Code acquisition for DS/SS communications in non-Gaussian impulsive channels

In this letter, we propose a new detector for code acquisition systems in non-Gaussian noise channels. Modeling the acquisition problem as a hypothesis testing problem, a detector is derived for non-Gaussian, symmetric /spl alpha/-stable noise, based on the locally optimum detection technique. Numerical results show that the proposed detector can offer robustness and substantial performance improvement over the conventional schemes in non-Gaussian channels.     

弱相关非高斯环境下基于局部最佳检测器的伪码捕获方法

该文为解决弱相关非高斯噪声环境下的伪码捕获问题,提出了一种基于局部最佳检测算法的伪码捕获方法,将伪码捕获等价为假设检验问题,将弱相关非高斯噪声建模为一阶滑动平均SS噪声模型,利用局部最佳检测算法推导出弱相关非高斯噪声环境下的伪码捕获检测统计量,在此基础上对检测统计量进行了简化,给出了其实现结构,并与传统的伪码捕获方法进行了性能仿真对比,仿真结果表明该文所提出的捕获方法在弱相关非高斯噪声环境下检测性能有较大幅度的提高,且非高斯噪声脉冲特性越明显,所设计的检测器优势越明显。     

Robust Detectors for Signals in Non-Gaussian Noise

The robustness of suboptimal nonlinear detectors for known discrete-time signals in non-Gaussian noise is investigated. The measure of robustness used is the degradation of asymptotic relative efficiency (compared to a linear detector) from that achieved by an optimal nonlinear detector. The first order density of non-Gaussian noise is modeled as a mixture of a small variance Gaussian background noise pdf and a large variance impulsive pdf.     

Fuzzy decorrelating detector for non-Gaussian CDMA channel

A fuzzy decorrelating detector for CDMA non-Gaussian channels is proposed. The proposed scheme combines a linear decorrelator with a nonlinear preprocessor based on fuzzy logic and rank ordering that is incorporated to combat impulsive noise. Simulation results show that the proposed technique is very robust in combating impulsive noise.     

Detection in correlated impulsive noise using fourth-ordercumulants

We consider detection and estimation in correlated impulsive noise. The non-Gaussian impulsive noise is modeled as the sum of two linear processes: a nominal part and an impulsive part. This model admits correlated impulsive bursts lasting many data samples. Identifiability of the noise model is established using fourth- and second-order cumulants. Under this model, the correlated time series can be whitened and an appropriate memoryless nonlinearity applied to attenuate the impulsive events. A detection statistic is then formed from the output of the nonlinearity. In the threshold detection case, the use of cumulants allows identification of the noise in the presence of the signal to be detected, obviating the need for noise-only training records. Simulation results with a sample size of 512 show small loss in detector performance versus an ideal detector with no impulsive part present     

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.     

基于分数低阶统计量的盲多用户检测算法

多用户检测算法是抑制CDMA系统中多址干扰的重要手段,但广泛存在的非高斯信道噪声会降低以往的基于高斯噪声模型假设的算法性能.本文采用α稳定分布作为噪声模型,提出了基于分数低阶统计量的盲多用户检测算法,并对该算法进行了理论分析.仿真和分析表明,该算法具有很好的韧性,同时适用于高斯噪声和脉冲噪声环境.     

Signed-rank nonparametric multiuser detection in non-Gaussian channels

We present a novel nonparametric multiuser detector for non-Gaussian channels that is based on the signed-rank norm for linear regression. Analytical and simulation results show that the proposed detector offers similar or better performance as compared to the minimax robust detector, but without requiring any a priori information on the noise. The complexity of this detector is lower than that of the pseudo-norm nonparametric detector stated previously by the authors. This is due to the fact that in contrast to the latter, it is not necessary to compute the intercept parameter for the signed-rank detector proposed in this correspondence. We analyze the behavior of the blind version of this detector and show that it outperforms the blind minimax detector. We also show that this detector has a bounded influence function and hence it is robust.     

Multiuser detection in impulsive channels

The present paper deals with the problem of data detection in direct-sequence code-division multiple-access (CDMA) systems with non-Gaussian ambient noise. This issue arises in pratical situations because many physical channels in which multiple-access communications is applied are known to be decidedly non-Gaussian, due largely to impulsive phenomena. (Such channels include urban and indoor radio channels, and underwater acoustic-modem channels). The optimum multiuser detector for the additive noise channel model is derived, and several suboptimal multiuser detectors are proposed. Moreover, for performance comparison purposes the robust multiuser detector, recently proposed in the literature, is also considered.     

Improved Robust Techniques for Multiuser Detection in Non-Gaussian Channels

In many physical channels where multiuser detection techniques are to be applied, the ambient channel noise is known through experimental measurements to be decidedly non-Gaussian, due largely to impulsive phenomena. This is due to the impulsive nature of man-made electromagnetic interference and a great deal of natural noise. This paper presents a robust multiuser detector for combating multiple access interference and impulsive noise in code division multiple access (CDMA) communication systems. A new M-estimator is proposed for "robustifying" the detector. The approach is corroborated with simulation results to evaluate the performance of the proposed robust multiuser detector compared with that of the linear decorrelating detector, and the Huber and the Hampel M-estimator based detectors. Simulation results show that the proposed detector with significant performance gain outperforms the linear decorrelating detector, and the Huber and the Hampel M-estimator based detectors. This paper also presents an improved robust blind multiuser detection technique based on a subspace approach, which requires only the signature waveform and the timing of the desired user to demodulate that user's signal. Finally, we show that the robust multiuser detection technique and its blind adaptive version can be applied to both synchronous and asynchronous CDMA channels.     

Neural networks applications for CDMA systems in non-Gaussian multi-path channels

Non-Gaussian noise is one of the most common noise models observed in wireless channels. This type of noise has severe impact on wireless systems with multiuser detection devices. In this paper, the issue of multiuser detection in non-Gaussian noise multipath channel is addressed. We also pay a close attention to the neural network applications, and propose a new robust neural network detector for multipath impulsive channels. The maximal ratio combining (MRC) technique is adopted to combine the multipath signals. Moreover, we discuss the performance of the proposed multiuser neural network decorrelating detector (NNDD), under class A Middleton model. Furthermore, the performance of the system under power imbalance scenario is shown. We show that the proposed NNDD has magnificent effect on the system performance. The system performance is measured through the bit error rate (BER). It is shown that the proposed robust receiver reduces the impact of the impulsive noise by processing the received signal and clipping the extreme amplitudes.     

脉冲噪声对空时分组码性能影响的研究

该文对脉冲及非高斯噪声环境下空时分组码(STBC)性能进行了研究。采用脉冲和高斯加性混合噪声模型,利用矩母函数(MGF)分析方法,通过建立多发单收(MISO)近似等效模型,推导出Rayleigh衰落信道下MISO空时分组码误符号率(SER)闭式表达式的渐近解。在此基础上,对于不同脉冲噪声发生概率、脉冲噪声与高斯噪声功率比条件下STBC的性能进行了分析。结果表明,即使在高信噪比情况下,混合噪声也将会使STBC系统性能显著降低。蒙特卡洛仿真结果验证了SER闭式解的有效性。     

A New M-Estimator Based Robust Multiuser Detection in Flat-Fading Non-Gaussian Channels

We have proposed a new M-estimator based structure for noncoherent demodulation of differentially phase-shift keyed (DPSK) signals transmitted simultaneously via direct sequence code division multiple access (CDMA) flat-fading channel and embedded in impulsive noise. The approach is also corroborated with simulation results to show the efficacy of the proposed detector with the proposed M-estimator in synchronous flat-fading non-Gaussian channels. The gross error sensitivity for the proposed estimator is analyzed. Further, lower bounds for the explosion and implosion breakdown points of the proposed estimator are derived.     

Adaptive path selective fuzzy decorrelating detector under impulsive noise for multipath fading CDMA systems

This letter proposes a novel adaptive path selective fuzzy decorrelating (APSFD) detector for direct-sequence code- division multiple-access (DS-CDMA), systems with time-varying multipath fading channels under impulsive noise. The proposed detector combines adaptive path selective decorrelating (APSD) detector with a fuzzy median filter which is based on fuzzy rank ordering of samples to eliminate the effect of impulsive noise. Simulation results clearly show that the proposed detector eliminates the effect of impulsive noise and improves the performance of APSD detector under high impulsive noise.     

RBF network assisted adaptive path selective decorrelating detector under impulsive noise for multipath fading CDMA systems

This paper proposes a novel radial basis function assisted adaptive path selective decorrelating detector for direct sequence code division multiple access systems with time-varying multipath fading channels under impulsive noise. The proposed detector combines adaptive path selective decorrelating detector (APSDD) with a radial basis function (RBF) network to eliminate the effect of impulsive noise. Simulation results clearly show that the proposed detector eliminates the effect of impulsive noise and improves the performance of APSDD under high impulsive noise.     

Nonparametric multiuser detection in non-Gaussian channels

Existing multiuser detection techniques in wireless systems are based on the assumption that some information on the parameters of the probability density function (pdf) of ambient noise is available. Such information may not be available in all cases, particularly for non-Gaussian and impulsive noises, or may change depending on circumstances. In this paper, we present a technique for multiuser detection that does not require any a priori knowledge about the noise parameters. This method is based on using pseudo norms for linear nonparametric regression. Analytical and simulation results show that the proposed method offers an improved, or at least comparable, performance over existing robust techniques in the absence of any information on the nature of noise in the environment. The increased computational complexity is marginal compared to existing parametric detectors. In addition, the proposed nonparametric detector is portable in the sense that it does not need to be tuned for different noise models without any considerable degradation of performance. We also show that in non-Gaussian noise, the performance of blind adaptive nonparametric multiuser detectors is better than that of robust multiuser detectors.     

脉冲噪声环境下改进的顽健循环时延估计算法

研究了脉冲噪声环境下循环平稳信号的时延估计问题,针对脉冲噪声环境中基于传统二阶谱相关函数的时延估计方法性能退化问题,提出了基于分数低阶循环谱的改进顽健算法。相对于传统算法,新算法对脉冲噪声、高斯噪声、干扰信号都具有较好的抑制作用。仿真结果证明了算法的有效性和顽健性。     

Performance of block Markov superposition transmission over non-Gaussian impulsive channels

Block Markov superposition transmission scheme was used over channels with symmetric alpha-stable (SαS) impulsive noise.Based on the equivalent genie-aided system,the lower bound of the block Markov superposition transmission system was analyzed.Numerical simulations over non-Gaussian impulsive channels with different characteristic exponents show that,in the low bit-error rate region,performance of the block Markov superposition transmission system matches well with the lower bound.Block Markov superposition transmission scheme performs well (with 0.85 dB away from Shannon limits at the BER of 10^-5) over non-Gaussian impulsive channels.     

Detection of weak signals in non-Gaussian noise

A locally optimum detector structure is derived for the detection of weak signals in non-Gaussian environments. Optimum performance is obtained by employing a zero-memory nonlinearity prior to the matched filter that would be optimum for detecting the signal were the noise Gaussian. The asymptotic detection performance of the locally optimum detector under non-Gaussian conditions is derived and compared with that for the corresponding detector optimized for operations in Gaussian noise. Numerical results for the asymptotic detection performance are shown for signal detection in noise environments of practical interest.