DS/CDMA系统中的一种自适应单用户接收机

本文提出了一种在异步多径DS/CDMA系统中基于独立分量分析算法的单用户接收机,这种接收机仅需要已知期望用户的定时和特征波形,计算量小、结构简单.它不但能用于在基站进行多用户信号的上行接收,而且适合于用在移动台进行下行接收.其性能较之匹配滤波器和盲MMSE多用户检测器有很大提高.     

多用户中继系统中联合收发机的设计方案

在多用户中继系统中,根据最小均方误差(MMSE)准则,提出了一种考虑直接路径的联合收发机设计方案.给出了迭代算法,对中继发射机和用户接收机进行了联合优化,其中用户接收机是用来接收合并源端发送信号和中继发送信号.数据仿真结果表明,提出的方案与不考虑直接路径的收发机方案以及其他已知的LMMSE方案相比,在均方误差(MSE)和误码率(BER)性能方面,有较大的提高.     

空时分组码OFDM系统的上行多用户检测

针对目前空时编码结构大多只研究单用户检测这一现状，研究了空时分组码OFDM系统的多用户结构，并提出了一种性能次优的基于均值的软判决多用户检测（SDMUD）算法。仿真表明，该检测算法性能要比MMSE线性检测算法提高约4dB，可获得较为满意的干扰消除效果，满足系统对多用户检测性能的现实期望。     

空时CDMA多用户信号检测

本文利用最小均方误差(MMSE)和最大似然(ML)准则,推导了空时CDMA多用户检测算法,分析了空时多用户检测与单用户检测的关系,并提出一种空时CDMA多用户检测接收机结构.计算机仿真结果说明了本文提出的空时CDMA多用户检测算法,与单用户检测方法相比其误码性能有相当的改进.     

长码CDMA系统上行链路多用户接收机设计

提出一种适用于长码CDMA移动通信系统上行链路的多用户接收机设计方案，包括多用户信道估计、多用户检测以及信道跟踪等算法。通过把用户传播时延的影响放入信道响应矩阵中，由信道估计间接得出各用户的传播时延。使用迭代运算的方式使得运算量分散，降低了对硬件平台的要求，使算法更为适用。增大观察窗的长度达到了更准确的用户信息比特判决，提高了接收机的性能。仿真结果表明文章提出的接收机设计方案具有很好的远近效应抑制能力，性能远高于传统的单用户Rake接收机。     

分集接收混合遗传算法多用户检测器在异步CDMA移动通信中的应用研究

本文研究了将混合遗传法应用于码分多址扩频通信的多用户检测中，从而消除多址接入干扰的方法。本文先给出了在异步瑞利衰落信道下解调扩频信号的分集接收混合遗传算法多用户检测器的原理框图，然后分析了用混合遗传算法进行多用户检测的理论依据和实际性能。仿真结果表明无论是抗多址干扰还是抑制远近效应，分集接收混合遗传算法多用户检测器都明显优于传统接收机，其性能接近分集接收最佳多用户检测器。     

迭代迫零多用户检测算法研究与应用

最优的最大似然多用户接收机的复杂度随用户数成指数增长,传统的Rake接收机干扰受限且存在远近效应。次优的线性多用户检测是性能和复杂度的折衷,其中,迫零联合检测多用户接收机属于一种线性解相关接收机,虽然避免了对数据符号矢量的穷举搜索,大大减少了计算量,但是由于其基本运算中包含了随机矩阵的求逆运算,而矩阵求逆运算对于硬件定点实现的舍入误差非常敏感,有时会产生很大的误差甚至无解。考察比较了迫零检测接收机的四种迭代算法。对其复杂度进行了分析和仿真,结果表明Gauss-Siedel是一种收敛速度较快,时间复杂度较低的迭代算法。     

一种多用户MIMO-OFDM系统中的天线与子载波分配算法

天线与子载波分配是多用户MIMO-OFDM系统无线资源管理中的重要内容.在分析了多用户MIMO-OFDM系统下行链路中最优天线与子载波分配算法的基础上,提出了一种次优的低复杂度天线与子载波分配算法.该算法通过先选择天线再选择用户从而避免了最优算法中的遍历搜索.仿真结果表明,在运算量大大降低的情况下,所提算法获得的系统最大容量和最优算法所获得的最大容量相比相差不大,而且空间和频率联合优化的结果使其性能远远优于仅在MIMO环境下进行子载波分配的算法.     

编码的多载波CDMA系统中Turbo时空多用户检测

联合MAP多用户检测和信道译码的迭代多用户检测技术可显著提高多载波CDMA系统的容量和性能,本文给出了结合智能天线和迭代MAP多用户检测的Turbo时空多用户检测算法,该方法进一步提高了系统的性能.Turbo时空多用户检测算法不仅极大减小了传统最优MAP多用户检测算法的运算量,而且,此算法性能在AWGN和频率选择性衰落信道中都能逼近单用户编码多载波CDMA系统多天线接收的性能.     

低复杂度的分组检测空时接收机

V-BLAST接收机是提高无线通信系统传输数率的有效技术,但由于该算法存在大量的求伪逆、迫零和排序,算法的复杂度高,限制了它在实际中的应用;线性迫零(ZF)接收机和最小均方误差(MMSE)接收机复杂度低,但性能差。该文提出了一种分组检测空时接收机,组内采用串行干扰抵消接收,与V-BLAST接收机相比,降低了算法的复杂度。仿真结果表明:所提出的基于MMSE准则下的分组检测空时接收机的性能明显好于基于迫零准则的 V-BLAST接收机。     

Novel Adaptive Nonlinear Predistorters Based on the Direct Learning Algorithm

The adaptive nonlinear predistorter is an effective technique to compensate for the nonlinear distortion existing in digital communication and control systems. However, available adaptive nonlinear predistorters using indirect learning are sensitive to measurement noise and do not perform optimally. Other available types are either slow to converge, complicated in structure and computationally expensive, or do not consider the memory effects in nonlinear systems such as a high power amplifier (HPA). In this paper, we first propose several novel adaptive nonlinear predistorters based on direct learning algorithms - the nonlinear filtered-x RLS (NFXRLS) algorithm, the nonlinear adjoint LMS (NALMS) algorithm, and the nonlinear adjoint RLS (NARLS) algorithm. Using these new learning algorithms, we design adaptive nonlinear predistorters for an HPA with memory effects or for an HPA following a linear system. Because of the direct learning algorithm, these novel adaptive predistorters outperform nonlinear predistorters that are based on the indirect learning method in the sense of normalized mean square error (NMSE), bit error rate (BER), and spectral regrowth. Moreover, our developed adaptive nonlinear predistorters are computationally efficient and/or converge rapidly when compared to other adaptive nonlinear predistorters that use direct learning, and furthermore can be easily implemented. We further simplify our proposed algorithms by exploring the robustness of our proposed algorithm as well as by examining the statistical properties of what we call the "instantaneous equivalent linear" (IEL) filter. Simulation results confirm the effectiveness of our proposed algorithms     

Adaptive step-size algorithms for blind interference suppression inDS/CDMA systems

This paper develops adaptive step-size blind LMS algorithms and adaptive forgetting factor blind RLS algorithms for code-aided suppression of multiple access interference (MAI) and narrowband interference (NBI) in DS/CDMA systems. These algorithms optimally adapt both the step size (forgetting factor) and the weight vector of the blind linear multiuser detector using the received measurements. Simulations are provided to compare the proposed algorithms with previously studied blind RLS and blind LMS algorithms. They show that the adaptive step-size blind LMS algorithm and adaptive forgetting factor blind RLS algorithm field significant improvements over the standard blind LMS algorithm and blind RLS algorithm in dynamic environments where the number of interferers are time-varying     

基于RLS_DGD的查找表更新算法

在间接学习结构的数字预失真技术中,需要使用自适应算法来更新查找表（LUT,LookUp Table）。在各种自适应算法中,RLS算法收敛快但是复杂度高。为降低其计算复杂度,这里提出采用二维坐标下降的RLS（RLS_DCD, RLS using Dichotomous Coordinate Descent）算法更新查找表,达到在数字预失真器系数的预测过程中以较低的运算量实现快速收敛的目的。仿真结果和分析表明,与采用RLS的自适应查找表更新算法比较,在邻信道功率比（ACPR, Adjacent Channel Power Ratio）改善指标相当的情况下,采用RLS—DCD的自适应查找表更新算法能大幅度降低其运算量。     

紫外目标探测弱信号处理方法研究

为了提高紫外探测系统性能,研究具有高灵敏性紫外目标探测弱信号处理方法是关键问题之一。首先,在阐述紫外目标探测原理的基础上,分析紫外目标辐射特性。其次,研究自适应噪声抵消信号处理的一般方法,以及基于最小均方误差LMS准则、递推最小二乘RLS准则和线性神经网络ADALINE的三种具体的自适应噪声抵消算法。再次,提出采用功率信噪比来衡量滤波算法的性能。最后,通过仿真计算比较分析这三种算法的滤波效果。结果表明:采用LMS和RLS算法信噪比提高约12.5 dB,且LMS算法比RLS算法略优,而采用ADALINE算法信噪比至少改善26.6 dB,可实现高性能滤波。对于紫外目标探测弱信号处理方法的发展与深入研究具有一定的作用和意义。     

Simultaneous suppression of multiaccess and narrow-bandinterference in asynchronous CDMA networks

This paper handles the simultaneous suppression of narrow-band and multiaccess interference in asynchronous CDMA networks. We consider both linear one-shot detection and block-detection, showing that, in both cases, the presence of an external narrow-band interferer generally results in the need for time-varying processing. As to the linear one-shot detectors, we derive both a zero-forcing and a minimum mean square error detector, showing that they are members of an only family, wherein the optimization criterion is the constrained minimization of a suitably defined output interference energy. We also present a comparative performance assessment between the various detection strategies, studying the impact of both the optimization criterion and other system parameters, such as the oversampling ratio and the length of the observation window. We also handle the problem of blind and adaptive detection. At first we show that the linear one-shot receivers are readily amenable to a blind implementation, upon off-line estimation of the covariance matrix of the observables. Next, we consider the problem of an adaptive implementation of a periodically time-varying minimum mean square error receiver, introducing and assessing a new cyclic recursive least squares (RLS) algorithm: we show that, unlike the conventional RLS algorithms, the new algorithm is capable of tracking the periodically time-varying variation of the receiver structure, induced by the presence of a data-like narrow-band interferer     

一种自适应阵列天线波束赋形合成算法

自适应阵列天线中的波束赋形技术是智能天线数字信号处理部分的核心,在介绍和比较常用波束赋形算法以及RLS算法的基础上,提出了-种改进的RLS算法以提高系统的性能。对于用自适应阵列天线改善GPRS基站系统,提高其容量、减少干扰信号、提高信噪比、提高系统频谱利用率有很大的现实意义。     

Blind adaptive MIMO receivers for space-time block-coded DS-CDMA systems in multipath channels using the constant modulus criterion

We propose blind adaptive multi-input multi-output (MIMO) linear receivers for DS-CDMA systems using multiple transmit antennas and space-time block codes (STBC) in multipath channels. A space-time code-constrained constant modulus (CCM) design criterion based on constrained optimization techniques is considered and recursive least squares (RLS) adaptive algorithms are developed for estimating the parameters of the linear receivers. A blind space-time channel estimation method for MIMO DS-CDMA systems with STBC based on a subspace approach is also proposed along with an efficient RLS algorithm. Simulations for a downlink scenario assess the proposed algorithms in several situations against existing methods.     

Code-aided interference suppression for DS/CDMA communications. II.Parallel blind adaptive implementations

For pt.I see ibid., vol.45, no.9, p.1101-11 (1997). An adaptive code-aided technique for the simultaneous suppression of narrow-band interference (NBI) and multiple-access interference (MAI) in direct-sequence code-division multiple-access (DS/CDMA) networks is proposed. This technique is based on the recursive least-squares (RLS) version of the minimum mean-square error (MMSE) algorithm for multiuser detection. The convergence dynamics of the RLS blind adaptive algorithm for suppressing the combined NBI and MAI are analyzed. The steady-state performance of this algorithm in terms of the signal-to-interference ratio (SIR) is also derived. Systolic array structures for parallel implementations of the RLS adaptive interference suppression algorithms are then proposed. Versions of the rotation-based QR-RLS algorithms for both the blind adaptation mode and the decision-directed adaptation mode are derived. These algorithms exhibit high degrees of parallelism, and can be mapped to VLSI systolic arrays to exploit massively parallel signal processing computation     

数字预失真器模型参数辨识算法研究

数字基带预失真技术是补偿功放非线性的最有效方法之一,而自适应算法的选择很大程度上影响着系统的预失真性能。其中,最小均方误差(LMS)算法和递归最小二乘法(RLS)是最常用的自适应收敛算法,在综合分析两种算法优缺点的基础上,提出了一种基于正弦函数的归一化LMS(NLMS)算法和RLS算法的组合算法。仿真结果表明,该组合算法在达到与RLS同样预失真精度的前提下,可大大减小计算量。     

A recursive least M-estimate algorithm for robust adaptive filtering in impulsive noise: fast algorithm and convergence performance analysis

This paper studies the problem of robust adaptive filtering in impulsive noise environment using a recursive least M-estimate algorithm (RLM). The RLM algorithm minimizes a robust M-estimator-based cost function instead of the conventional mean square error function (MSE). Previous work has showed that the RLM algorithm offers improved robustness to impulses over conventional recursive least squares (RLS) algorithm. In this paper, the mean and mean square convergence behaviors of the RLM algorithm under the contaminated Gaussian impulsive noise model is analyzed. A lattice structure-based fast RLM algorithm, called the Huber Prior Error Feedback-Least Squares Lattice (H-PEF-LSL) algorithm is derived. Part of the H-PEF-LSL algorithm was presented in ICASSP 2001. It has an order O(N) arithmetic complexity, where N is the length of the adaptive filter, and can be viewed as a fast implementation of the RLM algorithm based on the modified Huber M-estimate function and the conventional PEF-LSL adaptive filtering algorithm. Simulation results show that the transversal RLM and the H-PEF-LSL algorithms have better performance than the conventional RLS and other RLS-like robust adaptive algorithms tested when the desired and input signals are corrupted by impulsive noise. Furthermore, the theoretical and simulation results on the convergence behaviors agree very well with each other.