Adaptive methods for blind equalization and signal separation in MIMO systems

نویسنده

  • Mihai Enescu
چکیده

This thesis addresses the problems of blind source separation (BSS) and blind and semi-blind communications channel equalization. In blind source separation, signals from multiple sources arrive simultaneously at a sensor array, so that each sensor output contains a mixture of source signals. Sets of sensor outputs are processed to recover the source signals from the mixed observations. The term blind refers to the fact that specific source signal values and accurate parameter values of a mixing model are not known a priori. Application domains for the material in this thesis include communications, biomedical, and sensor array signal processing. The goal of this thesis is development of blind and semi-blind algorithms which require little or no prior information about source signal or mixing system parameter values in order to process the data. We start with the problem of extracting unknown input signals from measured outputs of instantaneous multiple-input multiple-output (I-MIMO) systems with constant parameter values. Suggested solutions are then extended to time-varying I-MIMO systems and also to constant finite impulse response multiple-input multiple-output (FIR-MIMO) systems. Another goal is to find a practical solution for the more challenging case of time-varying FIR-MIMO systems. The source separation techniques proposed in this thesis are based on state-space models and on recursive estimation. Blind separation algorithms based on Kalman filters are proposed. The source signals are treated using low-order autoregressive models. Projections along signal subspace eigenvectors are used to reduce the dimensionality of observations and also for spatial decorrelation of sources. Any changes that occur in the signal subspace can be tracked online. When considering slowly time-varying FIR-MIMO systems, fractional sampling can be used to derive a set of slowly time-varying I-MIMO systems. Thus, the proposed recursive BSS algorithms for I-MIMO systems can be used for blind equalization of slowly time-varying FIR communications channels. The problem of equalization of time-varying FIR MIMO systems is also addressed in this thesis. The proposed solutions involve semi-blind algorithms which work in two stages. First, a channel estimate is derived, and then the observation sequence is equalized. The algorithms estimate the otherwise-unknown noise statistics, and as a result achieve performance close to that of an optimal Kalman-based algorithm. A non-connected decision feedback equalization algorithm is derived for FIR-MIMO systems, using a minimum mean square error criterion. Simulation results show that the algorithm is able to track time and frequency selective channels and also to mitigate intersymbol and interuser interference.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Adaptive Blind Source Separation and Equalization for Multiple-Input/Multiple-Output Systems

In this paper, we investigate adaptive blind source separation and equalization for multiple-input/multiple-output (MIMO) systems. We first analyze the convergence of the constant modulus algorithm (CMA) used in MIMO systems (MIMOCMA). Our analysis reveals that the MIMO-CMA equalizer is able to recover one of the input signals, remove the intersymbol interference (ISI), and suppress the other i...

متن کامل

Adaptive Blind Multi - ChannelEqualization for Multiple

This paper investigates adaptive blind equalization for multiple-input and multiple-output (MIMO) channels and its application to blind separation of multiple signals received by antenna arrays in communication systems. The performance analysis is presented for the CMA equalizer used in MIMO channels. Our analysis results indicate that double innnite-length MIMO-CMA equalizer can recover one of...

متن کامل

On Blind Equalization of MIMO Channels - Communications, 1996. ICC '96, Conference Record, "Converging Technologies for Tomorrow's Applicat

This paper investigates adaptive blind equalization for multiple-input and multiple-output (MIMO) channels and its application to blind separation of multiple signals received by antenna arrays in communication systems. The performance analysis of the CMA equalizer used in MIMO channels is first presented. Our analysis results indicate that for the MIMO FIR channels satisfying certain condition...

متن کامل

Signal Processing Techniques in Mobile Communication Systems Signal Separation, Channel Estimation and Equalization

Over the last decade there has been an explosive growth in the use of wireless mobile communications. Second generations systems are mature technologies now and third generation systems and beyond are being implemented and researched. Future systems should support a substantially wider and enhanced range of services and thus would require even higher data rates compared to current system in ord...

متن کامل

In: Icassp97 Pp.1849-1852 Blind Equalization of Switching Channels by Ica and Learning of Learning Rate

In the literature of blind equalization, algorithms developed for equalizing an SISO or SIMO channel fail sometimes when the channel condition is poor. We derive blind equalization algorithms from blind separation algorithms to equalize the SISO channel with fractionally sampling. The approach is also applied to equalize SIMO or MIMO channels. For switching channels, we use an updating rule to ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2002