J. Treichler

Bio: J. Treichler is an academic researcher from Argos. The author has contributed to research in topics: Adaptive filter & White noise. The author has an hindex of 3, co-authored 3 publications receiving 1567 citations.

A new approach to multipath correction of constant modulus signals

Abstract: An adaptive digital filtering algorithm that can compensate for both frequency-selective multipath and interference on constant envelope modulated signals is presented. The method exploits the fact that multipath reception and various interference sources generate incidental amplitude modulation on the received signal. A class of so-called constant modulus performance functions is developed which sense this AM term but are insensitive to the angle modulation. Simple adaptive algorithms for finite-impulse-response (FIR) digital filters are developed which employ a gradient search of the performance function. One of the resulting algorithms is simulated for the example of an FM signal degraded by specular multipath propagation. Substantial improvements in noise power ratio (NPR) are observed (e.g., 25 dB) with moderately rapid convergence time. These results are then extended to include tonal interference on a FM signal and intersymbol interference on a QPSK data signal.

Transient and convergent behavior of the adaptive line enhancer

Abstract: The adaptive line enhancer (ALE) was first described as a practical technique for separating the periodic from the broad-band components of an input signal and for detecting the presence of a sinusoid in white noise. Subsequent work has shown that this adaptive filtering structure is applicable to spectral estimation, predictive deconvolution, speech processing, interference rejection, and other applications which have historically used matrix inversion or Levinson's algorithm techniques. This paper uses an eigenvalue-eigenvector analysis of the expected ALE impulse response vector to demonstrate properties of the convergent filter and to quantify the convergence time and characteristics of the ALE. In particular the ALE's response to a sinusoid plus white noise input is derived and compared to a computer simulation of the ALE with such an input. The eigenvalue-eigenvector technique is then used to evaluate the ALE's performance as an adaptive prewhitener for autoregressive (AR) models with white observation noise. A method is demonstrated which prevents the problem of spectral estimation bias which usually accrues from the observation noise.

Response of the adaptive line enhancer to chirped and doppler-shifted sinusoids

Abstract: The adaptive line enhancer (ALE) was first described by Widrow et al. as a practical on-line technique for separating the coherent components from the incoherent components of an input signal. Subsequent work has shown this same adaptive filtering structure to be applicable to maximum entropy spectral estimation, predictive deconvolution, and narrow-band interference rejection. While an often cited advantage of adaptive filtering is its tolerance of slowly time-varying input statistics, the existing analyses of the ALE have concentrated on the stationary case. This correspondence extends these results, applying the theory to the case of inputs containing sinuosids whose frequencies slowly vary in time. This is approached by developing a time-varying eigenvalue-eigenvector description of the expected filter impulse response vector. These results are then used to predict the expected impulse response vector for the ALE input of stationary white noise plus a sinusoid with linearly swept frequency. The response of the ALE for this particular input signal provides useful benchmarks for dealing with more complex forms of frequency modulation. The utility of the theoretical results is demonstrated by considering the ALE's response to an input of practical interest to the sonar community, a sinusoid whose apparent frequency is shifted by Doppler effects.

Spectrum estimation and harmonic analysis

Abstract: In the choice of an estimator for the spectrum of a stationary time series from a finite sample of the process, the problems of bias control and consistency, or "smoothing," are dominant. In this paper we present a new method based on a "local" eigenexpansion to estimate the spectrum in terms of the solution of an integral equation. Computationally this method is equivalent to using the weishted average of a series of direct-spectrum estimates based on orthogonal data windows (discrete prolate spheroidal sequences) to treat both the bias and smoothing problems. Some of the attractive features of this estimate are: there are no arbitrary windows; it is a small sample theory; it is consistent; it provides an analysis-of-variance test for line components; and it has high resolution. We also show relations of this estimate to maximum-likelihood estimates, show that the estimation capacity of the estimate is high, and show applications to coherence and polyspectrum estimates.

Application of antenna arrays to mobile communications. II. Beam-forming and direction-of-arrival considerations

Abstract: Array processing involves manipulation of signals induced on various antenna elements. Its capabilities of steering nulls to reduce cochannel interferences and pointing independent beams toward various mobiles, as well as its ability to provide estimates of directions of radiating sources, make it attractive to a mobile communications system designer. Array processing is expected to play an important role in fulfilling the increased demands of various mobile communications services. Part I of this paper showed how an array could be utilized in different configurations to improve the performance of mobile communications systems, with references to various studies where feasibility of apt array system for mobile communications is considered. This paper provides a comprehensive and detailed treatment of different beam-forming schemes, adaptive algorithms to adjust the required weighting on antennas, direction-of-arrival estimation methods-including their performance comparison-and effects of errors on the performance of an array system, as well as schemes to alleviate them. This paper brings together almost all aspects of array signal processing.

Blind identification and equalization based on second-order statistics: a time domain approach

Abstract: A new blind channel identification and equalization method is proposed that exploits the cyclostationarity of oversampled communication signals to achieve identification and equalization of possibly nonminimum phase (multipath) channels without using training signals. Unlike most adaptive blind equalization methods for which the convergence properties are often problematic, the channel estimation algorithm proposed here is asymptotically ex-set. Moreover, since it is based on second-order statistics, the new approach may achieve equalization with fewer symbols than most techniques based only on higher-order statistics. Simulations have demonstrated promising performance of the proposed algorithm for the blind equalization of a three-ray multipath channel. >

Space-time processing for wireless communications

Abstract: Space-time processing can improve network capacity, coverage, and quality by reducing co-channel interference (CCI) while enhancing diversity and array gain. This article focuses largely on the receive (mobile-to-base station) time-division multiple access (TDMA) (nonspread modulation) application for high-mobility networks. We describe a large (macro) cell propagation channel and discuss different physical effects such as path loss, fading delay spread, angle spread, and Doppler spread. We also develop a signal model incorporating channel effects. Both forward-link (transmit) and reverse-link (receive) channels are considered and the relationship between the two is discussed. Single- and multiuser models are treated for four important space-time processing problems, and the underlying spatial and temporal structure are discussed as are different algorithmic approaches to reverse link space-time professing with blind and nonblind methods for single- and multiple-user cases. We cover forward-link space-time algorithms and we outline methods for estimation of multipath parameters. We also discuss applications of space-time processing to CDMA, applications of space-time techniques to current cellular systems, and industry trends.