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In this paper we address the problem of list decoding of linear codes over an integer residue ring Z q , where q is a power of a prime p. The proposed procedure exploits a particular matrix representation of the linear code over Z p r , called the standard form, and the p -adic expansion of the to-be-decoded vector. In particular, we focus on the erasure channel in which the location of the errors is known. This problem then boils down to solving a system of linear equations with coefficients in Z p r . From the parity-check matrix representations of the code we recursively select certain equations that a codeword must satisfy and have coefficients only in the field p r − 1 Z p r . This yields a step by step procedure obtaining a list of the closest codewords to a given received vector with some of its coordinates erased. We show that such an algorithm actually computes all possible erased coordinates, that is, the provided list is minimal. [ABSTRACT FROM AUTHOR]

Abstract A convolutional code C over Z p r ((D)) is a Z p r ((D)) -submodule of Z p r n ((D)) that admits a polynomial set of generators, where Z p r ((D)) stands for the ring of (semi-infinity) Laurent series. In this paper we study several structural properties of its dual C ⊥. We use these results to provide a constructive algorithm to build an explicit generator matrix of C ⊥. Moreover, we show that the transpose of such a matrix is a parity-check matrix (also called syndrome former) of C. [ABSTRACT FROM AUTHOR]

A convolutional code C over Z p r [ D ] is a Z p r [ D ] -submodule of Z p r n [ D ] where Z p r [ D ] stands for the ring of polynomials with coefficients in Z p r . In this paper, we study the list decoding problem of these codes when the transmission is performed over an erasure channel, that is, we study how much information one can recover from a codeword w ∈ C when some of its coefficients have been erased. We do that using the p -adic expansion of w and particular representations of the parity-check polynomial matrix of the code. From these matrix polynomial representations we recursively select certain equations that w must satisfy and have only coefficients in the field p r − 1 Z p r . We exploit the natural block Toeplitz structure of the sliding parity-check matrix to derive a step by step methodology to obtain a list of possible codewords for a given corrupted codeword w , that is, a list with the closest codewords to w. [ABSTRACT FROM AUTHOR]