Adaptive Bayesian decision feedback equalizer for dispersive mobile radio channels

The paper investigates adaptive equalization of time dispersive mobile ratio fading channels and develops a robust high performance Bayesian decision feedback equalizer (DFE). The characteristics and implementation aspects of this Bayesian DFE are analyzed, and its performance is compared with those of the conventional symbol or fractional spaced DFE and the maximum likelihood sequence estimator (MLSE). In terms of computational complexity, the adaptive Bayesian DFE is slightly more complex than the conventional DFE but is much simpler than the adaptive MLSE. In terms of error rate in symbol detection, the adaptive Bayesian DFE outperforms the conventional DFE dramatically. Moreover, for severely fading multipath channels, the adaptive MLSE exhibits significant degradation from the theoretical optimal performance and becomes inferior to the adaptive Bayesian DFE

Estimation-based synthesis of H_∞-optimal adaptive equalizers over wireless channels

This paper presents a systematic synthesis procedure for H_∞-optimal adaptive FIR equalizers over a time-varying wireless channel. The channel is assumed to be frequency selective with Rayleigh fading. The proposed equalizer structure consists of the series connection of an adaptive FIR filter and a fixed equalizer (designed for the nominal channel). Adaptation of the weight vector of the adaptive FIR filter is achieved using the H_∞-optimal solution of an estimation-based interpretation of the channel equalization problem. Due to its H_∞-optimality, the proposed solution is robust to exogenous disturbances, and enables fast adaptation (i.e., a short training period) without compromising the steady-state performance of the equalization. Preliminary simulation are presented to support the above claims

Robust equalization of multichannel acoustic systems

In most real-world acoustical scenarios, speech signals captured by distant microphones from a source are reverberated due to multipath propagation, and the reverberation may impair speech intelligibility. Speech dereverberation can be achieved by equalizing the channels from the source to microphones. Equalization systems can be computed using estimates of multichannel acoustic impulse responses. However, the estimates obtained from system identification always include errors; the fact that an equalization system is able to equalize the estimated multichannel acoustic system does not mean that it is able to equalize the true system. The objective of this thesis is to propose and investigate robust equalization methods for multichannel acoustic systems in the presence of system identification errors. Equalization systems can be computed using the multiple-input/output inverse theorem or multichannel least-squares method. However, equalization systems obtained from these methods are very sensitive to system identification errors. A study of the multichannel least-squares method with respect to two classes of characteristic channel zeros is conducted. Accordingly, a relaxed multichannel least- squares method is proposed. Channel shortening in connection with the multiple- input/output inverse theorem and the relaxed multichannel least-squares method is discussed. Two algorithms taking into account the system identification errors are developed. Firstly, an optimally-stopped weighted conjugate gradient algorithm is proposed. A conjugate gradient iterative method is employed to compute the equalization system. The iteration process is stopped optimally with respect to system identification errors. Secondly, a system-identification-error-robust equalization method exploring the use of error models is presented, which incorporates system identification error models in the weighted multichannel least-squares formulation

A 3 Gb/s optical detector in standard CMOS for 850 nm optical communication

This paper presents a monolithic optical detector, consisting of an integrated photodiode and a preamplifier in a standard 0.18-/spl mu/m CMOS technology. A data rate of 3 Gb/s at BER <10/sup -11/ was achieved for /spl lambda/=850 nm with 25-/spl mu/W peak-peak optical power. This data rate is more than four times than that of current state-of-the-art optical detectors in standard CMOS reported so far. High-speed operation is achieved without reducing circuit responsivity by using an inherently robust analog equalizer that compensates (in gain and phase) for the photodiode roll-off over more than three decades. The presented solution is applicable to various photodiode structures, wavelengths, and CMOS generations

Video enhancement using adaptive spatio-temporal connective filter and piecewise mapping

This paper presents a novel video enhancement system based on an adaptive spatio-temporal connective (ASTC) noise filter and an adaptive piecewise mapping function (APMF). For ill-exposed videos or those with much noise, we first introduce a novel local image statistic to identify impulse noise pixels, and then incorporate it into the classical bilateral filter to form ASTC, aiming to reduce the mixture of the most two common types of noises - Gaussian and impulse noises in spatial and temporal directions. After noise removal, we enhance the video contrast with APMF based on the statistical information of frame segmentation results. The experiment results demonstrate that, for diverse low-quality videos corrupted by mixed noise, underexposure, overexposure, or any mixture of the above, the proposed system can automatically produce satisfactory results