Sparsening Filter Design for Iterative Soft-Input Soft-Output Detectors

Abstract

A large body of research exists around the idea of channel shortening, where a prefilter is designed to reduce the effective channel impulse response to some smaller number of contiguous taps. This idea was originally conceived to reduce the complexity of Viterbi-based maximum-likelihood equalizers. Here, we consider a generalization of channel shortening which we term channel sparsening . In this case, a prefilter is designed to reduce the effective channel to a small number of nonzero taps which do not need to be contiguous. When used in combination with belief-propagation-based maximum a posteriori (MAP) detectors, an analogous complexity reduction can be realized. We address the design aspects of sparsening filters, including several approaches to minimize the bit error rate of MAP detectors. We devote attention to the interaction of the sparsening filter and detector, and demonstrate the performance gains through simulation.

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Document Details

Document Type
Technical Report
Publication Date
Feb 29, 2012
Accession Number
ADA557288

Entities

People

  • Andrew G. Klein
  • Raquel G. Machado
  • Richard K. Martin

Organizations

  • Worcester Polytechnic Institute

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Acoustic Communications
  • Air Force
  • Algorithms
  • Communication Channels
  • Communication Systems
  • Computational Complexity
  • Data Science
  • Detectors
  • Engineering
  • Frequency Response
  • Information Science
  • Multiple Input Multiple Output
  • Noise
  • Simplex Method
  • Simulations
  • Statistical Algorithms
  • Wireless Communications

Fields of Study

  • Engineering

Readers

  • Economics
  • Marine Ecological Systems Migration
  • Radio communications and signal processing.