Performance of Wavelet-Transform-Domain Adaptive Equalizers

In this paper performances of wavelet transform domain (WTD) adaptive equalizers based on the least mean￣square (LMS) algorithm are analyzed. The optimum Wiener solution, the condition of convergence, the minimum mean square error (MSE) and the steady state excess MSE of the WTD adaptive equalizer are obtained. Constant and time varying convergence factor adaptive algorithms are studied respectively. Computational complexities of WTD LMS equalizers are given. The equalizer in WTD shows much better convergence performance than that of the conventional in time domain.

Wavelet Network Based MQAM Digital Communication Adaptive Equalizers

A novel wavelet network based adaptive equalizer (WNBAE) is presented and the structure and stochastic gradient learning algorithm is given. The proposed WNBAE has better performance than that of the conventional linear transversal equalizer based on the LMS and the RLS algorithms, as well as that of the decision feedback equalizer based on the RLS algorithm, especially for MQAM digital communication reception systems over the nonlinear channels. In addition, it outperforms the BP neural network based adaptive equalizer slightly. However, it has a slow convergence rate and a high computational complexity. Several simulations are performed to evaluate the behavior of the WNBAE.

An Analog Equalizer and Baseline-Wander Cancelle rfor 100/1000Base-TX Transceiver

A frequency-domain equalizer with a mixed-signal adaptive control loop and a novel baseline wander （BLW） canceller are proposed. The equalizer is independent of channel-modeling accuracy,and its control loop is intrinsically stable. An AGC function is incorporated into the equalizer without an extra AGC circuit. The proposed BLW canceller uses a peak detector to monitor the BLW and full feedback method to accomplish BLW canceling. High canceling accuracy and robust performance are achieved. The circuits are tested in 0.25μm CMOS technology. Better performance and smaller silicon area are achieved compared with results in the literature.

A Novel TDD Multicarrier System Using Pre-Equalizer in Downlink

In this paper, a time division duplex (TDD) multicarrier system based on Nyquist filter bank is proposed for wireless broadband communications. In this system a novel two tap pre equalizer is adopted to effectively suppress the inter symbol interference (ISI). Studies show that the system has almost the same frequency spectrum efficiency as the orthogonal frequency division multiplexing (OFDM) system. Simulation results show that the proposed system outperforms the conventional OFDM system with one tap ...

Self-adjusting decision feedback equalizer for variational underwater acoustic channel environments

Aimed at the abominable influences to blind equaliza-tion algorithms caused by complex time-space variability existing in underwater acoustic channels, a new self-adjusting decision feedback equalization （DFE） algorithm adapting to different under-water acoustic channel environments is proposed by changing its central tap position. Besides, this new algorithm behaves faster convergence speed based on the analysis of equalizers’ working rules, which is more suitable to implement communications in dif-ferent unknown channels. Corresponding results and conclusions are validated by simulations and spot experiments.

A DECISION FEEDBACK EQUALIZER FOR NON-LINEAR CHANNELS

A Simple and useful decision feedback equalizer used for non-linear channels with severe linear distortion and mild non-linear distortion is proposed. It is a combination of a nonlinear channel equalizer based on connectionist model and a common decision feedback equalizer for linear channels. For a typical non-linear channel model it is shown that the equalization performances of the proposed equalizer are improved significantly.

A New Equalization Performance Analyzing Method for Blind Adaptive Equalizers Inspired by Maximum Time Interval Error

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.

Separate Least Mean Square Based Equalizer with Joint Optimization for Multi-CAP Visible Light Communication

Visible light communication(VLC) is expected to be a potential candidate of the key technologies in the sixth generation(6G) wireless communication system to support Internet of Things(IoT) applications. In this work, a separate least mean square(S-LMS) equalizer is proposed to compensate lowpass frequency response in VLC system. Joint optimization is employed to realize the proposed S-LMS equalizer with pre-part and post-part by introducing Lagrangian. For verification, the performance of VLC system based on multi-band carrier-less amplitude and phase(m-CAP) modulation with S-LMS equalizer is investigated and compared with that without equalizer,with LMS equalizer and with recursive least squares(RLS)-Volterra equalizer. Results indicate the proposed equalizer shows significant improved bit error ratio(BER) performance under the same conditions. Compared to the RLS-Volterra equalizer, SLMS equalizer achieves better performance under low data rate or high signal noise ratio(SNR) conditions with obviously lower computational complexity.

An improved least mean square/fourth direct adaptive equalizer for under-water acoustic communications in the Arctic

An improved least mean square/fourth direct adaptive equalizer(LMS/F-DAE)is proposed in this paper for underwater acoustic communication in the Arctic.It is able to process complex-valued baseband signals and has better equalization performance than LMS.Considering the sparsity feature of equalizer tap coefficients,an adaptive norm(AN)is incorporated into the cost function which is utilized as a sparse regularization.The norm constraint changes adaptively according to the amplitude of each coefficient.For small-scale coefficients,the sparse constraint exists to accelerate the convergence speed.For large-scale coefficients,it disappears to ensure smaller equalization error.The performance of the proposed AN-LMS/F-DAE is verified by the experimental data from the 9th Chinese National Arctic Research Expedition.The results show that compared with the standard LMS/F-DAE,AN-LMS/F-DAE can promote the sparse level of the equalizer and achieve better performance.

An Approximated Expression for the Residual ISI Obtained by Blind Adaptive Equalizer and Biased Input Signals

Recently, two expressions (for the noiseless and noisy case) were proposed for the residual inter-symbol interference (ISI) obtained by blind adaptive equalizers, where the error of the equalized output signal may be expressed as a polynomial function of order 3. However, those expressions are not applicable for biased input signals. In this paper, a closed-form approximated expression is proposed for the residual ISI applicable for the noisy and biased input case. This new proposed expression is valid for blind adaptive equalizers, where the error of the equalized output signal may be expressed as a polynomial function of order 3. The new proposed expression depends on the equalizer’s tap length, input signal statistics, channel power, SNR, step-size parameter and on the input signal’s bias. Simulation results indicate a high correlation between the simulated results and those obtained from our new proposed expression.

基于中间件Equalizer的并行渲染技术研究

随着三维图形技术和可视化技术的发展,数据处理的规模越来越大,并行绘制系统越来越重要。然而,目前大部分并行渲染解决方案只是针对特定的应用程序,但更重要的是如何开发一个通用的并行渲染框架,并且它能支持各类数据可视化应用的任务。为了更深入地研究并行绘制技术,研究并行绘制框架Equalizer的架构和优点,并用Equalizer实现Ply模型的并行绘制。

A NEW ADAPTIVE EQUALIZER STRUCTURE FOR NONLINEAR CHANNELS

Based on the analysis of nonlinear channel models,a new connectionist model ofadaptive equalizer is constructed.Comparing with the connectionist model using the Volterraseries to extend the input vector space,the number of weights with the new structure is reducedsignificantly.It is shown by simulations that the weight values of the new scheme converge to theoptimal values closely for non-minimum phase channels as well minimum phase channels,if thechannel noise is small enough.Testing results of the BER(Bit Error Rate)tell us that the newadaptive equalizer for nonlinear channels is superior to the conventional linear equalizers in theequalization performances.

A NEW KIND OF EQUALIZER BASED ON ORTHONORMAL WAVELETS

An orthonomal wavelets based equalizer (OWBE) is presented. The equalizer is represented by a set of orthonomal wavelets and the corresponding coefficients. The paper gives the structure and also the adaption algorithm of the OWBE. Theoretical analysis shows that the OWBE convergences faster than the conventional LMS based linear equalizer(LE), while the increase in the computational complexity is very slow. Several simulations are performed to evaluate the behavior of the OWBE.

Constant modulus semi-blind space-time equalizer based on structure risk minimum criterion

A new adaptive filtering principle based on capability control and semi-blind method is presented. A new semi-blind space-time equalizer based on constant modulus characteristic and structure risk minimum （SRM） criterion is also proposed. The equalizer sufficiently exploits the learning information of communication signals by using the structure information of filter itself through capability control technique. Namely, it maximizes the amount of learning information to im- prove filter tracking performance. Simulations are carried out and the result is compared with that of typical recursive least squares space-time equalizer （RLS-STE） and constant modulus semi-blind space-time equalizer （ CM-SB-STE ）. The results show that, even if with insufficient training data, the SRM constant modulus semi-blind space-time equalizer （SCM-SB-STE） keeps good tracking per- formance, showing promises in mobile wireless communications.

Design and realization of digital audio equalizer based on MCU and FPAA

In analog audio equalizer, the filters are constructed by op-amplifiers and discrete components. Being influenced by its discrete capabilities, audio equalizer has many disadvantages. Meanwhile, pure digital audio equalizer has got better performance and stability, but its cost and price are too high. So digital audio equalizer only has its application in upscale domain. A new design method for audio equalizer is proposed, which attempts to design and realize a high precision and high SNR (signal noise ratio) digital audio equalizer system based on field programmable analog array (FPAA) and micro-controller unit. This design confirms that design speed and performance will be greatly enhanced when FPAA technology is applied to analog design domain.

Decision feedback equalizer based on non-singleton fuzzy regular neural networks

A new equalization method is proposed in this paper for severely nonlinear distorted channels. The structure of decision feedback is adopted for the non-singleton fuzzy regular neural network that is trained by gradient-descent algorithm. The model shows a much better performance on anti-jamming and nonlinear classification, and simulation is carried out to compare this method with other nonlinear channel equalization methods. The results show the method has the least bit error rate （BER）.

10Gb/s transmit equalizer using duobinary signaling over FR4 backplane

A 10Gb/s 6-tap transmit equalizer based on partial response signaling for high speed backplane transmission is presented. By combining features of equalizer and frequency-dependent channel,duobinary signaling can be generated at the output of FR4 backplane,aiming at increasing data rate while reducing design complexity. Based on 0.18μm CMOS technology,this equalizer has been designed and fabricated,in which both variable capacitor and load resistor calibration techniques are explored to eliminate the effect of process variations. The chip occupies 0.68×0.8mm^2 including I/O pads and consumes a power of 194 mW with 1.8V power supply. Measurement results show that a typical 3-level eye diagram can be obtained at the receiver and the equalizer can work properly at the data rate of 10Gb/s.

Adaptive support vector machine decision feedback equalizer

An adaptive support vector machine decision feedback equalizer（ASVM-DFE） based on the least square support vector machine（LS-SVM） is proposed,it solves linear system iteratively with less computational intensity.An adaptive non-singleton fuzzy support vector machine decision feedback equalizer（ANSFSVMDFE） is also presented,it adopts the non-singleton fuzzy Gaussian kernel function with similar characteristic of pre-filter and is modified with a space transformation based approach.Simulations under nonlinear time variant channels show that ASVM-DFE and ANSFSVM-DFE perform very well on nonlinear equalization and ANSFSVM-DFE acts especially well in resisting abrupt interference.

Adaptive blind equalizer based on least square support vector machine

An adaptive blind support vector machine equalizer（ABSVME） is presented in this paper.The method is based upon least square support vector machine（LSSVM）,and stems from signal feature reconstruction idea.By oversampling the output of a LSSVM equalizer and exploiting a reasonable decorrelation cost function design,the method achieves fine online channel tracing with Kumar express algorithm and static iterative learning algorithm incorporated.The method is verified through simulation and compared with other nonlinear equalizers.The results show that it provides excellent performance in nonlinear equalization and time-varying channel tracing.Although a constant module equalization algorithm requires that the signal has characteristic of constant module,this method has no such requirement.

Determining the Optimal Decision Delay Parameter for a Linear Equalizer

The achievable bit error rate of a linear equalizer is crucially determined by the choice of a decision delay parameter. This brief paper presents a simple method for the efficient determination of the optimal decision delay parameter that results in the best bit error rate performance for a linear equalizer. Keywords Linear equalizer - decision delay - bit error rate Eng Siong Chng received his university education at the University of Edinburgh, Edinburgh, Scotland (BEng 1991, PhD 1995). After his PhD, he spent 6 months in Japan, working as a researcher for Riken. After working in industry in Singapore for 7 years, he joined the School of Computer Engineering, Nanyang Technological University in 2003. His research interests are in digital signal processing for communication applications, speech and handwriting recognition and noise reduction.Sheng Chen obtained a BEng degree in control engineering from the East China Petroleum Institute, Dongying, China, in 1982, and a PhD degree in control engineering from the City University at London in 1986. He joined the School of Electronics and Computer Science at the University of Southampton in September 1999. He previously held research and academic appointments at the Universities of Sheffield, Edinburgh and Portsmouth. Dr Chen is a Senior Member of the IEEE in the USA. His recent research works include adaptive nonlinear signal processing, modeling and identification of nonlinear systems, neural networks and machine learning, finite-precision digital controller design, evolutionary computation methods and optimization. He has published over 200 research papers. In the database of the world’s most highly cited researchers in various disciplines, compiled by the Institute for Scientific Information (ISI) of the USA, Dr Chen is on the list of highly cited researchers in the category that covers all branches of engineering subject, see www.ISIHighlyCited.com.