Keywords

Uncertainty function, thermodynamic efficiency, information theory, statistical mechanics, capacity, phase space, laws of motion, encoding, momentum, sampling theory

Abstract

This work provides a fundamental view of the mechanisms which affect the power efficiency of communications processes along with a method for efficiency enhancement. Shannon's work is the definitive source for analyzing information capacity of a communications system but his formulation does not predict an efficiency relationship suitable for calculating the power consumption of a system, particularly for practical signals which may only approach the capacity limit. This work leverages Shannon's while providing additional insight through physical models which enable the calculation and improvement of efficiency for the encoding of signals. The proliferation of Mobile Communications platforms is challenging capacity of networks largely because of the ever increasing data rate at each node. This places significant power management demands on personal computing devices as well as cellular and WLAN terminals. The increased data throughput translates to shorter meantime between battery charging cycles and increased thermal footprint. Solutions are developed herein to counter this trend. Hardware was constructed to measure the efficiency of a prototypical Gaussian signal prior to efficiency enhancement. After an optimization was performed, the efficiency of the encoding apparatus increased from 3.125% to greater than 86% for a manageable investment of resources. Likewise several telecommunications standards based waveforms were also tested on the same hardware. The results reveal that the developed physical theories extrapolate in a very accurate manner to an electronics application, predicting the efficiency of single ended and differential encoding circuits before and after optimization.

Notes

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Graduation Date

2015

Semester

Spring

Advisor

Wocjan, Pawel

Degree

Doctor of Philosophy (Ph.D.)

College

College of Engineering and Computer Science

Department

Electrical Engineering and Computer Engineering

Degree Program

Electrical Engineering

Format

application/pdf

Identifier

CFE0006051

URL

http://purl.fcla.edu/fcla/etd/CFE0006051

Language

English

Release Date

November 2016

Length of Campus-only Access

1 year

Access Status

Doctoral Dissertation (Open Access)

Subjects

Dissertations, Academic -- Engineering and Computer Science; Engineering and Computer Science -- Dissertations, Academic

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