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A Markov chain model for Edge Memories in stochastic decoding of LDPC codes

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3 Author(s)
Kuo-Lun Huang ; Dept. of Electr. & Comput. Eng., Northeastern Univ., Boston, MA, USA ; Gaudet, V. ; Salehi, M.

Stochastic decoding is a recently proposed method for decoding Low-Density Parity-Check (LDPC) codes. Stochastic decoding is, however, sensitive to the switching activity of stochastic bits, which can result in a latching problem. Using Edge Memories (EMs) has been proposed as a method to counter the latching problem in stochastic decoding. In this paper, we introduce a Markov chain model for EMs and study state transitions over decoding cycles. The proposed method can be used to determine the convergence and the required number of decoding cycles in stochastic decoding. Moreover, it can help to study the behavior of decoding process and to estimate the decoding time.

Published in:

Information Sciences and Systems (CISS), 2011 45th Annual Conference on

Date of Conference:

23-25 March 2011