34 research outputs found

    On Optimal Anticodes over Permutations with the Infinity Norm

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    Motivated by the set-antiset method for codes over permutations under the infinity norm, we study anticodes under this metric. For half of the parameter range we classify all the optimal anticodes, which is equivalent to finding the maximum permanent of certain (0,1)(0,1)-matrices. For the rest of the cases we show constraints on the structure of optimal anticodes

    Two-dimensional patterns with distinct differences; constructions, bounds, and maximal anticodes

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    A two-dimensional (2-D) grid with dots is called a configuration with distinct differences if any two lines which connect two dots are distinct either in their length or in their slope. These configurations are known to have many applications such as radar, sonar, physical alignment, and time-position synchronization. Rather than restricting dots to lie in a square or rectangle, as previously studied, we restrict the maximum distance between dots of the configuration; the motivation for this is a new application of such configurations to key distribution in wireless sensor networks. We consider configurations in the hexagonal grid as well as in the traditional square grid, with distances measured both in the Euclidean metric, and in the Manhattan or hexagonal metrics. We note that these configurations are confined inside maximal anticodes in the corresponding grid. We classify maximal anticodes for each diameter in each grid. We present upper bounds on the number of dots in a pattern with distinct differences contained in these maximal anticodes. Our bounds settle (in the negative) a question of Golomb and Taylor on the existence of honeycomb arrays of arbitrarily large size. We present constructions and lower bounds on the number of dots in configurations with distinct differences contained in various 2-D shapes (such as anticodes) by considering periodic configurations with distinct differences in the square grid

    Enumerative Coding for Grassmannian Space

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    The Grassmannian space \Gr is the set of all k−k-dimensional subspaces of the vector space~\smash{\F_q^n}. Recently, codes in the Grassmannian have found an application in network coding. The main goal of this paper is to present efficient enumerative encoding and decoding techniques for the Grassmannian. These coding techniques are based on two different orders for the Grassmannian induced by different representations of kk-dimensional subspaces of \F_q^n. One enumerative coding method is based on a Ferrers diagram representation and on an order for \Gr based on this representation. The complexity of this enumerative coding is O(k5/2(n−k)5/2)O(k^{5/2} (n-k)^{5/2}) digit operations. Another order of the Grassmannian is based on a combination of an identifying vector and a reduced row echelon form representation of subspaces. The complexity of the enumerative coding, based on this order, is O(nk(n−k)log⁡nlog⁡log⁡n)O(nk(n-k)\log n\log\log n) digits operations. A combination of the two methods reduces the complexity on average by a constant factor.Comment: to appear in IEEE Transactions on Information Theor
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