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Improving the Rate of Convergence of Blind Adaptive Equalization for Fast Varying Digital Communication Systems
Iorkyase E.Tersoo,Michael O. Kolawole
International Journal of Advanced Computer Sciences and Applications , 2012,
Abstract: The recent digital transmission systems impose the application of channel equalizers with bandwidth efficiency, which mitigates the bottleneck of intersymbol interference for high-speed data transmission-over communication channels. This leads to the exploration of blind equalization techniques that do not require the use of a training sequence. Blind equalization techniques however suffer from computational complexity and slow convergence rate. The Constant Modulus Algorithm (CMA) is a better technique for blind channel equalization. This paper examined three different error functions for fast convergence and proposed an adaptive blind equalization algorithm with variable step size based on CMA criterion. A comparison of the existing and proposed algorithms’ speed of convergence shows that the proposed algorithm outperforms the other algorithms. The proposed algorithm can suitably be employed in blind equalization for rapidly changing channels as well as for high data rate applications.
A New Equalization Performance Analyzing Method for Blind Adaptive Equalizers Inspired by Maximum Time Interval Error  [PDF]
Guilad Suissa, Monika Pinchas
Journal of Signal and Information Processing (JSIP) , 2017, DOI: 10.4236/jsip.2017.82004
Abstract: Up to now, the Mean Square Error (MSE) criteria, the residual Inter-Symbol Interference (ISI) and the Bit-Error-Rate (BER) were used to analyze the equalization performance of a blind adaptive equalizer in its convergence state. In this paper, we propose an additional tool (additional to the ISI, MSE and BER) for analyzing the equalization performance in the convergence region based on the Maximum Time Interval Error (MTIE) criterion that is used for the specification of clock stability requirements in telecommunications standards. This new tool preserves the short term statistical information unlike the already known tools (BER, ISI, MSE) that lack this information. Simulation results will show that the equalization performance of a blind adaptive equalizer obtained in the convergence region for two different channels is seen to be approximately the same from the residual ISI and MSE point of view while this is not the case with our new proposed tool. Thus, our new proposed tool might be considered as a more sensitive tool compared to the ISI and MSE method.
New Results with Blind Time Domain Equalization for OFDM System  [PDF]
S. Elahmar,A. Djebbari,M. Bouziani,J.M. Rouvaen
Information Technology Journal , 2007,
Abstract: The Multicarrier Equalization by Restoration of RedundancY (MERRY) algorithm has been shown to blindly and adaptively shorten a channel to the length of the guard interval in an OFDM system. Most published works on blind Time Domain Equalization (TEQ) convergence analysis are confined to Ts-spaced equalizers. The common belief is that analysis of fractionally-spaced TEQ (FSTEQ’s) is a straightforward extension with similar results. This belief is, in fact, untrue. In this study, we present a convergence analysis of MERRY fractionally-spaced TEQ’s that proves the important advantages provided by the FSTEQ structure. We show that the FSTEQ MERRY algorithm converges significantly faster than the non-fractional TEQ MERRY algorithm. The main reason is that a fractionally-spaced blind adaptive TEQ admits infinitely many realizations of perfect channel shortening for a specific delay whereas a non-fractionally-spaced TEQ admits only one realization. Computer simulation demonstrates the performance improvement provided by the blind adaptive fractionally-spaced TEQ using MERRY algorithm for OFDM system.
Adaptive MMSE Equalizer for Blind Fractional Spaced CMA Channel Equalization through LMS Algorithm  [PDF]
Tara.Saikumar,R. Nirmala Devi,K. Kishna Rao
International Journal of Ad Hoc, Sensor & Ubiquitous Computing , 2012,
Abstract: The adaptive algorithm has been widely used in the digital signal processing like channel estimation, channel equalization, echo cancellation, and so on. One of the most important adaptive algorithms is the LMS algorithm. We present in this paper an multiple objective optimization approach to fast blind channel equalization. By investigating first the performance (mean-square error) of the standard fractionally spaced CMA (constant modulus algorithm) equalizer in the presence of noise, we show that CMA local minima exist near the minimum mean-square error (MMSE) equalizers. Consequently, Fractional Spaced CMA may converge to a local minimum corresponding to a poorly designed MMSE receiver with considerable large mean-square error. The step size in the LMS algorithm decides both the convergence speed and the residual error level, the highest speed of convergence and residual error level.
Under What Condition Do We Get Improved Equalization Performance in the Residual ISI with Non-Biased Input Signals Compared with the Biased Version  [PDF]
Monika Pinchas
Journal of Signal and Information Processing (JSIP) , 2015, DOI: 10.4236/jsip.2015.62008
Abstract: Recently, closed-form approximated expressions were obtained for the residual Inter Symbol Interference (ISI) obtained by blind adaptive equalizers for the biased as well as for the non-biased input case in a noisy environment. But, up to now it is unclear under what condition improved equalization performance is obtained in the residual ISI point of view with the non-biased case compared with the biased version. In this paper, we present for the real and two independent quadrature carrier case a closed-form approximated expression for the difference in the residual ISI obtained by blind adaptive equalizers with biased input signals compared with the non-biased case. Based on this expression, we show under what condition improved equalization performance is obtained from the residual ISI point of view for the non-biased case compared with the biased version.
Blind Channel Equalization  [PDF]
Sanaz Moshirian,Soheil Ghadami,Mohammad Havaei
Mathematics , 2012,
Abstract: Future services demand high data rate and quality. Thus, it is necessary to define new and robust algorithms to equalize channels and reduce noise in communications. Nowadays, new equalization algorithms are being developed to optimize the channel bandwidth and reduce noise, namely, Blind Channel Equalization. Conventional equalizations minimizing mean-square error generally require a training sequence accompanying the data sequence. In this study, the result of Least Mean Square (LMS) algorithm applied on two given communication channels is analyzed. Considering the fact that blind equalizers do not require pilot signals to recover the transmitted data, implementation of four types of Constant Modulus Algorithm (CMA) for blind equalization of the channels are shown. Finally, a comparison of the simulation results of LMS and CMA for the test channels is provided.
Adaptive blind equalization for ultra wideband system
一种基于自适应算法的超宽带系统盲均衡技术

SHI Xiao-lin,
师小琳

计算机应用 , 2009,
Abstract: A new adaptive blind equalization technology was proposed for Direct Sequence-Ultra WideBand (DS-UWB) and Time-Hopping-Ultra WideBand (TH-UWB) wireless communication systems. This method can effectively track the variation of Ultra WideBand (UWB) channels by using the variable forgetting factor to the adaptive algorithm and thus can compensate the interference due to the properties of channels. When receiving the signals, it can adjust the coefficients of equalizers without using the training sequence and then obtain the estimation of the sent signals. Furthermore, this method has relatively rapid convergence rate and good stability. Simulation results show that the proposed method has better performance in tracking UWB fading channels and it also help obtain lower Bit Error Rate (BER).
Performance Analysis of Adaptive Blind Equalizers Algorithms
Charu Sharma,Kapil Gupta
International Journal of Electronics Communication and Computer Technology , 2012,
Abstract: In this paper, we discuss the performance of Blind Equalization algorithms, which can deal with the cases that the input signals are correlated and decrease the filtering error. We describe the algorithm process and analysis the error performance and computational complexity and an example of adaptive blind equalization is given to verify these algorithms. Results and conclusions are made which may be benefit to the researchers and engineers in the adaptive filtering field.
A New Step Size Control Technique for Blind and Non-Blind Equalization Algorithms
E. Tu?cu,F. ?ak?r,A. Ozen
Radioengineering , 2013,
Abstract: A new variable step size (VSS) control technique employing cross correlation between channel output and error signal has been proposed as a solution to the problem of slow convergence of blind and non-blind equalization algorithms. The new method resolves the conflict between the convergence rate and low steady state error of the fixed step-size conventional blind and non-blind equalization algorithms, such as Constant Modulus Algorithm (CMA) and Least Mean Squares (LMS) algorithm. Computer simulations have been performed to verify the performance of the proposed method in frequency selective Rayleigh fading channels. The proposed technique has been compared with the popular non-blind equalizers, LMS and Recursive Least Squares (RLS) algorithms, and blind equalizers, the conventional CMA, Zhao’s VSS-CMA and Demir’s VSS-CMA as benchmarks. The obtained simulation results have demonstrated that the proposed VSS-CMA and VSS-LMS algorithms have considerably better performance than the conventional CMA, Zhao’s VSS-CMA and Demir’s VSS-CMA blind equalization algorithms, and the conventional LMS non-blind equalization algorithm.
Decision Feedback Blind Equalizer with Tap-Leaky Whitening for Stable Structure-Criterion Switching  [PDF]
Vladimir R. Krsti?,Miroslav L. Duki?
International Journal of Digital Multimedia Broadcasting , 2014, DOI: 10.1155/2014/987039
Abstract: The research presented in this paper improves the structure-criterion switching performance of the blind decision feedback equalizer (DFE) which eliminates error propagation effects by optimizing both the structure and the cost criterion. To conquer the complexity of the 64-QAM (quadrature amplitude modulated) signal constellation, the stochastic entropy-gradient algorithm is additionally regularized by the coefficient leaky term to avoid a coefficients norm overgrowth of the received signal whitener. Effectively, the leak of coefficients is employed to ensure a stable structure-criterion switching of DFE between blind and decision-directed operation modes. The optimization of the resulting whitening algorithm is achieved by means of two free, leaky and entropic, parameters which act in opposition to each other. Both, the influence of the 64-QAM signal on the feedback filter behavior and the parametric optimization of the whitening algorithm are analyzed through simulations. 1. Introduction Blind equalization methods are introduced as an alternative approach to the data communication concept employing a specially designed training sequence (pilot) to direct the train of receiver adaptive parameters [1, 2]. By using blind adaptive equalizers, which work without the assistance of a pilot, it is possible to increase effective system data rates and, also, to realize system applications where the train with a pilot is not possible [3, 4]. Unlike a linear equalizer which strives to complete an inverse channel response by a finite impulse response filter, a decision feedback equalizer (DFE) divides equalization task between linear feedforward and nonlinear feedback filters (equalizers). In such a manner, according to the hypothesis of correctly detected symbols, DFE exploits a nonlinear discrete nature of transmitted symbols to eliminate postcursor intersymbol interference (ISI) without a noise enhancement [5] using a relatively small number of coefficients [6]. This property of DFE is particularly important in systems characterized by deep spectral nulls channels. On the other hand, the main drawback of a DFE is error propagation phenomena which generally degrades its performance and can lead to an equalization failure depending on the length of error packets. For a blind DFE, the error propagation becomes a particularly critical issue because it appears inherently at the starting phase of equalization. Therefore, blind DFEs appeal for more efficient algorithms and signal processing techniques than their nonblind counterparts [7–13]. Motivated by the works of
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