Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.654137
Title: Probabilistic techniques for equalization of the mobile radio channel in the presence of co-channel interference
Author: Luschi, Carlo
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 2002
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Abstract:
This thesis studies the problem of soft-output equalization of the mobile radio channel in interference-limited environments, where it is often difficult to obtain an accurate statistical model of the (non-Gaussian) disturbance. The first part of the thesis proposes a new technique for single-channel MAP trellis equalization in the presence of multipath and non-Gaussian interference. The approach is based on the non-parametric estimation of the density function of the overall disturbance by means of kernel smoothing. The work considers the problem of density estimation with limited volume of data, and addresses the use of a whitening filter in the presence of coloured interference. As an application, simulation results are provided for the GSM system, showing a significant performance improvement with respect to the trellis equalizer based on the Gaussian assumption. The second part of the thesis considers the case of an antenna array receiver, and studies a simple method to derive the reliability information at the output of a deterministic decision-feedback least-squares space-time equalizer. Computer simulations for the Enhanced Data Rates for GSM Evolution (EDGE)/Enhanced General Packet Radio Service (EGPRS) system show that the receiver performance can be significantly improved by a soft-output calculation based on short-term statistics of the equalizer output error. The thesis also addresses the additional use of soft-decision feedback, which provides further robustness to the proposed soft-output equalizer. The study shows the relevance of probabilistic processing for robust equalization of the wireless channel in the presence of non-Gaussian interference, and emphasizes the advantages of strategies that do not rely on a statistical model of the disturbance.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.654137  DOI: Not available
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