Blind feedforward cyclostationarity-based timing estimation for linear modulations

By exploiting a general cyclostationary (CS) statistics-based framework, this letter develops a rigorous and unified asymptotic (large sample) performance analysis setup for a class of blind feedforward timing epoch estimators for linear modulations transmitted through time nonselective flat-fading channels. Within the proposed CS framework, it is shown that several estimators proposed in the literature can be asymptotically interpreted as maximum likelihood (ML) estimators applied on a (sub)set of the second- (and/or higher) order statistics of the received signal. The asymptotic variance of these ML estimators is established in closed-form expression and compared with the modified Crame/spl acute/r-Rao bound. It is shown that the timing estimator proposed by Oerder and Meyr achieves asymptotically the best performance in the class of estimators which exploit all the second-order statistics of the received signal, and its performance is insensitive to oversampling rates P as long as P/spl ges/3. Further, an asymptotically best consistent estimator, which achieves the lowest asymptotic variance among all the possible estimators that can be derived by exploiting jointly the second- and fourth-order statistics of the received signal, is also proposed.     

X-ray or UV adjustment of MOS threshold voltage: Analytical and numerical modeling

A model is formulated that describes how radiation-induced charge accumulates in the gate oxide of a MOS structure and how it decays through tunneling and thermal emission. The model is used in a numerical analysis of the x-ray or UV adjustment of threshold voltage in MOS-circuit manufacture. The limits of this process technique are evaluated.     

A VQ-based blind image restoration algorithm

Learning-based algorithms for image restoration and blind image restoration are proposed. Such algorithms deviate from the traditional approaches in this area, by utilizing priors that are learned from similar images. Original images and their degraded versions by the known degradation operator (restoration problem) are utilized for designing the VQ codebooks. The codevectors are designed using the blurred images. For each such vector, the high frequency information obtained from the original images is also available. During restoration, the high frequency information of a given degraded image is estimated from its low frequency information based on the codebooks. For the blind restoration problem, a number of codebooks are designed corresponding to various versions of the blurring function. Given a noisy and blurred image, one of the codebooks is chosen based on a similarity measure, therefore providing the identification of the blur. To make the restoration process computationally efficient, the principal component analysis (PCA) and VQ-nearest neighbor approaches are utilized. Simulation results are presented to demonstrate the effectiveness of the proposed algorithms.     

An improved statistical analysis of the least mean fourth (LMF) adaptive algorithm

The paper presents an improved statistical analysis of the least mean fourth (LMF) adaptive algorithm behavior for a stationary Gaussian input. The analysis improves previous results in that higher order moments of the weight error vector are not neglected and that it is not restricted to a specific noise distribution. The analysis is based on the independence theory and assumes reasonably slow learning and a large number of adaptive filter coefficients. A new analytical model is derived, which is able to predict the algorithm behavior accurately, both during transient and in steady-state, for small step sizes and long impulse responses. The new model is valid for any zero-mean symmetric noise density function and for any signal-to-noise ratio (SNR). Computer simulations illustrate the accuracy of the new model in predicting the algorithm behavior in several different situations.     

The effects of nonlocal impact ionization on the speed of avalanche photodiodes

The nonlocal enhancement in the velocities of charge carriers to ionization is shown to outweigh the opposing effects of dead space, increasing the avalanche speed of short avalanche photodiodes (APDs) over the predictions of a conventional local model which ignores both of these effects. The trends in the measured gain-bandwidth product of two short InAlAs APDs reported in the literature support this result. Relatively large speed benefits are predicted to result from further small reductions in the lengths of short multiplication regions.     

Analysis of feedback for higher order polarization-mode dispersion mitigation of NRZ 40-Gb/s optical transmission

First-order polarization-mode dispersion (PMD) compensation by means of a polarization controller and a differential delay line is not sufficient to guarantee error-free transmission for 40-Gb/s channels when higher order effects severely increase signal distortion. Higher order mitigation is possible by cascading more than one first-order block. However, only two-stage or three-stage devices remain simple enough to be actually controlled. The performance of such higher order PMD compensators is evaluated by means of numerical simulations. Two different feedback signals have been used, demonstrating that first-order and higher order PMD distortion of nonreturn-to-zero (NRZ) pulses at 40 Gb/s can be strongly mitigated for instantaneous values of the differential group delay (DGD) up to the bit slot, when the compensator is properly controlled.     

End-to-end congestion control schemes: utility functions, random losses and ECN marks

We present a framework for designing end-to-end congestion control schemes in a network where each user may have a different utility function and may experience noncongestion-related losses. We first show that there exists an additive-increase-multiplicative-decrease scheme using only end-to-end measurable losses such that a socially optimal solution can be reached. We incorporate round-trip delay in this model, and show that one can generalize observations regarding TCP-type congestion avoidance to more general window flow control schemes. We then consider explicit congestion notification (ECN) as an alternate mechanism (instead of losses) for signaling congestion and show that ECN marking levels can be designed to nearly eliminate losses in the network by choosing the marking level independently for each node in the network. While the ECN marking level at each node may depend on the number of flows through the node, the appropriate marking level can be estimated using only aggregate flow measurements, i.e., per-flow measurements are not required.     

Some Insights into MIMO Mutual Information: The High SNR Case

We consider mutual information of multiple-input multiple-output (MIMO) wireless channels with complex isotropic Gaussian input in the case where the receiver has perfect channel, knowledge. For arbitrary fading statistics, a mutual information lower bound is decomposed in a sum of three terms involving: a) average SNR; b) channel fading; and c) a term characterizing the "effective rank", or eigenvalue dispersion, of the channel matrix. The decomposition suggests that spatial multiplexing efficiency of a MIMO channel can be characterized by the so-called ellipticity statistic. Distribution functions, means and variances of the random terms in the decomposition for the case of Rayleigh fading are also derived     

High-resolution photonics-based interference suppression filter with wide passband

A new topology for a photonic signal processor, which overcomes the basic recursive frequency response problem that limits the passband range, is presented. The structure is based on a new multiple-wavelength offset-cavity structure that is cascaded with a series of unbalanced delay line structures. This not only can synthesize a very narrow notch response with good shape factor but also permits a multifold extension of the free spectral range (FSR) and passband width. Results on the interference mitigation filter demonstrate a stopband of 1% of center frequency and a fourfold increase in the FSR and passband width, while also having a very small shape factor, in excellent agreement with predictions.     

NEXUS — Resilient Intelligent Middleware

Service-oriented computing is the latest software paradigm brought about by the computing revolution. The different viewpoint and granularity of software components used in technologies based on the service-oriented architecture paradigm, compared to traditional object-oriented methodologies makes them better suited to many of the efforts that are being made in the pervasive and ubiquitous computing world. In the NEXUS project we are seeking ways of fusing the SOA and pervasive computing paradigms in order to build intelligent, robust and resilient networks connecting dynamic islands of service resources.