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Two Blind Adaptive Equalizers Connected in Series for Equalization Performance Improvement  [PDF]
Monika Pinchas
Journal of Signal and Information Processing (JSIP) , 2013, DOI: 10.4236/jsip.2013.41008
Abstract:

A variable step-size parameter is usually used to accelerate the convergence speed of a blind adaptive equalizer with N1 + N2 -1 coefficients where N1 and N2 are odd values. In this paper we show that improved equalization performance is achieved when using two blind adaptive equalizers connected in series where the first and second blind adaptive equalizer have N1 and N2 coefficients respectively compared with the case where a single blind adaptive equalizer is applied with N1 + N2 -1 coefficients. It should be pointed out that the same algorithm (cost function) is used for updating the filter taps for the different equalizers and that a fixed step-size parameter is used. Simulation results show that for the low signal to noise ratio (SNR) environment and for the case where the convergence speed is slow due to the channel characteristics, the new method has a faster convergence speed with a factor of approximately two while leaving the system with approximately the same or lower residual intersymbol interference (ISI).

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.
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.
A Dynamic Tap Allocation for Concurrent CMA-DD Equalizers  [cached]
Trindade DiegovonBM,Halmenschlager Vitor,Ortolan Leonardo,De Castro MariaCF
EURASIP Journal on Advances in Signal Processing , 2010,
Abstract: This paper proposes a dynamic tap allocation for the concurrent CMA-DD equalizer as a low complexity solution for the blind channel deconvolution problem. The number of taps is a crucial factor which affects the performance and the complexity of most adaptive equalizers. Generally an equalizer requires a large number of taps in order to cope with long delays in the channel multipath profile. Simulations show that the proposed new blind equalizer is able to solve the blind channel deconvolution problem with a specified and reduced number of active taps. As a result, it minimizes the output excess mean square error due to inactive taps during and after the equalizer convergence and the hardware complexity as well.
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.
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).
Nonlinear Blind Equalizers: NCMA and NMCMA  [PDF]
Donglin Wang, Sandeep Chandana
Int'l J. of Communications, Network and System Sciences (IJCNS) , 2010, DOI: 10.4236/ijcns.2010.36070
Abstract: This paper proposes two nonlinear blind equalizers: the nonlinear constant modulus algorithm (NCMA) and the nonlinear modified constant modulus algorithm (NCMA) by applying a nonlinear transfer function (NTF) into constant modulus algorithm (CMA) and modified constant modulus algorithm (MCMA), respectively. The effect of the NTF on CMA and MCMA is theoretically analyzed, which implies that the NTF can make their decision regions much sharper so that the proposed two nonlinear blind equalizers are more robust against the convergency error compared to their linear counterparts. The embedded single layer in NCMA and NMCMA simultaneously guarantees a comparably speedy convergency. On 16-quadrature amplitude modulation (QAM) symbols, computer simulations show that NCMA achieves an 8dB lower convergency mean square error (MSE) than CMA, and NMCMA achieves a 15dB lower convergency MSE than MCMA.
Learning Rate Updating Methods Applied to Adaptive Fuzzy Equalizers for Broadband Power Line Communications  [cached]
Moisés V. Ribeiro
EURASIP Journal on Advances in Signal Processing , 2004, DOI: 10.1155/s1687617204407021
Abstract: This paper introduces adaptive fuzzy equalizers with variable step size for broadband power line (PL) communications. Based on delta-bar-delta and local Lipschitz estimation updating rules, feedforward, and decision feedback approaches, we propose singleton and nonsingleton fuzzy equalizers with variable step size to cope with the intersymbol interference (ISI) effects of PL channels and the hardness of the impulse noises generated by appliances and nonlinear loads connected to low-voltage power grids. The computed results show that the convergence rates of the proposed equalizers are higher than the ones attained by the traditional adaptive fuzzy equalizers introduced by J. M. Mendel and his students. Additionally, some interesting BER curves reveal that the proposed techniques are efficient for mitigating the above-mentioned impairments.
NLMS Algorithm with Orthogonal Correction Factors using Adaptive Gain for Adaptive Transversal Equalizers
L.I. Huxiong
Research Journal of Applied Sciences, Engineering and Technology , 2011,
Abstract: A normalized least mean square with orthogonal correction factors using adaptive gain (NLMSOCF- AG) algorithm is proposed in order to improve the convergence rate and steady-state performance for adaptive transversal equalizers. The particular values of the step-size parameter are obtained that minimize the ensemble-average cost function by analyzing the estimated output-error. The experimental results show that the proposed algorithm has fast convergence rate and small steady-state error compared with the conventional NLMS-OCF algorithm.
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