Masters Theses

Keywords and Phrases

Detection and cancellation; Sinusoidal variation; Wireless communication

Abstract

"Fading channel estimation in wireless communication systems depends on an expected model for fading and any assumptions made about the channel itself. The bit error rate (BER) performance of the communication system is affected by how closely these assumptions made in designing the estimation technique match the deployment environment. Any unforeseen disturbances or hindrances in the environment deteriorate the BER performance of the system when the estimation system is not designed to combat such disturbances. To deal with such unforeseen obstacles, additional mathematical models can be proposed to model such disturbances and then the estimation techniques can either be reinforced with modular systems which work with the proposed models, or be redesigned as a whole with the help of actual observed data of the disturbances. The current thesis deals with such a scenario where sinusoidal variation is expected in the received power in addition to fading. A mathematical model of such power variation is assumed and a modular scheme is proposed to detect and combat the sinusoidal variation. The proposed scheme is tested by employing it in a simulated Multiple Input Multiple Output (MIMO) wireless communication system which adopts Space Time Block Coding (STBC) techniques"--Abstract, page iii.

Advisor(s)

Kosbar, Kurt Louis

Committee Member(s)

Grant, Steven L.
Moss, Randy Hays, 1953-

Department(s)

Electrical and Computer Engineering

Degree Name

M.S. in Electrical Engineering

Publisher

Missouri University of Science and Technology

Publication Date

Fall 2015

Pagination

ix, 67 pages

Note about bibliography

Includes bibliographical references (pages 64-66).

Rights

© 2015 Sushruth Sastry, All rights reserved.

Document Type

Thesis - Open Access

File Type

text

Language

English

Subject Headings

Wireless communication systems
Adaptive signal processing
MIMO systems
Space time codes

Thesis Number

T 10799

Electronic OCLC #

936209377

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