Bit-Error-Rate-Minimizing Channel Shortening Using Post-FEQ Diversity Combining and a Genetic Algorithm

Abstract

Channel shortening filter design is a widely examined topic in the literature. Most of the channel shortening equalizer proposals depend on perfect channel state information (CSI). However, this information may not be available in all situations. In cases where the channel state information is not needed, blind adaptive equalization techniques are appropriate. In wireline communication systems, the CSE design is based on maximizing the bit rate, but in wireless systems, there is a fixed bit loading algorithm, and the performance metric is Bit Error Rate (BER) minimization. In this work, a CSE is developed for multicarrier and single-carrier cyclic prefixed (SCCP) systems which attempt to minimize the BER. To minimize the BER, a Genetic Algorithm (GA) is used. If the CSI is shorter than the CP, the equalization can be done by a frequency domain equalizer (FEQ), which is just a bank of complex scalars. However, in the literature the adaptive FEQ design has not been well examined. The second phase of this thesis focuses on different types of algorithms for adapting the FEQ and modifying the FEQ architecture to get a lower BER.

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Document Details

Document Type
Technical Report
Publication Date
Mar 10, 2009
Accession Number
ADA498821

Entities

People

  • Gokhan Altin

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Amplitude Modulation
  • Channel State Information
  • Communication Channels
  • Communication Systems
  • Computational Complexity
  • Department Of Defense
  • Digital Communications
  • Electrical Engineering
  • Frequency Division Multiplexing
  • Frequency Domain
  • Local Area Networks
  • Modulation
  • Multiple Input Multiple Output
  • Orthogonal Frequency Division Multiplexing
  • Signal Processing

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Radio communications and signal processing.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Biotechnology