Decision feedback equalization (DFE) is a sampled-data technique used for data recovery in digital communications channels. Multi-level decision feedback equalization (MDFE) has been developed for channels using the 2/3(1,7) RLL code.
The optimum detector for a digital communication channel affected by ISI and noise consists of a matched filter, followed by a symbol rate sampler and a maximum likelihood sequence estimator. The optimal detector is unrealizable for saturation recording channels. A compromise structure uses fixed filter types with adjustable parameters. The objective is to maximize the signal-to-noise ratio in order to minimize the error rate.
The read-channel waveform is corrupted at sampling instants by noise generated by various sources. We use a continuous-time low-pass filter cascaded with an all-pass filter at the receiver front-end. The low-pass filter band-limits high-frequency noise before sampling, and the all-pass filter equalizes the signal.
This thesis examines different structures of the receiver and their optimal parameter placing. A design methodology developed specifically for choosing the poles and zeros location of the linear front-end part of the receiver is presented. It
makes use of nonlinear optimization, and a software package written in MATLAB for equalizer computer aided design (CAD) is included in the appendix.
The optimization criterion usually mentioned in the literature for digital channel optimal design is the sum of the intersymbol interference and noise. A new objective function is proposed in the thesis, and the error rate probability is shown to decrease by 30%.
Issues pertaining to digital simulation of continuous-time systems are discussed. Design results are presented for different receiver structures, and bit error rate simulations are used for design validation. / Graduation date: 1997
Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/34239 |
Date | 07 March 1997 |
Creators | Onu, Dan |
Contributors | Kenney, John G. |
Source Sets | Oregon State University |
Language | en_US |
Detected Language | English |
Type | Thesis/Dissertation |
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