Title page for ETD etd-04112007-104316

Type of Document Dissertation
Author Ikuma, Takeshi
Author's Email Address tikuma@vt.edu
URN etd-04112007-104316
Title Non-Wiener Effects in Narrowband Interference Mitigation Using Adaptive Transversal Equalizers
Degree PhD
Department Electrical and Computer Engineering
Advisory Committee
Advisor Name Title
Beex, A. A. Louis Committee Chair
Ball, Joseph A. Committee Member
Baumann, William T. Committee Member
Kachroo, Pushkin Committee Member
Tranter, William H. Committee Member
  • Butterweck expansion
  • Transfer function approximation
  • MSE analysis
  • Mean weight analysis
  • LMS algorithm
  • NLMS algorithm
Date of Defense 2007-04-10
Availability unrestricted

The least mean square (LMS) algorithm is widely expected to operate near the corresponding Wiener filter solution. An exception to this popular perception occurs when the algorithm is used to adapt a transversal equalizer in the presence of additive narrowband interference. The steady-state LMS equalizer behavior does not correspond to that of the fixed Wiener equalizer: the mean of its weights is different from the Wiener weights, and its mean squared error (MSE) performance may be significantly better than the Wiener performance. The contributions of this study serve to better understand this so-called non-Wiener phenomenon of the LMS and normalized LMS adaptive transversal equalizers.

The first contribution is the analysis of the mean of the LMS weights in steady state, assuming a large interference-to-signal ratio (ISR). The analysis is based on the Butterweck expansion of the weight update equation. The equalization problem is transformed to an equivalent interference estimation problem to make the analysis of the Butterweck expansion tractable. The analytical results are valid for all step-sizes. Simulation results are included to support the analytical results and show that the analytical results predict the simulation results very well, over a wide range of ISR.

The second contribution is the new MSE estimator based on the expression for the mean of the LMS equalizer weight vector. The new estimator shows vast improvement over the Reuter-Zeidler MSE estimator. For the development of the new MSE estimator, the transfer function approximation of the LMS algorithm is generalized for the steady-state analysis of the LMS algorithm. This generalization also revealed the cause of the breakdown of the MSE estimators when the interference is not strong, as the assumption that the variation of the weight vector around its mean is small relative to the mean of the weight vector itself.

Both the expression for the mean of the weight vector and for the MSE estimator are analyzed for the LMS algorithm at first. The results are then extended to the normalized LMS algorithm by the simple means of adaptation step-size redefinition.

  Filename       Size       Approximate Download Time (Hours:Minutes:Seconds) 
 28.8 Modem   56K Modem   ISDN (64 Kb)   ISDN (128 Kb)   Higher-speed Access 
  IKUMA-PhD.pdf 1.79 Mb 00:08:18 00:04:16 00:03:44 00:01:52 00:00:09

Browse All Available ETDs by ( Author | Department )

dla home
etds imagebase journals news ereserve special collections
virgnia tech home contact dla university libraries

If you have questions or technical problems, please Contact DLA.