Polynomial-time Capacity Calculation and Scheduling for Half-Duplex 1-2-1 Networks

Yahya H. Ezzeldin, Martina Cardone, Christina Fragouli, Giuseppe Caire

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

This paper studies the 1-2-1 half-duplex network model, where two half-duplex nodes can communicate only if they point "beams" at each other; otherwise, no signal can be exchanged or interference can be generated. The main result of this paper is the design of two polynomial-time algorithms that: (i) compute the approximate capacity of the 1-2-1 half-duplex network and, (ii) find the network schedule optimal for the approximate capacity. The paper starts by expressing the approximate capacity as a linear program with an exponential number of constraints. A core technical component consists of building a polynomial-time separation oracle for this linear program, by using algorithmic tools such as perfect matching polytopes and Gomory-Hu trees.

Original languageEnglish (US)
Title of host publication2019 IEEE International Symposium on Information Theory, ISIT 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages460-464
Number of pages5
ISBN (Electronic)9781538692912
DOIs
StatePublished - Jul 2019
Event2019 IEEE International Symposium on Information Theory, ISIT 2019 - Paris, France
Duration: Jul 7 2019Jul 12 2019

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
Volume2019-July
ISSN (Print)2157-8095

Conference

Conference2019 IEEE International Symposium on Information Theory, ISIT 2019
Country/TerritoryFrance
CityParis
Period7/7/197/12/19

Bibliographical note

Funding Information:
Y. H. Ezzeldin and C. Fragouli were supported in part by NSF awards 1514531, 1824568 and UC-NL grant LFR-18-548554. 1Constant gap refers to a quantity that is independent of the channel coefficients and operating SNR, and solely depends on the number of nodes.

Funding Information:
Y. H. Ezzeldin and C. Fragouli were supported in part by NSF awards 1514531, 1824568 and UC-NL grant LFR-18-548554.

Publisher Copyright:
© 2019 IEEE.

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