You are here

Statistical Modeling of Small-Scale Fading Channels

Title: Statistical Modeling of Small-Scale Fading Channels.
200 views
59 downloads
Name(s): Hekeno, Mahinga, author
Kwan, Bing W., professor directing thesis
Yu, Ming, committee member
Arora, Krishna, committee member
Department of Electrical and Computer Engineering, degree granting department
Florida State University, degree granting institution
Type of Resource: text
Genre: Text
Issuance: monographic
Date Issued: 2008
Publisher: Florida State University
Place of Publication: Tallahassee, Florida
Physical Form: computer
online resource
Extent: 1 online resource
Language(s): English
Abstract/Description: With the increase of wireless networks, consumers are increasingly aware of the importance and convenience of wireless technology. Wireless technologies such as WLANs, mobile phones, blue tooth or PCS rely on a range of mechanisms to provide for high Quality of Service (QoS), the core of which would be accurate modeling of the wireless channels. The radio channel emanates time-variant linear channel characteristics. In this research, the analysis of the statistics of the underlying channel behavior is investigated using a developed physics-based channel model that characterizes small-scale fading behavior the wireless channels. Specifically, we investigate Flat Slow Fading, Flat Fast Fading, Frequency-Selective Slow Fading and Frequency-Selective Fast Fading propagation channels. This thesis will provide for computer simulation of a physics-based channel model to define the essential channel parameters, and subsequently reproduce the characterized channel by appropriately utilizing the autoregressive process to remodel the attained channel data. The principal method for this study is the use of Levinson-Durbin recursion to build a signal model for channel analysis. The motivation for this research is, given a set of channel parameters obtained from the physics-based channel model, the proposed autoregressive signal model can reproduce the physical channel parameters and accurately predict the nature of small scale fading present in a channel whether it is Flat Slow Fading, Flat Fast Fading, Frequency-Selective Slow Fading or Frequency-Selective Fast Fading. Performance comparisons are then made from the generated physical properties of the channel with the simulation results of the constructed autoregressive model built by the use of statistical comparison analysis such as autocorrelation properties to demonstrate the merits of the approach. This manuscript is organized as follows; Chapter one provides an introduction and background information of communication systems. Chapter two describes random time-varying channels, different parameters affecting the propagation of signals in the communication channel; phenomena such as Doppler shift and multipath delay are discussed. The physics-based channel is developed in chapter two. Chapter three discusses different parameters that can be used to categorize wireless channels and types of multipath fading that can happen in a wireless channel. Autoregressive channel modeling using Levinson-Durbin recursion is discussed in chapter four. Simulation results of the developed model are provided and discussed in chapter five. Chapter six gives a conclusion and discusses areas where further studies need to be carried out.
Identifier: FSU_migr_etd-4134 (IID)
Submitted Note: A Thesis submitted to the Department of Electrical Engineering in partial fulfillment of the requirements for the degree of Master of Science.
Degree Awarded: Spring Semester, 2008.
Date of Defense: December 14, 2007.
Keywords: Doppler Shift, Statistical Modeling, Multipath
Bibliography Note: Includes bibliographical references.
Advisory Committee: Bing W. Kwan, Professor Directing Thesis; Ming Yu, Committee Member; Krishna Arora, Committee Member.
Subject(s): Electrical engineering
Computer engineering
Persistent Link to This Record: http://purl.flvc.org/fsu/fd/FSU_migr_etd-4134
Owner Institution: FSU

Choose the citation style.
Hekeno, M. (2008). Statistical Modeling of Small-Scale Fading Channels. Retrieved from http://purl.flvc.org/fsu/fd/FSU_migr_etd-4134