List decoding

About: List decoding is a research topic. Over the lifetime, 7251 publications have been published within this topic receiving 151182 citations.

System and method for resolving decoding ambiguity via dialog

Abstract: A method of language recognition wherein decoding ambiguities are identified and at least partially resolved intermediate to the language decoding procedures to reduce the subsequent number of final decoding alternatives. The user is questioned about identified decoding ambiguities as they are being decoded. There are two language decoding levels: fast match and detailed match. During the fast match decoding level a large potential candidate list is generated, very quickly. Then, during the more comprehensive (and slower) detailed match decoding level, the fast match candidate list is applied to the ambiguity to reduce the potential selections for final recognition. During the detailed match decoding level a unique candidate is selected for decoding. Decoding may be interactive and, as each ambiguity is encountered, recognition suspended to present questions to the user that will discriminate between potential response classes. Thus, recognition performance and accuracy is improved by interrupting recognition, intermediate to the decoding process, and allowing the user to select appropriate response classes to narrow the number of final decoding alternatives.

Iterative timing recovery

Abstract: The last decade has seen the development of iteratively decodable error-control codes of unprecedented power, whose large coding gains enable reliable communication at very low signal-to-noise ratio (SNR). A by-product of this trend is that timing recovery must be performed at an SNR lower than ever before. Conventional timing recovery ignores the presence or error-control coding and thus doomed to fail when the SNR is low enough. This article describes the iterative timing recovery, a method for implementing timing recovery in cooperation with iterative error-control decoding so as to approximate a more complicated receiver that jointly solves the timing recovery and decoding problems.

Code construction and decoding of parallel concatenated tail-biting codes

Abstract: Based on the two-dimensional (2-D) weight distribution of tail-biting codes we give guidelines on how to choose tail biting component codes that are especially suited for parallel concatenated coding schemes. Employing these guidelines, we tabulate tail-biting codes of different rate, length, and complexity. The performance of parallel concatenated block codes (PCBCs) using iterative (turbo) decoding is evaluated by simulation and bounds are calculated in order to study their asymptotic performance.

List decoding algorithms for certain concatenated codes

Abstract: We give ecient (polynomial-time) list-decoding algorithms for certain families of errorcorrecting codes obtained by \concatenation". Specically, we give list-decoding algorithms for codes where the \outer code" is a Reed-Solomon or Algebraic-geometric code and the \inner code" is a Hadamard code. Codes obtained by such concatenation are the best known constructions of error-correcting codes with very large minimum distance. Our decoding algorithms enhance their nice combinatorial properties with algorithmic ones, by decoding these codes up to the currently known bound on their list-decoding \capacity". In particular, the number of errors that we can correct matches (exactly) the number of errors for which it is known that the list size is bounded by a polynomial in the length of the codewords.

Decoding one out of many

Abstract: Generic decoding of linear codes is the best known attack against most code-based cryptosystems. Understanding and measuring the complexity of the best decoding techniques is thus necessary to select secure parameters. We consider here the possibility that an attacker has access to many cryptograms and is satisfied by decrypting (i.e. decoding) only one of them. We show that, for the parameter range corresponding to the McEliece encryption scheme, a variant of Stern's collision decoding can be adapted to gain a factor almost $\sqrt{N}$ when N instances are given. If the attacker has access to an unlimited number of instances, we show that the attack complexity is significantly lower, in fact the number of security bits is divided by a number slightly smaller than 3/2 (but larger than 1). Finally we give indications on how to counter those attacks.