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 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.

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.

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.

Two Blind Adaptive Equalizers Connected in Series for Equalization Performance Improvement

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).

Convergence Curve for Non-Blind Adaptive Equalizers

In this paper a closed-form approximated expression is proposed for the Intersymbol Interference (ISI) as a function of time valid during the entire stages of the non-blind adaptive deconvolution process and is suitable for the noisy, real and two independent quadrature carrier input case. The obtained expression is applicable for type of channels where the resulting ISI as a function of time can be described with an exponential model having a single time constant. Based on this new expression for the ISI as a function of time, the convergence time (or number of iteration number required for convergence) of the non-blind adaptive equalizer can be calculated. Up to now, the equalizer’s performance (convergence time and ISI as a function of time) could be obtained only via simulation when the channel coefficients were known. The new proposed expression for the ISI as a function of time is based on the knowledge of the initial ISI and channel power (which is measurable) and eliminates the need to carry out any more the above mentioned simulation. Simulation results indicate a high correlation between the simulated and calculated ISI (based on our proposed expression for the ISI as a function of time) during the whole deconvolution process for the high as well as for the low signal to noise ratio (SNR) condition.

Design of a 6.25 Gbps backplane SerDes with adaptive decision feedback equalization

A 6.25 Gbps SerDes core used in the high signed based on the OIF-CEI-02.0 standard. To speed backplane communication receiver has been decounteract the serious Inter-Syrmbol-Interference （ISI）, the core employed a half-rate four-tap decision feedback equalizer （DFE）. The equalizer used the Signsign least mean-squared （SS-LMS） algorithm to realize the coefficient adaptation. An automatic gain control （AGC） amplifier with the sign least mean-squared （S-LMS） algorithm has been used to compensate the transmission media loss. To recover the clock signal from the input data serial and provide for the DFE and AGC, a bang-bang clock recovery （BB-CR） is adopted. A third order phase loop loek （PLL） model was proposed to predict characteristics of the BB-CR. The core has been verified by behavioral modeling in MATLAB. The results indicate that the core can meet the specifications of the backplane receiver. The DFE recovered data over a 34＂ FR-4 backplane has a peak-to-peak jitter of 17 ps, a horizontal eye opening of 0.87 UI, and a vertical eye opening of 500 mVpp.

A New Equalization Method for Lithium-Ion Battery Packs Based on CUK

Aiming at the traditional CUK equalizer can only perform energy equalization between adjacent batteries,if the two single batteries that need to be equalized are far away from each other,there will be the problem of longer energy transmission path and lower equalization efficiency,this paper optimizes the CUK equalizer and optimizes its peripheral selection circuit,which can support the equalization of single batteries at any two positions.The control strategy adopts the open-circuit voltage(OVC)of the battery and the state of charge(SOC)of the battery as the equalization variables,and selects the corresponding equalization variables according to the energy conditions of the two batteries that need to be equalized,and generates the adaptive equalization current with an adaptive PID controller in order to improve the equalization efficiency.Simulation modeling is performed in Matlab/Simulink 2021b,and the experimental results show that the optimized CUK equalizer in this paper improves the equalization time by 25.58%compared with the traditional CUK equalizer.In addition,compared with the mean value difference(MVD)method,the adaptive PID method reduces the equalization time by about 30%in the static and charging and discharging experimental environments,which verifies the superiority of this equalization scheme.

Design of Time-Domain Equalizer in Elastic Wave Earth Channel

In low-frequency elastic wave through-the-earth communication system,because of multipath transmission caused by characteristics of the layered earth,the time domain equalizer is different from other wireless communication systems.A modified LMS algorithm of variable step size is proposed based on improvement of traditional LMS.On the base of principle and simulation analysis,the improved Least Mean Square(LMS)algorithm is analyzed and the performances are compared between the improved LMS algorithm and traditional LMS algorithm.In the improved algorithm,the contradiction between convergence speed and the steady-state error is considered at the same time.Therefore,the improved algorithm has good convergence properties and channel-tracking performance.

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 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 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.

TRANSFORM DOMAIN CONJUGATE GRADIENT ALGORITHM FOR ADAPTIVE FILTERING

This paper proposed a new normalized transform domain conjugate gradient algorithm (NT-CGA), which applies the data independent normalized orthogonal transform technique to approximately whiten the input signal and utilises the modified conjugate gradient method to perform sample-by-sample updating of the filter weights more efficiently. Simulation results illustrated that the proposed algorithm has the ability to provide a fast convergence speed and lower steady-error compared to that of traditional least mean square algorithm (LMSA), normalized transform domain least mean square algorithm (NT- LMSA), Quasi-Newton least mean square algorithm (Q-LMSA) and time domain conjugate gradient algorithm (TD-CGA) when the input signal is heavily coloured.

Time-domain clustered transmit power adaptation for OFDM system in fading channels

This paper proposes a time-domain clustered transmitter power adaptation scheme for orthogonal frequency division multiplexing (OFDM) system, which can significantly reduce the feedback amount during power adaptation comparison with conventional frequency-domain adaptation schemes. It was found that the cluster size plays an important role on the adaptation performance, especially for the vehicular environment. Simulation results showed that using Lagrange interpolation to obtain an explicit curve of Doppler frequency vs cluster size yields good trade-off between the resulted bit error rate (BER) and the amount of feedback.

基于CLAHE-PCA的矿井低照度图像增强研究

地下矿山巷道环境往往面临光线不足,难以通过获取其暗通道图像判断岩体剥落等异常情况。针对矿井巷道暗通道图像对比度低的问题,提出了一种基于CLAHE-PCA的图像增强算法。首先使用CLAHE算法将获取的矿井巷道原始暗通道图像做对比度增强处理,然后使用自适应Gamma算法对亮度低的图像予以增加对比度矫正;将矫正后获得的灰度图转为RGB图像,通过PCA对其进行平滑处理,以便更多地还原暗通道图像的细节。以峰值信噪比、结构相似性、平均梯度和信息熵等作为评价指标,对试验结果进行验证。结果表明:该方法能够有效处理低对比度的矿井巷道图像,处理后的图像结构相似性达到93%,鲁棒性强,同时能够更多地还原图像的细节。

一种宽带非线性信道校正方法

针对高速数传解调器接收宽带高阶调制信号时因信道非线性导致的性能恶化问题,提出一种基于两层自适应均衡网络的非线性信道校正方法。该方法先利用递归最小二乘法获得Volterra非线性前置校正系数,再利用自适应基带均衡器消除信道的剩余影响,以提升解调器的捕获跟踪能力,并在高速数传解调器工程应用中实现2.4 Gb/s 16QAM信号的稳定接收。

在线燃烧离子色谱仪的高精度测温电路设计

在线燃烧离子色谱仪将样品前处理和检测过程相结合,极大提高了检测效率。而燃烧温度过高会降低燃烧管的使用寿命,燃烧温度过低会使样品裂解不充分,所以设计高精度测温电路来测量燃烧温度很有必要。首先设计了RFI滤波电路,抑制高频噪声对热电偶输出热电势的影响;其次设计了双ADC自适应采集电路,实现档位的快速切换;最后设计了Pt1000测温电路来测量冷端温度,使冷端补偿误差小于0.052℃;提出了等精度最小二乘法拟合校正算法,根据测温精度在测温范围内自动划分等精度区间,提高了测温精度且降低了MCU的工作量。实验结果表明:在0~1200℃范围内,测温精度可达0.6℃。