TY - JOUR
T1 - Batched point location in SINR Diagrams via algebraic tools
AU - Aronov, Boris
AU - Katz, Matthew J.
N1 - Funding Information:
An earlier version of this article (excluding Sections 4 and 5) was presented at ICALP’15 [3]. Work on this article by B.A. has been partially supported by the National Science Foundation Grants No. CCF-11-17336, No. CCF-12-18791, and No. CCF-15-40656, and by Grant No. 2014/170 from the US-Israel Binational Science Foundation. Work on this article by M.K. has been supported by Grant No. 2014/170 from the US-Israel Binational Science Foundation, and by Grants No. 1045/10 and No. 1884/16 from the Israel Science Foundation. Authors’ addresses: B. Aronov, Department of Computer Science and Engineering, Tandon School of Engineering, New York University, 2 MetroTech Center, Brooklyn, NY 11201, USA; email: boris.aronov@nyu.edu; M. J. Katz, Department of Computer Science, Ben-Gurion University of the Negev, P.O.B. 653, Beer-Sheva 8410501, Israel; email: matya@cs.bgu.ac.il. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. © 2018 ACM 1549-6325/2018/08-ART41 $15.00 https://doi.org/10.1145/3209678
Publisher Copyright:
© 2018 ACM.
PY - 2018/8/1
Y1 - 2018/8/1
N2 - The SINR (Signal to Interference plus Noise Ratio) model for the quality of wireless connections has been the subject of extensive recent study. It attempts to predict whether a particular transmitter is heard at a specific location, in a setting consisting of n simultaneous transmitters and background noise. The SINR model gives rise to a natural geometric object, the SINR diagram, which partitions the space into n regions where each of the transmitters can be heard and the remaining space where no transmitter can be heard. Efficient point location in the SINR diagram, i.e., being able to build a data structure that facilitates determining, for a query point, whether any transmitter is heard there, and if so, which one, has been recently investigated in several articles. These planar data structures are constructed in time at least quadratic in n and support logarithmic-time approximate queries.Moreover, the performance of some of the proposed structures depends strongly not only on the number n of transmitters and on the approximation parameter, but also on some geometric parameters that cannot be bounded a priori as a function of n or. In this article, we address the question of batched point location queries, i.e., answering many queries simultaneously. Specifically, in one dimension, we can answer n queries exactly in amortized polylogarithmic time per query, while in the plane we can do it approximately. In another result, we show how to answer n2 queries exactly in amortized polylogarithmic time per query, assuming the queries are located on a possibly non-uniform n ~ n grid. All these results can handle arbitrary power assignments to the transmitters. Moreover, the amortized query time in these results depends only on n and We also show how to speed up the preprocessing in a previously proposed point-location structure in SINR diagram for uniform-power sites, by almost a full order of magnitude. For this, we obtain results on the sensitivity of the reception regions to slight changes in the reception threshold, which are of independent interest. Finally, these results demonstrate the (so far underutilized) power of combining algebraic tools with those of computational geometry and other fields.
AB - The SINR (Signal to Interference plus Noise Ratio) model for the quality of wireless connections has been the subject of extensive recent study. It attempts to predict whether a particular transmitter is heard at a specific location, in a setting consisting of n simultaneous transmitters and background noise. The SINR model gives rise to a natural geometric object, the SINR diagram, which partitions the space into n regions where each of the transmitters can be heard and the remaining space where no transmitter can be heard. Efficient point location in the SINR diagram, i.e., being able to build a data structure that facilitates determining, for a query point, whether any transmitter is heard there, and if so, which one, has been recently investigated in several articles. These planar data structures are constructed in time at least quadratic in n and support logarithmic-time approximate queries.Moreover, the performance of some of the proposed structures depends strongly not only on the number n of transmitters and on the approximation parameter, but also on some geometric parameters that cannot be bounded a priori as a function of n or. In this article, we address the question of batched point location queries, i.e., answering many queries simultaneously. Specifically, in one dimension, we can answer n queries exactly in amortized polylogarithmic time per query, while in the plane we can do it approximately. In another result, we show how to answer n2 queries exactly in amortized polylogarithmic time per query, assuming the queries are located on a possibly non-uniform n ~ n grid. All these results can handle arbitrary power assignments to the transmitters. Moreover, the amortized query time in these results depends only on n and We also show how to speed up the preprocessing in a previously proposed point-location structure in SINR diagram for uniform-power sites, by almost a full order of magnitude. For this, we obtain results on the sensitivity of the reception regions to slight changes in the reception threshold, which are of independent interest. Finally, these results demonstrate the (so far underutilized) power of combining algebraic tools with those of computational geometry and other fields.
KW - Algebraic Methods
KW - Batched Point Location
KW - Fast Polynomial Multiplication
KW - Fast Polynomial Multipoint Evaluation
KW - Range Searching
KW - Sinr Diagram
KW - Sinr Model
KW - Wireless Networks
UR - http://www.scopus.com/inward/record.url?scp=85049792366&partnerID=8YFLogxK
U2 - 10.1145/3209678
DO - 10.1145/3209678
M3 - Article
AN - SCOPUS:85049792366
VL - 14
JO - ACM Transactions on Algorithms
JF - ACM Transactions on Algorithms
SN - 1549-6325
IS - 4
M1 - 41
ER -