-throughput satellites use multi-beam technology to achieve polarization isolation and spatial isolation to reuse frequency resources,resulting in increased traffic capacity,but this presents a higher demand for fast adaptive beamforming algorithms.In order to solve the shortcoming that the convergence rate and steady-state error can not be satisfied simultaneously when using the LMS algorithm,an improved least mean square algorithm was proposed,which used the statistical average gradient update to solve the problem of the formation of beam instability caused by the instantaneous gradient,which can speed up at the beginning of the beamforming and maintain a small error value after the convergence has reached a steady state.The use of 61-element hexagonal array phased array antenna to form a 7-point beam in an environment where high-throughput satellites have a strong rainfall attenuation was considered.The results show that the improved algorithm can greatly improve the convergence speed and obtain better steady state performance under the condition of only a small increase in complexity,which can be applied to high-throughput satellite beamforming technology with severe inter-beam co-channel interference in emergency communication scenarios.     

DFT/LMS算法在DSSS中的应用及性能分析

本文分析了直接序列扩频(DSSS)系统中最小错误概率(MPE)意义下的最优滤波器,并依据矩阵求逆引理证明最小均方误差(MMSE)意义下的最优滤波——维纳滤波也是MPE意义下的最优滤波。在DSSS中应用自适应滤波,无须先验已知扩频码的码型和干扰的统计特性,就能一并完成解扩以及有效抑制干扰。离散傅立叶变换/最小均方(DFT/LMS)算法的收敛速度远快于LMS算法,而运算量、稳健性与LMS算法基本相同。基于DFT/LMS算法的自适应滤波大大简化DSSS系统接收机的设计,显著增强系统抗干扰能力,具有很强的实用性。     

MBER Space-Time Decision Feedback Equalization Assisted Multiuser Detection for Multiple Antenna Aided SDMA Systems

This paper proposes a space-time decision feedback equalization (ST-DFE) assisted multiuser detection (MUD) scheme for multiple receiver antenna aided space division multiple access systems. A minimum bit error rate (MBER) design is invoked for the MUD, which is shown to be capable of improving the achievable bit error rate performance and enhancing the attainable system capacity over that of the standard minimum mean square error (MMSE) design. An adaptive implementation of the MBER ST-DFE assisted MUD is proposed using a stochastic gradient-based least bit error rate algorithm, which is demonstrated to consistently outperform the classical least mean square (LMS) algorithm, while achieving a lower computational complexity than the LMS algorithm for the binary signalling scheme. Our simulation results demonstrate that the MBER ST-DFE assisted MUD is more robust to channel estimation errors as well as to potential error propagation imposed by decision feedback errors, compared to the MMSE ST-DFE assisted MUD.     

应用于卫星多波束天线的自适应波束形成算法比较

射频干扰会严重影响卫星通信链路性能,而自适应调零天线是一种有效的卫星抗干扰措施.本文对应用于多波束天线的各种自适应波束形成算法进行对比分析,理论分析与仿真结果皆表明,DMI和RLS算法相对经典的LMS算法而言,在收敛速率和输出信噪干扰比上皆有相当的优越性.这些快速算法适合卫星通信的干扰抑制应用.     

Mitigation of Multipath Effects Based on a Robust Fractional Order Bidirectional Least Mean Square (FOBLMS) Beamforming Algorithm for GPS Receivers

Consideration on positioning and location services among the public has been increasing in the recent years with their applications in most of the anticipating milieus such as automobile navigation system etc. This insists for a development of high recitation global navigation satellite system such as global positioning system (GPS). Multipath effects, interference, signal jamming etc. are the major sources of error influencing the performance of the GPS receiver. Literature presents many of the multipath mitigation techniques. Among them, adaptive processing technology based beamforming algorithms appears a viable solution for multipath mitigation. The least mean square (LMS) beamforming algorithms were sensitive to dynamic environments thus affecting the accuracy of GPS. In this paper, an adaptive beamforming algorithm called fractional order bidirectional least mean square (FOBLMS) algorithm is proposed to mitigate the multipath effects and to conceal the jammer signal in a GPS receiver. The FOBLMS is an integration of the fractional calculus and bidirectional least mean square algorithm. The effectiveness of the proposed algorithm is validated using the bit error rate and experimentation gain results over the existing beamforming algorithms. Experimental results demonstrated that the performance of the proposed beamforming algorithm is better than LMS algorithm with maximal relative antenna gain of 28.92 dB, 32.84 dB for two and four element antenna arrays at ??60° and 10°, direction of arrivals respectively. The outcome of this work would be useful for developing a robust technique for multipath mitigation in GPS receivers.