Reduced complexity ADMM-based schedules for LP decoding of LDPC convolutional codes

The ADMM based linear programming (LP) technique shows interesting error correction performance when decoding binary LDPC block codes. Nonetheless, it's applicability to decode LDPC convolutional codes (LDPC-CC) has not been yet investigated. In this paper, a first flooding based formulation of the ADMM-LP for decoding LDPC-CCs is described. In addition, reduced complexity decoding schedules to lessen the storage requirements and improve the convergence speed of an ADMM-LP based LDPC-CC decoder without significant loss in error correction performances are proposed and assessed from an algorithmic and computational/memory complexity perspectives.