Title page for ETD etd-12112014-103147


Type of Document Master's Thesis
Author Roy, Tamoghna
Author's Email Address tamoghna@vt.edu
URN etd-12112014-103147
Title BER Modeling for Interference Canceling Adaptive NLMS Equalizer
Degree Master of Science
Department Electrical and Computer Engineering
Advisory Committee
Advisor Name Title
Dr. A. A. (Louis) Beex Committee Chair
Dr. Douglas K. Lindner Committee Member
Dr. Jeffrey H. Reed Committee Member
Keywords
  • Gaussian Mixture Model
  • BER Modeling
  • Non-Wiener Effects
  • (N)LMS Equalizer
Date of Defense 2014-12-01
Availability unrestricted
Abstract
Adaptive LMS equalizers are widely used in digital communication systems for their simplicity in implementation. Conventional adaptive filtering theory suggests the upper bound of the performance of such equalizer is determined by the performance of a Wiener filter of the same structure. However, in the presence of a narrowband interferer the performance of the LMS equalizer is better than that of its Wiener counterpart. This phenomenon, termed a non-Wiener effect, has been observed before and substantial work has been done in explaining the underlying reasons. In this work, we focus on the Bit Error Rate (BER) performance of LMS equalizers.

At first a model – the Gaussian Mixture (GM) model – is presented to estimate the BER performance of a Wiener filter operating in an environment dominated by a narrowband interferer. Simulation results show that the model predicts BER accurately for a wide range of SNR, ISR, and equalizer length. Next, a model similar to GM termed the Gaussian Mixture using Steady State Weights (GMSSW) model is proposed to model the BER behavior of the adaptive NLMS equalizer. Simulation results show unsatisfactory performance of the model. A detailed discussion is presented that points out the limitations of the GMSSW model, thereby providing some insight into the non-Wiener behavior of (N)LMS equalizers. An improved model, the Gaussian with Mean Square Error (GMSE), is then proposed. Simulation results show that the GMSE model is able to model the non-Wiener characteristics of the NLMS equalizer when the normalized step size is between 0 and 0.4. A brief discussion is provided on why the model is inaccurate for larger step sizes.

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