Improved CMA-FSE blind equalization algorithm for wireless ultraviolet communication

There are serious intersymbol interference (ISI) and signal attenuation in wireless ultraviolet communication system.Aiming at this problem,an improved constant modulus fractionally spaced equalizer (CMA-FSE) based on signal-to-noise (SNR) estimation was proposed.The algorithm combined the fractionally spaced equalizer (FSE) and constant modulus algorithm (CMA) for blind equalization of wireless ultraviolet channels.The input SNR was measured by the mean square value of the received signal,and it was used to determine the best iterative step to ensure the convergence of the equalization algorithm.Simulation results show that the improved CMA-FSE algorithm can converge rapidly under various SNR,and it can effectively suppress ISI and improve the BER performance of the system.Compared with the existing algorithms,the improved algorithm is more useful in channel tracking and noise suppression.     

Global convergence of fractionally spaced Godard (CMA) adaptiveequalizers

The Godard (1980) or constant modulus algorithm (CMA) equalizer is perhaps the best known and the most popular scheme for blind adaptive channel equalization. Most published works on blind equalization convergence analysis are confined to T-spaced equalizers with real-valued inputs. The common belief is that analysis of fractionally spaced equalizers (FSEss) with complex inputs is a straightforward extension with similar results. This belief is, in fact, untrue. We present a convergence analysis of Godard/CMA FSEs that proves the important advantages provided by the FSE structure. We show that an FSE allows the exploitation of the channel diversity that supports two important conclusions of great practical significance: (1) a finite-length channel satisfying a length-and-zero condition allows Godard/CMA FSE to be globally convergent, and (2) the linear FSE filter length need not be longer than the channel delay spread. Computer simulation demonstrates the performance improvement provided by the adaptive Godard FSE     

Blind fractionally spaced equalization of noisy FIR channels:direct and adaptive solutions

Blind fractionally spaced equalizers reduce intersymbol interference using second-order statistics without the need for training sequences. Methods for finding FIR zero-forcing blind equalizers directly from the observations are described, and adaptive versions are developed. In contrast, most current methods require channel estimation as a first step to estimating the equalizer. The direct methods can be zero-forcing, minimum mean-square error, or even minimum mean square error (MMSE) within the class of zero-forcing equalizers. Performance of the proposed methods and comparisons with existing approaches are shown for a variety of channels, including an empirically measured digital microwave channel     

Blind adaptive spatial-temporal equalization algorithms forwireless communications using antenna arrays

Antenna arrays are used for diversity reception so as to improve the quality of wireless communication systems. To make full use of the information contained in each sensor, a spatial-temporal equalizer is used to remove intersymbol interference and mitigate the additive channel noise. This equalizer can be used in the wireless communication systems to improve the performance. This article introduces two blind adaptive algorithms for spatial-temporal equalization. Computer simulation demonstrates that the new algorithms converge faster than fractionally spaced constant-modulus algorithm (FS-CMA)     

A fractionally spaced blind equalizer based on linear programming

We formulate the blind fractionally spaced equalization (FSE) problem as one that minimizes a piecewise linear convex function subject to some linear constraints on the equalizer parameters. We show that this formulation achieves both the interference removal and the carrier phase recovery when the input signal possesses a certain quadrature amplitude modulation (QAM) type symmetry. A fast linear programming implementation is presented to solve the convex minimization problem. Computer simulation results indicate the new linear programming-based FSE is able to accurately equalize channels that are known to be not equalizable by T-spaced (or baud rate) blind equalizers and yields superior performance to other blind FSE methods     

Adaptive blind equalization for MIMO systems uadaptive blind equalization for MIMO systems under α-stable noise environmentnder α-stable noise environment

The presence of non-Gaussian impulsive noise in wireless system can degrade the performance of existing equalizers and signal detectors. In this paper, the problem of blind source separation and equalization for MIMO systems in heavy-tailed impulsive noise is studied. A generalized multiuser constant modulus cost function by employing the fractional lower-order statistic of the equalizer input signal is proposed. The associated adaptive blind equalization algorithm based on a stochastic gradient descent method is defined as fractional lower-order multi-user constant modulus algorithm (FLOS MU CMA). Computer simulations are presented to illustrate the performance of the new algorithm.     

Application of Recurrent Wavelet Neural Networks to the Digital Communications Channel Blind Equalization

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l0-范数约束的稀疏多径信道分数间隔双模式盲均衡算法

针对深衰落稀疏多径信道下多进制相移键控（Multiple Phase Shift Keying,MPSK）信号的盲均衡问题,提出了一种l₀-范数约束的分数间隔稀疏自适应双模式盲均衡算法.该算法借鉴传统的分数间隔双模式盲均衡算法思想,结合稀疏自适应滤波理论,首先利用l₀-范数对均衡器抽头系数进行稀疏性约束,构造出一种l₀-范数约束的分数间隔双模式最小均方误差代价函数,然后依据梯度下降法推导出盲均衡器抽头系数更新公式,并对迭代步长进行归一化和比例系数化.理论分析和仿真实验表明,与基于门限稀疏化的盲均衡算法、基于分数阶范数的盲均衡算法及分数间隔双模式盲均衡算法相比,本文所提算法在保证较快收敛速度的前提下,能有效降低剩余符号间干扰.本文设计的盲均衡算法为水声通信系统中接收方恢复出发送信号,提供了一种快速有效的方法.     

Fractionally spaced equalizer based on dynamically varying modulus algorithm for spectrally efficient channel compensation in SC-FDMA based systems

Orthogonal frequency division multiplexing (OFDM) based wireless communication systems are expected to satisfy the thirst for ever increasing demand on higher spectral efficiency. But, OFDM systems suffer from peak to average power ratio (PAPR) and inter carrier interference (ICI) problems. It is observed that when OFDM is used in the uplink, PAPR problem is more severe and the relative mobility of the user equipments with respect to the base station will cause Doppler spread which leads to ICI. One of the solutions to minimize PAPR and ICI is single carrier frequency division multiple access. But there is a tradeoff in spectral efficiency. The main objective of this paper is to evaluate the performance of fractionally spaced equalizer (FSE) for blind channel estimation based on higher order statistics and to identify any better alternative to improve its performance. Dynamically varying modulus algorithm (DVMA) based FSE is proposed in this paper which is a better alternative for supervised equalization. The simulation results prove that FSE blind equalizer based on DVMA outperform the conventional supervised and blind equalizers.     

一种用于水声通信的快速自适应均衡器设计

信道均衡是现代水声通信系统中克服码间干扰的重要手段,根据时变水声信道需进行信道均衡的要求,设计了一种判决反馈盲均衡器。针对恒模算法在固定步长下存在收敛速度与剩余误差的矛盾缺陷,提出了一种基于剩余误差的变步长恒模算法,并对改进算法进行了计算机仿真及试验测试,结果表明,改进算法无论是在收敛性能还是在均衡效果上都有大幅提高,在实际水声通信中具有较好的应用价值。     

Performance of smart lightwave receivers with linear equalization

Signal processing techniques can be used to reduce linear and nonlinear distortion in high-speed lightwave systems caused by fiber dispersion and nonideal responses of optoelectronic and electronic components. The improvement in the performance of 2.5 and 10 Gb/s intensity modulation, direct detection systems is assessed for receivers which utilize an analog taped delay line equalizer to compensate for signal distortion. Synchronous and fractionally spaced equalizers are evaluated. Smart receivers that jointly optimize the decision time, decision threshold, and equalizer tap weights under a minimum bit error ration criterion are considered. This yields the optimum system performance and allows consideration of both reduced distortion and enhanced noise arising from the signal processing. The effectiveness of the equalization is determined as a function of several important system parameters. Three-tap and five-tap synchronous equalizers yield virtually the same improvement in receiver sensitivity. Depending on the system, a five-tap fractionally spaced equalizer with half-bit-period tap spacing may or may not be significantly more effective than a three-tap synchronous equalizer     

Performance of trellis codes for a class of equalized ISI channels

The performance of trellis codes is examined for a class of intersymbol interference (ISI) channels that occur in high-frequency radio systems. The channels considered are characterized by in-band spectral nulls and by a rapid time variation. The baseline modulation technique is 4QAM (four-point quadrature amplitude modulation). When spectral nulls are absent, performance of fractionally spaced linear equalizers and trellis decoders is found to be near ideal and to be better than using symbol-spacing in the equalizer. However, error propagation in the feedback path, resulting from equalizer-based decisions, ruins the performance of the combination of decision-feedback equalizers and trellis decoders when spectral nulls are present. Their performance can be improved by using fractionally spaced feedforward equalizer sections and by designing the decoder to compensate for ISI. Rate 2/3 codes are found to outperform rate 1/2 codes in error performance     

基于线性预测的盲最小均方误差均衡器

盲过采样均衡器仅用二阶统计量便可减小码间干扰,该文采用线性预测方法,提出了一种盲最小均方误差(MMSE)均衡器。该方法不需要先估计信道,可直接利用过采样的接收信号均衡信道。此外,该均衡器可采用递推最小二乘算法自适应地实现,具有较高的计算效率。仿真结果表明,该均衡器比基于线性预测的盲置零均衡器有更小的符号估计均方误差。     

Fractionally spaced equalizers

Modern digital transmission systems commonly use an adaptive equalizer as a key part of the receiver. The design of this equalizer is important since it determines the maximum quality attainable from the system, and represents a high fraction of the computation used to implement the demodulator. Analytical results offer a new way of looking at fractionally spaced equalizers and have some surprising practical implications. This article describes the data communications problem, the rationale for introducing fractionally spaced equalizers, new results, and their implications. We then apply those results to actual transmission channels     

Protocol-aided channel equalization in wireless ATM

We study the equalization problem in time division multiple access wireless asynchronous transfer mode (ATM) systems. Aiming at minimizing the overhead associated with equalization, we propose a protocol-aided channel equalization (PACE) approach for wireless ATM. Specifically, the medium access control (MAC) and data link control (DLC) protocols are exploited to provide known ATM cell headers to the receiver at the base station. A blind channel estimation-decision feedback equalizer (BCE-DFE) algorithm is developed for uplink data transmissions. There are two advantages of the BCE-DFE algorithm: the elimination of training symbols for uplink data bursts and the removal of channel estimation error propagation suffered by conventional block equalization schemes. Simulation results show the BCE-DFE has a robust performance for wireless ATM uplink data transmissions over fast time-varying channels     

Sampling and prefiltering effects on blind equalizer design

In the development of equalization algorithms for unknown channels, the effects of the sampling rate and the analog receive prefilter prior to discretization of the received signal are often overlooked. In this paper, these effects are investigated. The relationship between the fractionally spaced output samples of a noise-limiting prefilter and the symbol spaced output samples of a matched filter is studied for both the time-invariant and the time-varying channels. It is shown that the prefilter and the sampling rate can have significant effects on blind equalization algorithms. Thus, this paper provides a common framework for comparing different blind algorithms that are studied in the literature with different sampling rates. A case study of the well-known subspace method for blind channel identification is presented. The effects of the noise color due to the prefilter on equalizers is investigated, and the sensitivity of the truncation of the overall channel impulse response in terms of the mean squared error (MSE) performance criterion is investigated through numerical examples     

Kalman Filter-Trained Recurrent Neural Equalizers for Time-Varying Channels

Recurrent neural networks have been successfully applied to communications channel equalization because of their modeling capability for nonlinear dynamic systems. Major problems of gradient-descent learning techniques commonly employed to train recurrent neural networks are slow convergence rates and long training sequences required for satisfactory performance. This paper presents decision-feedback equalizers using a recurrent neural network trained with Kalman-filtering algorithms. The main features of the proposed recurrent neural equalizers, using the extended Kalman filter and the unscented Kalman filter, are fast convergence and good performance using relatively short training symbols. Experimental results for various time-varying channels are presented to evaluate the performance of the proposed approaches over a conventional recurrent neural equalizer.     

Blind equalizer for constant-modulus signals based on Gaussian process regression

A new blind equalization method for constant modulus (CM) signals based on Gaussian process for regression (GPR) by incorporating a constant modulus algorithm (CMA)-like error function into the conventional GPR framework is proposed. The GPR framework formulates the posterior density function for weights using Bayes' rule under the assumption of Gaussian prior for weights. The proposed blind GPR equalizer is based on linear-in-weights regression model, which has a form of nonlinear minimum mean-square error solution. Simulation results in linear and nonlinear channels are presented in comparison with the state-of-the-art support vector machine (SVM) and relevance vector machine (RVM) based blind equalizers. The simulation results show that the proposed blind GPR equalizer without cumbersome cross-validation procedures shows the similar performances to the blind SVM and RVM equalizers in terms of intersymbol interference and bit error rate.     

Multipath Outage Performance of Digital Radio Receivers Using Finite-Tap Adaptive Equalizers

Recent analysis/simulation studies have quantified the multipath outage statistics of digital radio systems using ideal adaptive equalization. In this paper, we consider the use of finite-tap delay line equalizers, with the aim of determining how many taps are needed to approximate ideal performance. To this end, we assume anM-level QAM system using cosine rolloff spectral shaping and an adaptive equalizer with either fractionally spaced or synchronously spaced taps. We invoke a widely used statistical model for the fading channel and computer-simulate thousands of responses from its ensemble. For each trial, we compute a detection signal-to-distortion measure, suitably maximized with respect to the tap gains. We can thereby obtain probability distributions of this measure for specified combinations of system parameters. These distributions, in turn, can be interpreted as outage probabilities (or outage seconds) versus the number of modulation levels. A major finding of this study is that, for the assumed multipath fading model, very few taps (the order of five) are needed to approximate the performance of an ideal infinite-tap equalizer. We also find that a simple, suboptimal form of timing recovery is generally quite adequate, and that fractionally spaced equalizers are more advantageous than synchronously spaced equalizers with the same number of taps. This advantage is minor for rolloff factors of 0.5 and larger but increases dramatically as the rolloff factor approaches zero.     

Trellis-coded CPFSK and soft-decision feedback equalization for micro-cellular wireless applications

In this paper, trellis-codedM-ary CPFSK with noncoherent envelope detection and adaptive channel equalization are investigated to improve the bit error rate (BER) performance of microcellular digital wireless communications systems. For the same spectral efficiency, the trellis-coded modulation (TCM) schemes studied outperform minimum shift keying (MSK) with noncoherent or differentially coherent detection in Rayleigh fading channels. For the case of frequency-selective fading channels, adaptive channel equalization is applied to mitigate the time-variant intersymbol interference (ISI). A new equalizer structure is proposed which, in its feedback path, makes use of fractionally spaced signal samples instead of symbol-spaced hard decisions on transmitted symbols. Computer simulation results indicate that the soft-decision feedback equalizer (SDFE) can significantly improve the system's performance.