152 research outputs found

    LP-decodable multipermutation codes

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    In this paper, we introduce a new way of constructing and decoding multipermutation codes. Multipermutations are permutations of a multiset that may consist of duplicate entries. We first introduce a new class of matrices called multipermutation matrices. We characterize the convex hull of multipermutation matrices. Based on this characterization, we propose a new class of codes that we term LP-decodable multipermutation codes. Then, we derive two LP decoding algorithms. We first formulate an LP decoding problem for memoryless channels. We then derive an LP algorithm that minimizes the Chebyshev distance. Finally, we show a numerical example of our algorithm.Comment: This work was supported by NSF and NSERC. To appear at the 2014 Allerton Conferenc

    Computing the Ball Size of Frequency Permutations under Chebyshev Distance

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    Let SnλS_n^\lambda be the set of all permutations over the multiset {1,...,1λ,...,m,...,mλ}\{\overbrace{1,...,1}^{\lambda},...,\overbrace{m,...,m}^\lambda\} where n=mλn=m\lambda. A frequency permutation array (FPA) of minimum distance dd is a subset of SnλS_n^\lambda in which every two elements have distance at least dd. FPAs have many applications related to error correcting codes. In coding theory, the Gilbert-Varshamov bound and the sphere-packing bound are derived from the size of balls of certain radii. We propose two efficient algorithms that compute the ball size of frequency permutations under Chebyshev distance. Both methods extend previous known results. The first one runs in O((2dλdλ)2.376logn)O({2d\lambda \choose d\lambda}^{2.376}\log n) time and O((2dλdλ)2)O({2d\lambda \choose d\lambda}^{2}) space. The second one runs in O((2dλdλ)(dλ+λλ)nλ)O({2d\lambda \choose d\lambda}{d\lambda+\lambda\choose \lambda}\frac{n}{\lambda}) time and O((2dλdλ))O({2d\lambda \choose d\lambda}) space. For small constants λ\lambda and dd, both are efficient in time and use constant storage space.Comment: Submitted to ISIT 201

    Constructions of Rank Modulation Codes

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    Rank modulation is a way of encoding information to correct errors in flash memory devices as well as impulse noise in transmission lines. Modeling rank modulation involves construction of packings of the space of permutations equipped with the Kendall tau distance. We present several general constructions of codes in permutations that cover a broad range of code parameters. In particular, we show a number of ways in which conventional error-correcting codes can be modified to correct errors in the Kendall space. Codes that we construct afford simple encoding and decoding algorithms of essentially the same complexity as required to correct errors in the Hamming metric. For instance, from binary BCH codes we obtain codes correcting tt Kendall errors in nn memory cells that support the order of n!/(log2n!)tn!/(\log_2n!)^t messages, for any constant t=1,2,...t= 1,2,... We also construct families of codes that correct a number of errors that grows with nn at varying rates, from Θ(n)\Theta(n) to Θ(n2)\Theta(n^{2}). One of our constructions gives rise to a family of rank modulation codes for which the trade-off between the number of messages and the number of correctable Kendall errors approaches the optimal scaling rate. Finally, we list a number of possibilities for constructing codes of finite length, and give examples of rank modulation codes with specific parameters.Comment: Submitted to IEEE Transactions on Information Theor

    Limited-Magnitude Error-Correcting Gray Codes for Rank Modulation

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    We construct Gray codes over permutations for the rank-modulation scheme, which are also capable of correcting errors under the infinity-metric. These errors model limited-magnitude or spike errors, for which only single-error-detecting Gray codes are currently known. Surprisingly, the error-correcting codes we construct achieve a better asymptotic rate than that of presently known constructions not having the Gray property, and exceed the Gilbert-Varshamov bound. Additionally, we present efficient ranking and unranking procedures, as well as a decoding procedure that runs in linear time. Finally, we also apply our methods to solve an outstanding issue with error-detecting rank-modulation Gray codes (snake-in-the-box codes) under a different metric, the Kendall τ\tau-metric, in the group of permutations over an even number of elements S2nS_{2n}, where we provide asymptotically optimal codes.Comment: Revised version for journal submission. Additional results include more tight auxiliary constructions, a decoding shcema, ranking/unranking procedures, and application to snake-in-the-box codes under the Kendall tau-metri

    Evaluation of mixed permutation codes in PLC channels, using hamming distance profile

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    Abstract: We report a new concept involving an adaptive mixture of different sets of permutation codes (PC) in a single DPSK-OFDM modulation scheme. Since this scheme is robust and the algorithms involved are simple, it is a good candidate for implementation for OFDM-based power line communication (PLC) systems. By using a special and easy concept called Hamming distance profile, as a comparison tool, we are able to showcase the strength of the new PC scheme over other schemes reported in literature, in handling the incessant noise types associated with PLC channels. This prediction tool is also useful for selecting an efficient PC codebook out of a number of ! similar ones

    Multipermutation Codes in the Ulam Metric for Nonvolatile Memories

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    We address the problem of multipermutation code design in the Ulam metric for novel storage applications. Multipermutation codes are suitable for flash memory where cell charges may share the same rank. Changes in the charges of cells manifest themselves as errors whose effects on the retrieved signal may be measured via the Ulam distance. As part of our analysis, we study multipermutation codes in the Hamming metric, known as constant composition codes. We then present bounds on the size of multipermutation codes and their capacity, for both the Ulam and the Hamming metrics. Finally, we present constructions and accompanying decoders for multipermutation codes in the Ulam metric

    Increasing the Minimum Distance of Codes by Twisting

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