【24h】

Generalized sphere packing bound: Basic principles

机译:广义球体包装界定:基本原则

获取原文

摘要

Kulkarni and Kiyavash recently introduced a new method to establish upper bounds on the size of deletion-correcting codes. This method is based upon tools from hypergraph theory. The deletion channel is represented by a hypergraph whose edges are the deletion balls (or spheres), so that a deletion-correcting code becomes a matching in this hypergraph. Consequently, a bound on the size of such a code can be obtained from bounds on the matching number of a hypergraph. Classical results in hypergraph theory are then invoked to compute an upper bound on the matching number as a solution to a linear-programming problem: the problem of finding fractional transversals. The method by Kulkarni and Kiyavash can be applied not only for the deletion channel but also for other channels, and in particular for those where the error spheres sizes are not all the same. This paper studies this method in its most general setup. We first show that if the error channel is regular and symmetric then the upper bound by this method coincides with the well-known sphere packing bound and thus is called here the generalized sphere packing bound. Even though this bound is explicitly given by a linear programming problem, finding its exact value may still be a challenging task. The art of finding the exact upper bound or slightly weaker ones is the assignment of weights to the hypergraph's vertices in a way that the satisfy the constraints in the linear programming problem. Every valid assignment yields an upper bound and the goal is to find assignments that provide strong upper bounds. We show that for graphs which satisfy a monotonicity property it is possible to find a general formula for such an assignment. Lastly, in order to simplify the complexity of the linear programming, we present a technique based upon graph automorphisms that in many cases can significantly reduce the number of variables and constraints in the linear programming problem. All of our results will be demonstrated an- calculated for the Z channel which will be a case study in our work.
机译:Kulkarni和Kiyavash最近推出了一种在删除校正代码大小上建立上限的新方法。该方法基于超图理论的工具。删除信道由超图表示,其边缘是删除球(或球体),使得删除校正代码成为该超图中的匹配。因此,可以从超图的匹配数上的界限获得这种代码的大小的绑定。然后调用超图理论的古典结果,以将匹配数的上限计算为线性编程问题的解决方案:找到分数横向的问题。 Kulkarni和Kiyavash的方法不仅可以用于删除通道,还可以应用于其他通道,特别是对于那些错误球体尺寸并不相同的那些。本文在其最一般的设置中研究了该方法。首先表明,如果误差通道是规则的且对称的,则该方法的上限与众所周知的球体填充绑定,因此在此称为普遍的球体包装绑定。即使这界限由线性编程问题明确给出,也可以找到其确切值可能仍然是一个具有挑战性的任务。找到精确的上限或稍微较弱的艺术是以满足线性编程问题的约束来分配给超图的顶点的权重。每个有效的分配都会产生一个上限,目标是找到提供强大的上限的分配。我们表明,对于满足单调性属性的图表,可以找到这样的分配的通式。最后,为了简化线性编程的复杂性,我们提出了一种基于图形自体形态的技术,即在许多情况下可以显着降低线性编程问题中的变量和约束的数量。我们所有的结果都将被证明为Z频道计算,这将是我们工作中的案例研究。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号