MIMO decision feedback equalization from an H/sup /spl infin// perspective

We approach the multiple input multiple output (MIMO) decision feedback equalization (DFE) problem in digital communications from an H/sup /spl infin// estimation point of view. Using the standard (and simplifying) assumption that all previous decisions are correct, we obtain an explicit parameterization of all H/sup /spl infin// optimal DFEs. In particular, we show that, under the above assumption, minimum mean square error (MMSE) DFEs are H/sup /spl infin// optimal. The H/sup /spl infin// approach also suggests a method for dealing with errors in previous decisions.     

Optimum open eye equalizer design for nonminimum phase channels

This paper contains results on the design of optimum equalizers to eliminate intersymbol interference (ISI) in linear nonminimum phase channels conveying binary signals. The optimization is with respect to an open eye condition with a delay d. For causal stable channels with n _c nonminimum phase zeros, we argue that this problem requires only the consideration of the n_c-tap FIR modified channel that has all the n_c nonminimum phase zeros of the original channel. We show that if this modified channel can be equalized to yield an equalized system that is open eye with delay d, then the optimizing equalizer is, in fact, (d-n_c)-tap FIR with all zeros outside the unit circle. We also give a simple necessary and sufficient condition to determine if for a particular d, a given channel can be equalized to achieve an equalized response that is open eye with delay d     

On linear H∞ equalization of communicationchannels

As an alternative to existing techniques and algorithms, we investigate the merit of the H^∞ approach to the linear equalization of communication channels. We first give the formulation of all causal H^∞ equalizers using the results of and then look at the finite delay ease. We compare the risk-sensitive H^∞ equalizer with the MMSE equalizer with respect to both the average and the worst-case BER performances and illustrate the improvement due to the use of the H^∞ equalizer     

Equalization and semi-blind channel estimation for space-time block coded signals over a frequency-selective fading channel

In this paper, we investigate the equalization and channel identification for space-time block coded signals over a frequency-selective multiple-input multiple-output (MIMO) channel. The equalization has been considered by taking into account the cyclostationarity of space-time block coded signals. The minimum mean square error (MMSE) solutions have been derived for the linear and decision feedback (DF) equalizers. The channel estimation is required for the equalization. With known symbols (as pilot symbols), MIMO channels can be estimated. In addition, due to the redundancy induced by space-time block code, it is possible to identify MIMO channels blindly using the subspace method. We consider both blind and semi-blind channel estimation for MIMO channels. It is shown that the semi-blind channel estimate has fewer estimation errors, and it results in less (bit error rate) performance degradation of the MMSE linear and DF equalizers.     

Asymptotic properties on codeword lengths of an optimal FV code for general sources

This correspondence is concerned with asymptotic properties on the codeword length of a fixed-to-variable length code (FV code) for a general source {X/sup n/}/sub n=1//sup /spl infin// with a finite or countably infinite alphabet. Suppose that for each n /spl ges/ 1 X/sup n/ is encoded to a binary codeword /spl phi//sub n/(X/sup n/) of length l(/spl phi//sub n/(X/sup n/)). Letting /spl epsiv//sub n/ denote the decoding error probability, we consider the following two criteria on FV codes: i) /spl epsiv//sub n/ = 0 for all n /spl ges/ 1 and ii) lim sup/sub n/spl rarr//spl infin///spl epsiv//sub n/ /spl les/ /spl epsiv/ for an arbitrarily given /spl epsiv/ /spl isin/ [0,1). Under criterion i), we show that, if X/sup n/ is encoded by an arbitrary prefix-free FV code asymptotically achieving the entropy, 1/nl(/spl phi//sub n/(X/sup n/)) - 1/nlog/sub 2/ 1/PX/sup n/(X/sup n/) /spl rarr/ 0 in probability as n /spl rarr/ /spl infin/ under a certain condition, where P/sub X//sup n/ denotes the probability distribution of X/sup n/. Under criterion ii), we first determine the minimum rate achieved by FV codes. Next, we show that 1/nl(/spl phi//sub n/(X/sup n/)) of an arbitrary FV code achieving the minimum rate in a certain sense has a property similar to the lossless case.     

Integrated transversal equalizers in high-speed fiber-optic systems

Intersymbol interference (ISI) caused by intermodal dispersion in multimode fibers is the major limiting factor in the achievable data rate or transmission distance in high-speed multimode fiber-optic links for local area networks applications. Compared with optical-domain and other electrical-domain dispersion compensation methods, equalization with transversal filters based on distributed circuit techniques presents a cost-effective and low-power solution. The design of integrated distributed transversal equalizers is described in detail with focus on delay lines and gain stages. This seven-tap distributed transversal equalizer prototype has been implemented in a commercial 0.18-/spl mu/m SiGe BiCMOS process for 10-Gb/s multimode fiber-optic links. A seven-tap distributed transversal equalizer reduces the ISI of a 10-Gb/s signal after 800 m of 50-/spl mu/m multimode fiber from 5 to 1.38 dB, and improves the bit-error rate from about 10/sup -5/ to less than 10/sup -12/.     

Space–Time Turbo Equalization With Successive Interference Cancellation for Frequency-Selective MIMO Channels

This paper addresses the issue of iterative space–time equalization for multiple-input–multiple-output (MIMO) frequency-selective fading channels. A new soft equalization concept based on successive interference cancellation (SIC) is introduced for a space–time bit-interleaved coded modulation (STBICM) transmission. The proposed equalizer allows us to separate intersymbol interference (ISI) and multiantenna interference (MAI) functions. Soft ISI is successively suppressed using a low-complexity suboptimum minimum mean square error (MMSE) criterion. The decoupling of ISI and MAI offers more flexibility in the design of the whole space–time equalizer. Different multiantenna detection criteria can be considered, ranging from simple detectors to the optimal maximum a posteriori (MAP) criterion. In particular, we introduce two soft equalizers, which are called SIC/SIC and SIC/MAP, and we show that they can provide a good performance-to-complexity tradeoff for many system configurations, as compared with other turbo equalization schemes. This paper also introduces an MMSE-based iterative channel state information (CSI) estimation algorithm and shows that attractive performance can be achieved when the proposed soft SIC space–time equalizer iterates with the MMSE-based CSI estimator.      

Fast and low complexity blind equalization via subgradient projections

We propose a novel blind equalization method based on subgradient search over a convex cost surface. This is an alternative to the existing iterative blind equalization approaches such as the Constant Modulus Algorithm (CMA), which often suffer from the convergence problems caused by their nonconvex cost functions. The proposed method is an iterative algorithm called SubGradient based Blind Algorithm (SGBA) for both real and complex constellations, with a very simple update rule. It is based on the minimization of the l/sub /spl infin// norm of the equalizer output under a linear constraint on the equalizer coefficients using subgradient iterations. The algorithm has a nice convergence behavior attributed to the convex l/sub /spl infin// cost surface as well as the step size selection rules associated with the subgradient search. We illustrate the performance of the algorithm using examples with both complex and real constellations, where we show that the proposed algorithm's convergence is less sensitive to initial point selection, and a fast convergence behavior can be achieved with a judicious selection of step sizes. Furthermore, the amount of data required for the training of the equalizer is significantly lower than most of the existing schemes.     

MMSE analysis of certain large isometric random precoded systems

Linear precoding consists in multiplying by an N/spl times/K matrix a K-dimensional vector obtained by serial-to-parallel conversion of a symbol sequence to be transmitted. In this paper, new tools, borrowed from the so-called free probability theory, are introduced for the purpose of analyzing the performance of minimum mean-square error (MMSE) receivers for certain large random isometric precoded systems on fading channels. The isometric condition represents the case of precoding matrices with orthonormal columns. It is shown in this contribution that the signal-to-interference-plus-noise ratio (SINR) at the equalizer output converges almost surely to a deterministic value depending on the probability distribution of the channel coefficients when N/spl rarr/+/spl infin/ and K/N/spl rarr//spl alpha//spl les/1. These asymptotic results are used to analyze the impact of orthogonal spreading as well as to optimally balance the redundancy introduced between linear precoding versus classical convolutional coding, while preserving a simple MMSE equalization scheme at the receiver.     

A CMOS 0.25-/spl mu/m continuous-time FIR filter with 125 ps per tap delay as a fractionally spaced receiver equalizer for 1-gb/s data transmission

This paper presents a CMOS 0.25-/spl mu/m continuous-time 6-tap FIR filter that is used as a fractionally spaced receiver equalizer for 1-Gb/s data transmission. Each tap of the FIR filter delay line is realized with a second-order low-pass filter. Simulations show that the tap delay can be tuned from 100 ps to 300 ps while keeping a constant group delay within the bandwidth of 2.1 GHz and 800 MHz correspondingly. Experimental results show that the FIR filter can successfully recover a 1-Gb/s differential digital signal that has been transmitted over a 220-inch PCB trace which causes -31.48-dB attenuation at the symbol rate frequency of 1 GHz. The measured bit error rate after equalization is less than 10/sup -12/ over a 750-ps sampling range, compared to a 10/sup -2/ bit-error rate before equalization. Also presented are the measurement results comparing the horizontal and the vertical openings of the signals before and after equalization for PCB traces with different length. The chip dissipates 45 mW from a 2.5-V supply and occupies 0.33/spl times/0.27 mm/sup 2/ in a 0.25-/spl mu/m CMOS process.     

Wide-band impedance matching: H/sup /spl infin// performance bounds

This paper presents the first implementation of Helton's H/sup /spl infin// approach to wide-band impedance matching. The prototypical problem is to maximize the transducer power gain uniformly over an operating band for a load connected to a generator by a lossless two-port. The H/sup /spl infin// approach computes the maximum transducer power gain attainable by any lossless two-port uniformly over the operating band. This maximum gain is computed for Fano's classic RLC circuit and an high-frequency antenna represented by measured reflectance data.     

Parameter estimation and equalization techniques for communication channels with multipath and multiple frequency offsets

We consider estimation of frequency offset (FO) and equalization of a wireless communication channel, within a general framework which allows for different frequency offsets for various multipaths. Such a scenario may arise due to different Doppler shifts associated with various multipaths, or in situations where multiple basestations are used to transmit identical information. For this general framework, we propose an approximative maximum-likelihood estimator exploiting the correlation property of the transmitted pilot signal. We further show that the conventional minimum mean-square error equalizer is computationally cumbersome, as the effective channel-convolution matrix changes deterministically between symbols, due to the multiple FOs. Exploiting the structural property of these variations, we propose a computationally efficient recursive algorithm for the equalizer design. Simulation results show that the proposed estimator is statistically efficient, as the mean-square estimation error attains the Crame/spl acute/r-Rao lower bound. Further, we show via extensive simulations that our proposed scheme significantly outperforms equalizers not employing FO estimation.     

非线性信道自适应均衡的一种方法

本文通过对非线性信道模型的分析,构造了一种新的、关联模型的自适应均衡器。分析表明,与一般的基于Volterra级数的非线性扩展关联模型相比,新结构的权数大为减少。模拟实验证实,当信道噪声较小时,新结构以较高的精度收敛于最佳解。而且无论对最小相位或非最小相位信道,该均衡器均表现出良好的收敛特性和误码性能。     

Nonlinear equalization of multipath fading channels withnoncoherent demodulation

A nonlinear decision-based adaptive equalizer compatible with differentially coherent phase shift keying (PSK) is proposed for frequency-selective fading channels. This equalization scheme is appropriate whenever conventional equalizers are not capable of tracking phase variations in selective fading channels. The received signal is first converted to a baseband signal and then sent through a differential detector. A nonlinear processor before the equalizer generates the needed nonlinear terms that are weighted and summed in the equalizer. Nonlinear intersymbol interference at the output of the differential detector is dealt with by minimizing an error signal between the output of the equalizer and the detected data. The adaptation algorithm can be any algorithm currently used for conventional equalizers. Our simulation results confirm that for channels with spectral nulls, equalization is achieved successfully with the proposed scheme, whereas, linear equalizers, either with coherent or noncoherent detection, fail     

An H/sub /spl infin// optimization and its fast algorithm for time-variant system identification

In some estimation or identification techniques, a forgetting factor /spl rho/ has been used to improve the tracking performance for time-varying systems. However, the value of /spl rho/ has been typically determined empirically, without any evidence of optimality. In our previous work, this open problem is solved using the framework of H/sub /spl infin// optimization. The resultant H/sub /spl infin// filter enables the forgetting factor /spl rho/ to be optimized through a process noise that is determined by the filter Riccati equation. This paper seeks to further explain the previously derived H/sub /spl infin// filter, giving an H/sub /spl infin// interpretation of its tracking capability. Additionally, a fast algorithm of the H/sub /spl infin// filter, called the fast H/sub /spl infin// filter, is presented when the observation matrix has a shifting property. Finally, the effectiveness of the derived fast algorithm is illustrated for time-variant system identification using several computer simulations. Here, the fast H/sub /spl infin// filter is shown to outperform the well known least-mean-square algorithm and the fast Kalman filter in convergence rate.     

Low-Complexity Block Turbo Equalization for OFDM Systems in Time-Varying Channels

We propose low-complexity block turbo equalizers for orthogonal frequency-division multiplexing (OFDM) systems in time-varying channels. The presented work is based on a soft minimum mean-squared error (MMSE) block linear equalizer (BLE) that exploits the banded structure of the frequency-domain channel matrix, as well as a receiver window that enforces this banded structure. This equalization approach allows us to implement the proposed designs with a complexity that is only linear in the number of subcarriers. Three block turbo equalizers are discussed: two are based on a biased MMSE criterion, while the third is based on the unbiased MMSE criterion. Simulation results show that the proposed iterative MMSE BLE achieves a better bit error rate (BER) performance than a previously proposed iterative MMSE serial linear equalizer (SLE). The proposed equalization algorithms are also tested in the presence of channel estimation errors.      

Robust H/sub /spl infin// controller design with recurrent neural network for linear synchronous motor drive

In this paper, a robust controller design with H/sub /spl infin// performance using a recurrent neural network (RNN) is proposed for the position tracking control of a permanent-magnet linear synchronous motor. The proposed robust H/sub /spl infin// controller, which comprises a RNN and a compensating control, is developed to reduce the influence of parameter variations and external disturbance on system performance. The RNN is adopted to estimate the dynamics of the lumped plant uncertainty, and the compensating controller is used to eliminate the effect of the higher order terms in Taylor series expansion of the minimum approximation error. The tracking performance is ensured in face of parameter variations, external disturbance and RNN estimation error once a prespecified H/sub /spl infin// performance requirement is achieved. The synthesis of the RNN training rules and compensating control are based on the solution of a nonlinear H/sub /spl infin// control problem corresponding to the desired H/sub /spl infin// performance requirement, which is solved via a choice of quadratic storage function. The proposed control method is able to track both the periodic step and sinusoidal commands with improved performance in face of large parameter perturbations and external disturbance.     

复值的MBER非线性均衡器用于QAM信号

本文提出一种复值的最低误码率非线性滤波器用于非线性信道中QAM信号的均衡.推导了针对QAM信号的最低误码率准则训练算法的目标函数,并用Voherra序列来实现复值的非线性均衡器.为使非线性均衡器能在线自适应训练并增加训练算法的数值稳定性,提出～种滑窗随机梯度算法.大量仿真表明,对于非线性信道中QAM信号的均衡,最低误码率非线性均衡器的性能优于最小均方误差准则.     

Efficient reinitialization of the prewhitened constant modulusalgorithm

We present a reinitialization scheme for blind equalizers adapted via the constant modulus algorithm (CMA) when an all-pole prefilter is included to whiten the received signal. The mechanism exploits the special structure of the minimum mean squared error (MMSE) equalizers and their relation with CMA equalizers. A heuristic rule for blind determination of the best equalization delay is also provided. Using these guidelines, the equalizer is capable of finding the optimal setting in an online and computationally efficient fashion. In particular, estimation and inversion of the channel output autocorrelation matrix is not needed, in contrast with previous approaches