Decoding LDPC convolutional codes on Markov channels

  • Authors:
  • Manohar Kashyap;Chris Winstead

  • Affiliations:
  • Department of Electrical and Computer Engineering, College of Engineering, Utah State University, Logan, UT;Department of Electrical and Computer Engineering, College of Engineering, Utah State University, Logan, UT

  • Venue:
  • EURASIP Journal on Wireless Communications and Networking
  • Year:
  • 2008

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Abstract

This paper describes a pipelined iterative technique for joint decoding and channel state estimation of LDPC convolutional codes over Markov channels. Example designs are presented for the Gilbert-Elliott discrete channel model. We also compare the performance and complexity of our algorithm against joint decoding and state estimation of conventional LDPC block codes. Complexity analysis reveals that our pipelined algorithm reduces the number of operations per time step compared to LDPC block codes, at the expense of increased memory and latency. This tradeoff is favorable for low-power applications.