TY - JOUR

T1 - Nonuniform SINR+Voronoi diagrams are effectively uniform

AU - Kantor, Erez

AU - Lotker, Zvi

AU - Parter, Merav

AU - Peleg, David

N1 - Funding Information: Supported in a part by NSF Award Numbers CCF-1217506, CCF-AF-0937274, 0939370-CCF, and AFOSR Contract Numbers FA9550-14-1-0403 and FA9550-13-1-0042.Supported in part by the Ministry of Science, Technology and Space, Israel, French-Israeli project MAIMONIDE 31768XL, the Israel Science Foundation (grant 1549/13) and the French-Israeli Laboratory FILOFOCS.Supported in part by the Israel Science Foundation (grant 1549/13), the I-CORE program of the Israel PBC and ISF (grant 4/11), and the Rothschild and Fulbright Fellowships.Supported in part by the Israel Science Foundation (grant 1549/13) and the I-CORE program of the Israel PBC and ISF (grant 4/11). Publisher Copyright: © 2021

PY - 2021/7/22

Y1 - 2021/7/22

N2 - This paper concerns the behavior of an SINR diagram of wireless systems, composed of a set S of n stations embedded in Rd, 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 effectively5 fat. This holds for every power assignment, every path-loss parameter α and every dimension d≥1. The convexity property also holds for every SINR threshold β>0, and the effective fatness property holds for any β>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 si for any given reception point p∈P in its Voronoi cell [Formula presented]. 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.

AB - This paper concerns the behavior of an SINR diagram of wireless systems, composed of a set S of n stations embedded in Rd, 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 effectively5 fat. This holds for every power assignment, every path-loss parameter α and every dimension d≥1. The convexity property also holds for every SINR threshold β>0, and the effective fatness property holds for any β>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 si for any given reception point p∈P in its Voronoi cell [Formula presented]. 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.

KW - Point location

KW - SINR

KW - Voronoi diagram

UR - http://www.scopus.com/inward/record.url?scp=85108081775&partnerID=8YFLogxK

U2 - https://doi.org/10.1016/j.tcs.2021.04.018

DO - https://doi.org/10.1016/j.tcs.2021.04.018

M3 - Article

SN - 0304-3975

VL - 878-879

SP - 53

EP - 66

JO - Theoretical Computer Science

JF - Theoretical Computer Science

ER -