A noble blind equalization algorithm (BEA) using a single/multilevel modulus is proposed. According to the residual intersymbol interference (ISI) level of the equalizer output, the new algorithm adopts relevantly a single modulus or a multilevel modulus to form its cost function. Moreover, since the proposed approach separates complex two-dimensional signal into in-phase and quadrature components, and forms the error signals for each component, it has inherently the capability of phase recovery. Hence, it improves the performances of steady-state and recovers the phase rotation without any degradation of transient property. Simulation results confirm the effectiveness of the new approach.

We propose an improved orthogonal frequency division multiplexing (OFDM) signal detector which uses the minimum mean-square error (MMSE) noise feedback equalization (NFE). The input bit stream is trellis-coded to form OFDM signal blocks and the maximal ratio combining (MRC) is adopted at the receiver in order to improve the performance of the detector. As a result, we obtain significantly improved detection performance compared with the conventional OFDM receivers as follows. Using the proposed MMSE-NFE in the receiver, we can obtain the performance gain of about 1.5 dB to 2 dB in symbol energy to noise power spectral density (Es/No) for Doppler frequencies of fd=20 and 100 Hz, respectively, over the receiver with the MMSE linear equalization (LE) alone at symbol error rate (SER) of about 10-3. With MRC and trellis coding, the performance gain of about 11 dB in Es/No for fd=20 and 100 Hz at SER of about 10-3 is obtained.

In this letter, we propose a blind adaptation method for the decision feedback equalizer (DFE). In the proposed scheme, a DFE is divided into two parts: a front-end linear equalizer (LE), and a prediction error filter (PEF) followed by a feedback part. The coefficients of the filters in each part are updated using constant modulus algorithm and decision feedback prediction algorithm, respectively. The front-end LE removes intersymbol interference ISI, and the PEF with feedback part whitens the noise to reduce noise power enhanced by the LE. Pre-processing by the LE enables the DFE to equalize nonminimum phase channels. Simulation results show that the proposed scheme provides reliable convergence, and the resulting symbol error rate is much less than that of the conventional LE and very close to that of the DFE using a training sequence.

In high-speed digital land mobile radio communication, communication quality is degraded by frequency selective fading that has intersymbol interference. It causes increase of bit error rate (BER). To decrease BER in the channel, this paper proposes a system with combined multilevel coding and adaptive equalization using interleaving. By using interleaving, the proposed system obtains time diversity effect. Furthermore the system realizes a type of decision feedback adaptive equalizer where signal after multilevel decoder is fed back. These features of the system cause decrease of BER. The proposed system is compared with a similar system with a feedback signal before multilevel decoder. The average bit error rate of the proposed system is less than 1/100 with that of the compared system at average Eb/No = 22 [dB] in a case of fading channel with one intersymbol interference.

This paper presents a new blind identification method of nonminimum phase FIR systems and an adaptive blind equalization for PAM/QAM inputs without employing higher-order statistics. They are based on the observation that the absolute mean of a second-order white sequence can measure whether the sequence is higher-order white or not. The proposed methods are new alternatives to many higher-order statistics approaches. Some computer simulations show that the absolute mean is exactly estimated and the proposed methods can overcome the disadvantages of the higher-order statistics approaches.

A blind equalization algorithm which makes use of the Stop" region of the Stop-and-Go algorithm is proposed. By adaptively updating the tap weights at the Stop region as well, it is intended to improve the convergence property of the Stop-and-Go algorthm. The performance of the proposed algorithm is compared with the conventional Stop-and-Go algorithm using various communication channels. Simulation results indicate the improvement of the convergence speed while maintaining or possibly lowering the residual error.

This study is aimed to derive a new theoretical solution for blind equalizers. Undr the common assumptions for this framework, it is found that the condition for blind equalization is directly associated with an eigenproblem, i.e. the tap coefficients of the equalizer appear as an eigenvector of a higher order statistics matrix. Computer simulations show that very fast convergence can be achieved based on the approach.

This paper proposes and investigates a tap selectable Viterbi equalizer for mobile radio communications. When the multipath channel is modeled by a tapped delay line only, the taps which may seriously affect the data sequence estimation are selected and used to calculate the trellis metric in the Viterbi algorithm. The proposed equalization algorithm can reduce the number of path metric calculations and the number of path selections in the Viterbi algorithm. Moreover, we propose an extended equalizer which has antenna diversity. This equalizer calculates the path metric using the antenna outputs and results of channel estimators. Computer simulation is used to evaluate the BER performance of the proposed equalizer in a multipath radio channel.

The performance of decision-feedback equalization combined with maximum-likelihood detection (DFE/ML) using the fixed-delay-tree-search/decision feedback (FDTS/DF) algorithm was estimated analytically in terms of the length of the feedback-filter and the depth of the ML-detector. Performance degradation due to error propagation in the feedback-loop and in the ML-detector was taken into account by using a Markov process analysis. It was quantitatively shown that signal-to-noise-ratio (SNR) performance in high-density magnetic recording channels can be improved by combining an ML-detector with a feedback-filter and that the error propagation in the DFE channel can be reduced by using an ML-detector. Finally, it was found that near-optimum performance with regard to channel SNR and error propagation can be achieved, over the channel density range from 2 to 3, by increasing the sum of the feedback-filter length and the ML-detector depth to six bits.

An adaptive digital filter with adaptive sampling phase is proposed. The structure of the filter makes use of an adaptive delay device at the input of the filter. The algorithm is derived to determine the value of the delay and the filter coefficients by minimizing MSE (mean square error) between the desired signal and the filter output. The computer simulation of the convergence of the proposed adaptive filter with the input of sinusoidal wave and BPSK modulated wave are shown. According to the simulation, the MSE of the proposed adaptive delay algorithm is lower than that of the conventional LMS algorithm.

This paper describes a spatial and temporal multipath channel model which is useful in array antenna environments for mobile radio communications. From this model, a no distortion criterion, that is an extension of the Nyquist criterion, is derived for equalization in both spatial and temporal domains. An adaptive tapped-delay-line (TDL) array antenna is used as a tool for equalization in both spatial and temporal domains. Several criterion for such spatial and temporal equalization such as ZF (Zero Forcing) and MSE (Mean Square Error), are available to update the weights and tap coefficients. In this paper, we discuss the optimum weights based on the ZF criterion in both spatial and temporal domains. Since the ZF criterion satisfies the Nyquist criterion in case of noise free, this paper applies the ZF criterion for the spatial and temporal equalization as a simple case. The Z transform is applied to represent the spatial and temporal model of the multipath channel and to derive the optimal weights of the TDL array antenna. However, in some cases the optimal antenna weights cannot be decided uniquely. Therefore, the effect on the equalization errors due to a finite number of antenna elements and tap coefficients can be shown numerically by computer simulations.

Future digital land mobile communication, for a moving picture, requires more transmission speed and less bit error rate than the existing system does for speech. In the system, the intersymbol interference may not be ignored, because of higher transmission speed. An adaptive equalizer is necessary to cancel intersymbol interference. To achieve low bit error rate performance on the mobile radio channel, trellis-coded modulation with interleaving is necessary. This paper proposes an interleaved trellis-coded modulation scheme combined with a decision feedback type adaptive equalizer of high performance. The reliable symbol reconstructed in the trellis decoder is used as the feedback signal. To make equalizer be free from decoding delay, deinterleaving is effectively utilized. The branch metric, for trellis-coded modulation decoding, is calculated as terms of squared errors between a received signal and an expected signal by taking the reconstructed symbol and the impulse response estimated by the recursive least squares algorithm into account. The metric is constructed to have good discrimination performance to incorrect symbols even in non-minimum phase and to realize path diversity effect in a frequency selective fading channel. Computer simulation results are shown for several channel models. On a frequency selective fading channel, average bit error rate is less than 1/100 of that of the RLS-MLSE equalizer for fdTs=1/1000 at average Eb/N0 beyond 15dB. Performance degradation due to equalization error is less than 1.8dB. Performance is greatly improved by the effect of the reconstructed symbol feedback.

In this letter we propose an interpolation technique for low-quality fingerprint images for highly reliable feature extraction. To improve the feature extraction rate, we extract fingerprint features by referring to both the interpolated image obtained by using a directional Laplacian filter and the high-contrast image obtained by using histogram equalization. Experimental results show the applicability of our method.

This paper presents an adaptive MLSE (Maximum Likelihood Sequence Estimator) suitable for TDMA cellular systems. The proposed MLSE has two special features such as handling wide dynamic range signals without analogue gain controls and fast channel tracking capability. In order to handle wide dynamic range signals without conventional AGCs (Automatic Gain Controller), the proposed MLSE uses envelope components of received signals obtained from a non-linear log-amplifier module which has wide log-linear gain characteristics. By using digital signal processing technique, the log-converted envelope components are normalized and converted to linear values which conventional adaptive MLSEs can handle. As a channel tracking algorithm of the channel estimator, the proposed MLSE adopts a QT-LMS (Quick-Tracking Least Mean Square) algorithm, which is obtained by modifying LMS algorithm to enable a faster tracking capability. The algorithm has a fast tracking capability with low complexity and is suitable for implementation in a fixed-point digital signal processor. The performances of the MLSE have been evaluated through experiments in TDMA cellular environments with π/4-shifted QPSK, 24.3k symbol/sec. It is shown that, under conditions of 65dB amplitude variations and 80Hz Doppler frequency, the MLSE successfully achieves less than 3% B.E.R., which is required for digital cellular systems.

The joint estimation of two unknowns, i.e. system and input sequence, is overviewed in two methodologies of equalization and identification. Statistical approaches such as optimizing the ensamble average of the cost function at the equalizer output have been widely researched. One is based on the principle of distribution matching that total system must be transparent when the equalizer output has the same distribution as the transmitted sequence. Several generalizations for the cost function to measure mis-matching between distributions have been proposed. The other approach applies the higher order statistics like polyspectrum or cumulant, which possesses the entire information of the system. For example, the total response can be evaluated by the polyspectrum measured at equalizer output, and by zero-forcing both side of the response tail the time dependency in the equalizer output can be eliminated. This is based on the second principle that IID simultaneously at input and at output requires a tranparent system. The recent progress of digital mobile communication gives an incentive to a new approach in the Viterbi algorithm. The Viterbi algorithm coupled with the blind channel identification can be established under a finite alphabet of the transmitted symbols. In the blind algorithm, length of the candidate sequence, which decides the number of trellis states, should be defined as long enough to estimate the current channel response. The channel impairments in mobile communication, null spectrum and rapid time-variance, are solved by fast estimation techniques, for example by Kalman filters or by direct solving the short time least squared error equations. The question of what algorithm has the fastest tracking ability is discussed from algebraic view points.

The well known optimum approach to detect spread spectrum signals transmitted in bursts over frequency selective radio channels is matched filtering, which performs despreading, and subsequent Viterbi equalization (VE) to cope with intersymbol interference (ISI). With respect to complexity, VE is feasible only if data modulation schemes with a few symbol levels as e.g. 2PSK are used and if the delay spread of the channel is not too large. The paper gives a survey of suboptimum data detectors based on linear block estimation. Such data detectors are less expensive than VE especially in the case of multilevel data modulation schemes as 4PSK or 16QAM. Special emphasis is laid on data detectors based on Gauss-Markoff estimation because these detectors combine the advantages of unbiasedness and minimum variance of the estimate. In computer simulations, the Gauss-Markoff estimation algorithm is applied to spread spectrum burst transmission over radio channels specified by COST 207. It is shown that the SNR degradation which is a measure of the suboptimality of the detector does not exceed a few dB, and that even moderate spectrum spreading considerably reduces the detrimental effect of channel frequency selectivity.

The performance evaluation by analysis of systems employing Reduced State Viterbi decoding is addressed. This type of decoding is characterized by an inherent error propagation effect, which yields a difficulty in the error probability analysis, and has been usually neglected in the literature. By modifying the Full State trellis diagram, we derive for Reduced State schemes, new transfer function bounds with the effects of error propagation. Both the Chernoff and the tight upper bound are applied to the transfer function in order to obtain the bit error probability upper bound. Furthermore, and in order to get a tighter bound for Reduced State decoding schemes with parallel transitions, the pairwise probability of the two sequences involved in an error event is upper bounded, and then the branch metric of a sequence taken from that bound is associated with a truncated instead of complete Gaussian noise probability density function. To support the analysis, particular assessment is done for a Trellis Coded Modulation scheme.

A Decision Feedback Equalizer (DFE) structure with a varying number of tap lengths was used with a recursive least squares (RLS) algorithm to determine tradeoffs between equalizer size and performance in mobile and portable digital radio systems. A mobile channel simulator, SMRCIM, was used to demonstrate how much an equalizer can improve the BER in real world urban channels. The results show that at 850MHz, the DFE is unable to improve the BER when the mobile terminal exceeds speeds of 115km/h for U.S. Digital Cellular systems. The performance of adaptive equalization for indoor high data rate systems was evaluated using the indoor channel simulator SIRCIM, and we found that DFEs have excellent performance for indoor radio channels. For simple structures, the BER is less than 10-3 at 15dB Eb/NO using coherent QPSK modulation. Finally, an equalizer structure for non-coherent π/4 DQPSK modulation was developed and simulation results are presented.