33,370 research outputs found

    Low-Density Parity-Check Codes From Transversal Designs With Improved Stopping Set Distributions

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    This paper examines the construction of low-density parity-check (LDPC) codes from transversal designs based on sets of mutually orthogonal Latin squares (MOLS). By transferring the concept of configurations in combinatorial designs to the level of Latin squares, we thoroughly investigate the occurrence and avoidance of stopping sets for the arising codes. Stopping sets are known to determine the decoding performance over the binary erasure channel and should be avoided for small sizes. Based on large sets of simple-structured MOLS, we derive powerful constraints for the choice of suitable subsets, leading to improved stopping set distributions for the corresponding codes. We focus on LDPC codes with column weight 4, but the results are also applicable for the construction of codes with higher column weights. Finally, we show that a subclass of the presented codes has quasi-cyclic structure which allows low-complexity encoding.Comment: 11 pages; to appear in "IEEE Transactions on Communications

    Planar 3-dimensional assignment problems with Monge-like cost arrays

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    Given an n×n×pn\times n\times p cost array CC we consider the problem pp-P3AP which consists in finding pp pairwise disjoint permutations φ1,φ2,…,φp\varphi_1,\varphi_2,\ldots,\varphi_p of {1,…,n}\{1,\ldots,n\} such that ∑k=1p∑i=1nciφk(i)k\sum_{k=1}^{p}\sum_{i=1}^nc_{i\varphi_k(i)k} is minimized. For the case p=np=n the planar 3-dimensional assignment problem P3AP results. Our main result concerns the pp-P3AP on cost arrays CC that are layered Monge arrays. In a layered Monge array all n×nn\times n matrices that result from fixing the third index kk are Monge matrices. We prove that the pp-P3AP and the P3AP remain NP-hard for layered Monge arrays. Furthermore, we show that in the layered Monge case there always exists an optimal solution of the pp-3PAP which can be represented as matrix with bandwidth ≤4p−3\le 4p-3. This structural result allows us to provide a dynamic programming algorithm that solves the pp-P3AP in polynomial time on layered Monge arrays when pp is fixed.Comment: 16 pages, appendix will follow in v

    Testing of random matrices

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    Let nn be a positive integer and X=[xij]1≤i,j≤nX = [x_{ij}]_{1 \leq i, j \leq n} be an n×nn \times n\linebreak \noindent sized matrix of independent random variables having joint uniform distribution \hbox{Pr} {x_{ij} = k \hbox{for} 1 \leq k \leq n} = \frac{1}{n} \quad (1 \leq i, j \leq n) \koz. A realization M=[mij]\mathcal{M} = [m_{ij}] of XX is called \textit{good}, if its each row and each column contains a permutation of the numbers 1,2,...,n1, 2,..., n. We present and analyse four typical algorithms which decide whether a given realization is good
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