Nonuniform Sinr Plus Voronoi Diagrams Are Effectively Uniform

THEORETICAL COMPUTER SCIENCE(2021)

引用 1|浏览12
暂无评分
摘要
This paper concerns the behavior of an SINR diagram of wireless systems, composed of a set S of n stations embedded in R-d, when restricted to the corresponding Voronoi diagram-imposed on S. The diagram obtained by restricting the SINR zones to their corresponding Voronoi cells is referred to hereafter as an SINR+Voronoi diagram.Uniform SINR diagrams, where all stations transmit with the same power, are simple and nicely structured, e.g., the station reception zones are convex and "fat". In contrast, nonuniform SINR diagrams might be complex; the reception zones might be fractured and their boundaries might contain many singular points. In this paper, we establish the perhaps surprising fact that a nonuniform SINR+Voronoi diagram is topologically almost as nice as a uniform SINR diagram. In particular, it is convex and effectively(5) fat. This holds for every power assignment, every path-loss parameter alpha and every dimension d >= 1. The convexity property also holds for every SINR threshold beta > 0, and the effective fatness property holds for any beta > 1. These fundamental properties provide a theoretical justification to engineering practices basing zonal tessellations on the Voronoi diagram, and help to explain the soundness and efficacy of such practices.We also consider two algorithmic applications. The first concerns the Power Control with Voronoi Diagram(PCVD) problem, where given n stations embedded in some polygon P, it is required to find the power assignment that optimizes the SINR threshold of the transmission station s(i) for any given reception point p is an element of P in its Voronoi cell VOR(s(i)). The second application is approximate point location; we show that for SINR+Voronoi zones, this task can be solved considerably more efficiently than in the general non-uniform case. (C) 2021 Published by Elsevier B.V.
更多
查看译文
关键词
Voronoi diagram, SINR, Point location
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要