Title page for ETD etd-5941513972900

Type of Document Dissertation
Author Laster, Jeffery D.
URN etd-5941513972900
Title Robust GMSK Demodulation Using Demodulator Diversity and BER Estimation
Degree PhD
Department Electrical and Computer Engineering
Advisory Committee
Advisor Name Title
Beex, A. A. Louis
Rappaport, Theodore S.
Stutzman, Warren L.
Ye, Keying
Reed, Jeffrey Hugh Committee Chair
  • GMSK
  • interference rejection
  • BER estimation
  • demodulator diversity
  • adaptive signal processing
Date of Defense 1997-01-28
Availability unrestricted

This research investigates robust demodulation

of Gaussian Minimum Shift Keying (GMSK)

signals, using demodulator diversity and

real-time bit-error-rate (BER) estimation.

GMSK is particularly important because of its

use in prominent wireless standards around the

world (GSM, DECT, CDPD, DCS1800, and

PCS1900). The dissertation begins with a

literature review of GMSK demodulation

techniques (coherent and noncoherent) and

includes an overview of single-channel

interference rejection techniques in digital

wireless communications. Various forms of

GMSK demodulation are simulated, including

the limiter discriminator and differential

demodulator (i.e., twenty-five variations in all).

Ten represent new structures and variations.

The demodulator performances are evaluated

in realistic wireless environments, such as

additive white Gaussian noise, co-channel

interference, and multipath environments

modeled by COST207 and SMRCIM.

Certain demodulators are superior to others

for particular channel impairments, so that no

demodulator is necessarily the best in every

channel impairment. This research formally

introduces the concept of demodulator

diversity, a new idea which consists of a bank

of demodulators which simultaneously

demodulate the same signal and take

advantage of the redundancy in the similar

signals. The dissertation also proposes

practical real-time BER estimation techniques

which have tremendous ramifications for

communications. Using Parzen's estimator for

probability density functions (pdfs) and

Gram-Charlier series approximation for pdfs,

BER can be estimated using short observation

intervals (10 to 500 training symbols) and, in

some cases, without any training sequence.

We also introduce new variations of

Gram-Charlier estimation using robust

estimators. BER (in place of MSE) can now

drive adaptive signal processing. Using a cost

function and gradient for Parzen's estimator

(derived in this paper), BER estimation is

applied to demodulator diversity with

substantial gains of 1-10 dB in

carrier-to-interference ratio over individual

receivers in realistic channels (with adaptive

selection and weighting). With such gains, a

BER-based demodulator diversity scheme can

allow the employment of a frequency reuse

factor of N=4, instead of N=7, with no

degradation in performance. A lower reuse

factor means more channels are available in a

cell, thus increasing overall capacity. The

resulting techniques are simple and easily

implemented at the mobile. BER estimation

techniques can also be used in BER-based

equalization and dynamic allocation of


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