平坦衰落信道下一种基于进化粒子滤波的盲检测器

该文针对平坦瑞利衰落信道下的盲粒子滤波检测器存在的样本贫化问题,提出了一种基于进化粒子滤波的盲检测方法。在粒子滤波的重采样阶段,引入进化规化思想,即采用进化粒子滤波的方法解决样本的贫化现象,从而构成了一种基于进化粒子滤波的盲检测器。仿真结果表明,在信道模型系数未知条件下,该检测器的误码率性能较盲粒子滤波检测器优越,接近已知信道模型系数情况下的混合卡尔曼滤波检测器性能。     

非高斯噪声环境的进化粒子滤波盲检测器

对于信道模型系数未知的平坦瑞利衰落信道下非高斯噪声环境中的盲信号检测,提出了一种基于进化粒子滤波的盲检测算法。该算法能够解决一般的粒子滤波对于估计长时间不变的状态存在的样本贫化的问题和系统噪声的非高斯问题。仿真试验结果证明,在信道模型系数未知的平坦衰落信道下,非高斯的噪声环境中,该算法性能优越,接近达到已知信道模型系数情况下的混合卡尔曼滤波算法的性能。     

Wavelet-based sequential Monte Carlo blind receivers in fading channels with unknown channel statistics

Recently, an adaptive Bayesian receiver for blind detection in flat-fading channels was developed by the present authors, based on the sequential Monte Carlo methodology. That work is built on a parametric modeling of the fading process in the form of a state-space model and assumes the knowledge of the second-order statistics of the fading channel. In this paper, we develop a nonparametric approach to the problem of blind detection in fading channels, without assuming any knowledge of the channel statistics. The basic idea is to decompose the fading process using a wavelet basis and to use the sequential Monte Carlo technique to track both the wavelet coefficients and the transmitted symbols. A novel resampling-based wavelet shrinkage technique is proposed to dynamically choose the number of wavelet coefficients to best fit the fading process. Under such a framework, blind detectors for both flat-fading channels and frequency-selective fading channels are developed. Simulation results are provided to demonstrate the excellent performance of the proposed blind adaptive receivers.     

A blind particle filtering detector of signals transmitted over flat fading channels

A new particle filtering detector (PFD) is proposed for blind signal detection over flat Rayleigh fading channels whose model coefficients are unknown. The detector employs a hybrid importance function and a mixture Kalman filter. It also incorporates an auxiliary particle filtering strategy with a smoothing kernel in the resampling step. Further, by considering practical information of communication systems and the physical interpretation of the adopted second-order autoregressive (AR) channel model, a fully blind particle filtering implementation is developed. The structure of the proposed PFD can be easily adapted to other system requirements. Simulations are provided that demonstrate the performance of the new PFD.     

SMC-based blind detection for DS-CDMA systems over multipath fading channels

This letter derives a computationally efficient sequential Monte Carlo solution for blind detection of direct-sequence code-division multiple-access systems over multipath fading channels by decomposing the observed data into a number of signal components. Then the parameters of each component can be estimated by the sequential importance sampling and Kalman filtering. In comparison with other similar receivers, simulation results demonstrate that the proposed solution achieves the desirable performance with a significantly reduced computational complexity.     

Monte Carlo Bayesian Signal Processing for Wireless Communications

Many statistical signal processing problems found in wireless communications involves making inference about the transmitted information data based on the received signals in the presence of various unknown channel distortions. The optimal solutions to these problems are often too computationally complex to implement by conventional signal processing methods. The recently emerged Bayesian Monte Carlo signal processing methods, the relatively simple yet extremely powerful numerical techniques for Bayesian computation, offer a novel paradigm for tackling wireless signal processing problems. These methods fall into two categories, namely, Markov chain Monte Carlo (MCMC) methods for batch signal processing and sequential Monte Carlo (SMC) methods for adaptive signal processing. We provide an overview of the theories underlying both the MCMC and the SMC. Two signal processing examples in wireless communications, the blind turbo multiuser detection in CDMA systems and the adaptive detection in fading channels, are provided to illustrate the applications of MCMC and SMC respectively.     

一种粒子滤波的盲多用户检测快速算法

该文在时间观察状态空间模型基础上,针对粒子滤波计算复杂的问题,构造了一种在同步快变平衰落信道下计算复杂度低的粒子滤波的DS-CDMA盲多用户检测快速算法。该算法通过对超过门限数目的粒子分类,以不同类别粒子的概率差值作为粒子滤波所需粒子数目是否足够的判断准则,自动调节不同情况下所需的粒子数目,并对不同类别粒子概率差值下盲多用户检测性能进行分析。仿真结果表明,该文算法可以在保证盲多用户检测性能的前提下有效地降低运算复杂度,且检测性能与概率差值成正比。     

Modified SMC method of blind multiuser detection for DS-CDMA systems over fading channels

This paper presents the application of sequential Monte Carlo (SMC) methodology for blind detection in wireless direct sequence code division multiple access (DS-CDMA) systems over fading channels. It is known that the conventional SMC method requires a high-computational complexity that grows exponentially with the number of active users. This paper proposes a solution to this problem by employing Cholesky factorization to decompose the observed data into separate components for each user and then the parameters of each user are estimated with the SMC inference method under the decision feedback framework. Based on these concepts, an efficient blind decision feedback SMC (DF-SMC) receiver is developed for differentially encoded DS-CDMA systems. Simulation results demonstrate the promising performance of the proposed receiver for both flat fading and frequency-selective fading channels.     

基于粒子滤波的Turbo盲均衡

粒子滤波是一种基于贝叶斯估计的算法,在信道盲辨识和盲均衡问题上具有快收敛、抗深衰信道等优势。Turbo盲均衡在低信噪比条件下有较好的误码性能。为了在深衰信道下使通信具有良好的误码性能,对粒子滤波盲均衡算法进行改进,改进算法的重要性采样函数利用了粒子的先验信息,得到一种软输入软输出的粒子滤波盲均衡算法。依据Turbo盲均衡的框架结构实现了一种基于粒子滤波的Turbo盲均衡算法,该算法利用信道编码带来的编码增益,提高了均衡和信道辨识的性能。仿真结果表明相比粒子滤波盲均衡算法本文提出算法的误码率性能提高1dB左右,误帧率性能则提高了3dB以上,经分析可知在信道系数估计较为准确的条件下,系统数据帧几乎没有误码。      

Subspace methods for blind joint channel estimation and multiuser detection in CDMA systems

Recently developed subspace techniques for blind adaptive multiuser detection are briefly reviewed first. In particular, blind methods based on signal subspace tracking for adapting linear multiuser detectors in AWGN CDMA channels are considered, as well as extensions of these techniques to frequency selective fading channels, dispersive channels, and antenna array spatial processing. In addition, subspace‐based nonlinear adaptive techniques for robust blind multiuser detection in non‐Gaussian ambient noise channels are also described. Several new techniques are then developed within the subspace framework for blind joint channel estimation and multiuser detection, under some specific channel conditions. These include (1) an adaptive receiver structure for joint multiuser detection and equalization in dispersive CDMA channels, (2) a subspace method for joint multiuser detection and equalization in unknown correlated noise, and (3) a method for joint interference suppression and channel tracking in time‐varying fading channels. This revised version was published online in August 2006 with corrections to the Cover Date.     

A blind detector for Rayleigh flat-fading channels with non-Gaussian interference via the particle learning algorithm

A blind particle learning detector (BPLD) is developed for signal detection in Rayleigh flat-fading channels with non-Gaussian interference. The parameters of the fading channel model and the noise model are all unknown. The impulsive noise is modeled as a mixture of Gaussian distributions, which is capable of representing a broad class of non-Gaussian noise. The particle learning algorithm is employed to simultaneously estimate signal and parameters of the fading channel model and the noise model. The delay weight method is used to improve the performance. Simulation results show that the performance of the BPLD proposed can follow closely the performance of the detector with known parameters of the fading channel model and the noise model.     

应用粒子滤波器实现混沌通信系统的盲信道均衡

粒子滤波器(Particle filter,PF)是一种结合重要性权重抽样的序贯蒙特卡罗方法,能够应用到任意状态空间模型,并且能较好地估计经过非线性变化后的随机变量的统计特性.本文应用粒子滤波器和信号建模技术研究混沌通信系统的盲信道均衡问题,发展基于混沌的通信系统的盲均衡技术.仿真结果证实了,当Logistic映射作为混沌发生器和通信场景为固定参数与时变衰落信道时,该盲信道均衡器与基于扩展卡尔曼滤波算法的盲均衡器和基于无先导变换的自适应盲均衡器相比,有较好的均衡实现.此外,利用本文的盲均衡算法,实现了一种混沌调制通信系统的解调.     

一种新的抗远近效应的盲DS-CDMA接收机

本文研究多径频率选择性衰落信道下直接序列扩频码分多址(DS-CDMA)信号的处理问题,提出了一种新型的盲接收机.该接收机不需预知多址干扰用户的扩频码,不需预知信道参数,只需已知期望用户的扩频码和粗略的定时,就可以完成用户的盲检测.同时,该接收机通过降维自适应去相关滤波和基于判决指导的自适应多径合并,来获得低成本和良好的抗衰落、抗远近效应性能.仿真结果验证了本文提出的接收机的优良性能.     

Adaptive joint detection and decoding in flat-fading channels viamixture Kalman filtering

A novel adaptive Bayesian receiver for signal detection and decoding in fading channels with known channel statistics is developed; it is based on the sequential Monte Carlo methodology that has emerged in the field of statistics. The basic idea is to treat the transmitted signals as “missing data” and to sequentially impute multiple samples of them based on the observed signals. The imputed signal sequences, together with their importance weights, provide a way to approximate the Bayesian estimate of the transmitted signals and the channel states. Adaptive receiver algorithms for both uncoded and convolutionally coded systems are developed. The proposed techniques can easily handle the non-Gaussian ambient channel noise. It is shown through simulations that the proposed sequential Monte Carlo receivers achieve near-bound performance in fading channels for both uncoded and coded systems, without the use of any training/pilot symbols or decision feedback. Moreover, the proposed receiver structure exhibits massive parallelism and is ideally suited for high-speed parallel implementation using the very large scale integration (VLSI) systolic array technology     

Algorithmic and architectural optimizations for computationally efficient particle filtering.

In this paper, we analyze the computational challenges in implementing particle filtering, especially to video sequences. Particle filtering is a technique used for filtering nonlinear dynamical systems driven by non-Gaussian noise processes. It has found widespread applications in detection, navigation, and tracking problems. Although, in general, particle filtering methods yield improved results, it is difficult to achieve real time performance. In this paper, we analyze the computational drawbacks of traditional particle filtering algorithms, and present a method for implementing the particle filter using the Independent Metropolis Hastings sampler, that is highly amenable to pipelined implementations and parallelization. We analyze the implementations of the proposed algorithm, and, in particular, concentrate on implementations that have minimum processing times. It is shown that the design parameters for the fastest implementation can be chosen by solving a set of convex programs. The proposed computational methodology was verified using a cluster of PCs for the application of visual tracking. We demonstrate a linear speed-up of the algorithm using the methodology proposed in the paper.     

Blind adaptive space-time multiuser detection with multipletransmitter and receiver antennas

The demand for performance and capacity in cellular systems has generated a great deal of interest in the development of advanced signal processing techniques to optimize the use of system resources. In particular, much work has been done on space-time processing in which multiple transmit/receive antennas are used in conjunction with coding to exploit spatial diversity. We consider space-time multiuser detection using multiple transmit and receive antennas for code-division multiple-access (CDMA) communications. We compare, via analytical bit-error-probability calculations, user capacity, and complexity, two linear receiver structures for different antenna configurations. Motivated by its appearance in a number of third-generation (3G) wideband CDMA standards, we use the Alamouti (see IEEE J. Select. Areas Commun., vol.16, p.1451-58, Oct. 1998) space-time block code for two-transmit-antenna configurations. We also develop blind adaptive implementations for the two transmit/two receive antenna case for synchronous CDMA in flat-fading channels and for asynchronous CDMA, in fading multipath channels. Finally, we present simulation results for the blind adaptive implementations     

LTE系统中小区搜索算法研究

设计了完整的LTE系统小区初始搜索算法,包括定时同步、频偏估计、循环前缀类型盲检测、扇区ID和小区ID组识别、帧同步算法,其中定时同步和频偏估计以及扇区ID识别由主同步信号在时域完成,循环前缀类型盲检测、小区ID组识别、帧同步由辅同步信号在频域完成。理论分析与仿真结果表明,所设计算法在AWGN与多径信道下均具有良好的性能,能够满足LTE系统小区搜索的性能需求。     

Performance of sequence estimation scheme of narrowband digital FMsignals with limiter-discriminator detection

A communication scheme using binary FM with noncoherent limiter-discriminator detection has been well known. Up to now, the improvement of bit error rate at the receiver side has been carried out through the bandwidth optimization of the IF filter, the decision feedback equalization (DFE), or simple two-state maximum likelihood sequence estimator (MLSE). This channel is inherently the intersymbol interference (ISI) channel due to the premodulation baseband filtering as well as the narrowband IF filtering. So the sequence estimation scheme using the Viterbi algorithm can be applied successfully, although the channel is not additive white Gaussian and maximum likelihood in the strict sense. In this paper, through computer simulations, we examine the actual BER improvement of the sequence estimation scheme with multiple-state trellis especially for MSK and GMSK signals. We mainly consider static AWGN and frequency nonselective Rician fading channels. Consequently, by adjusting the IF filter bandwidth, very large estimation gains are obtained compared to the conventional DFE or MLSE detector for AWGN and Rician fading channels. This scheme does not produce large demodulation delay and is implemented only by adding the signal processing part to the final stage of the receiver. This scheme seems to be very useful for any applications including satellite mobile channels     

A robust adaptive DFE receiver for DS-CDMA systems under multipathfading channels

This paper presents a novel receiver design from signal processing viewpoint for direct-sequence code-division multiple access (DS-CDMA) systems under multipath fading channels. A robust adaptive decision-feedback equalizer (DFE) is developed by using optimal filtering technique via minimizing the mean-square error (MSE). The multipath fading channels are modeled as tapped-delay-line filters, and the tap coefficients are described as Rayleigh distributions in order to imitate the frequency-selective fading channel. Then, a robust Kalman filtering algorithm is used to estimate the channel responses for the adaptation of the proposed DFE receiver under the situation of partially known channel statistics. The feedforward and feedback filters are designed by using not only the estimated channel responses but the uncertainties and error covariance of channel estimation as well. As shown in the computer simulations, the proposed adaptive DFE receiver is robust against the estimation errors and modeling dynamics of the channels. Hence, it is very suitable for receiver design in data transmissions through multipath fading channels encountered in most wireless communication systems     

一种新型的在瑞利信道下盲检测器设计

针对采用卡尔曼滤波或线性预测方案进行信号检测时,需要已知信道模型参数或预先估计信道参数这一局限性问题,提出一种新型的瑞利信道下的盲检测器。盲检测器通过设计粒子学习算法,能够在未知的信道衰落模型参数和噪声模型参数条件下检测信号。为了提升检测器的性能,采用信号延迟判决技术。仿真结果表明,盲检测器性能优异,已接近在已知信道模型参数下检测器的性能。该盲检测器易于并行设计实现,具有很高的实用价值。