Stochastic Multipath Modeling of Wideband Polarized MIMO Channels

Doctoral Dissertation


Multiple input multiple output (MIMO) and small cells are key technologies utilized in advanced wireless networks. With the shrinkage in cell radius, the probability of line-of-sight (LoS) or specular reflections increases, impacting the form of the channel model that should be used. MIMO systems can also be equipped with multi-polarized arrays to improve their performance, however, this adds to the complexity and asymmetry in the channel model. In this thesis we propose a novel wideband statistical MIMO channel model that is capable of incorporating LoS and specular reflections into a correlation-based polarization-sensitive multipath MIMO model. LoS and specular reflections are observed as sinusoidal components in the channel impulse response, however, their detection and estimation is a difficult task since the number of “stationary’ independent samples taken in the time-domain from a wideband channel impulse response is limited to a small number before the channel statistics begin to change substantially. We apply extreme value theory (EVT) to the problem of enumerating sinusoids in unknown correlated Gaussian noise. Results are applied in an algorithm that allows enumeration and estimation of LoS or specular reflections in a sequence of measured channel impulse responses. In order to demonstrate the efficacy of the approach with real-world measurements, we designed a wideband MIMO channel sounder to capture channel impulse response snapshots. Assuming the channel model form, we applied parameter estimation techniques to derive a wideband model for the observed channel. This model was then shown to represent the measured channel using various figures of merit such as capacity, frequency correlation function and singular value distribution. Two primary outcomes resulted from this work. First, a stochastic model for wideband multi-polarized MIMO channels that incorporates multiple line-of-sight or specular rays has been developed and empirically validated in an indoor environment. Second, a model order selection criterion has been proposed and demonstrated for the enumeration of sinusoids in unknown correlated Gaussian noise.


Attribute NameValues
  • etd-04172015-153814

Author Farzad Talebi
Advisor Dr. Thomas Pratt
Contributor Dr. Thomas Fuja, Committee Member
Contributor Dr. Nicholas Laneman, Committee Member
Contributor Dr. Thomas Pratt, Committee Chair
Contributor Dr. Martin Haenggi, Committee Member
Degree Level Doctoral Dissertation
Degree Discipline Electrical Engineering
Degree Name PhD
Defense Date
  • 2015-03-30

Submission Date 2015-04-17
  • United States of America

  • Signal Processing

  • Parameter Estimation

  • Wireless

  • MIMO

  • Channel Model

  • Wideband

  • University of Notre Dame

  • English

Record Visibility Public
Content License
  • All rights reserved

Departments and Units


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