BER Modeling for Interference Canceling Adaptive NLMS Equalizer

Simple item page
dc.contributor.authorRoy, Tamoghnaen
dc.contributor.committeechairBeex, A. A. Louisen
dc.contributor.committeememberReed, Jeffrey H.en
dc.contributor.committeememberLindner, Douglas K.en
dc.contributor.departmentElectrical and Computer Engineeringen
dc.date.accessioned2017-06-13T19:43:38Zen
dc.date.adate2015-01-13en
dc.date.available2017-06-13T19:43:38Zen
dc.date.issued2014-12-01en
dc.date.rdate2015-01-13en
dc.date.sdate2014-12-11en
dc.description.abstractAdaptive 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.en
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-12112014-103147en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-12112014-103147/en
dc.identifier.urihttp://hdl.handle.net/10919/78055en
dc.language.isoen_USen
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectGaussian Mixture Modelen
dc.subjectBER Modelingen
dc.subjectNon-Wiener Effectsen
dc.subject(N)LMS Equalizeren
dc.titleBER Modeling for Interference Canceling Adaptive NLMS Equalizeren
dc.typeThesisen
dc.type.dcmitypeTexten
thesis.degree.disciplineElectrical and Computer Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
etd-12112014-103147_Roy_T_T_2014.pdf
Size:
6.58 MB
Format:
Adobe Portable Document Format
Download

Collections

Masters Theses