Learning beyond local view: Value and information in the bits

Achaleshwar Sahai, A. Salman Avestimehr, Ashutosh Sabharwal

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

1 Scopus citations

Abstract

Given certain amount of resources available for acquiring network-state information, what should be learned? In this paper, we study this fundamental question for a Z channel where each user has certain local view and beyond that it is allowed to learn k-bits of global network state information. We show that if the interference is unknown to both the transmitters, the best learning strategy is to quantize the signal to interference ratio and reveal it to both transmitters. However, if the interference is known to at least one of the transmitters, then a two-dimensional quantization of the global channel state is the optimal utilization of the k-bits.

Original languageEnglish (US)
Title of host publication2012 46th Annual Conference on Information Sciences and Systems, CISS 2012
DOIs
StatePublished - 2012
Event2012 46th Annual Conference on Information Sciences and Systems, CISS 2012 - Princeton, NJ, United States
Duration: Mar 21 2012Mar 23 2012

Publication series

Name2012 46th Annual Conference on Information Sciences and Systems, CISS 2012

Conference

Conference2012 46th Annual Conference on Information Sciences and Systems, CISS 2012
Country/TerritoryUnited States
CityPrinceton, NJ
Period3/21/123/23/12

ASJC Scopus subject areas

  • Information Systems

Fingerprint

Dive into the research topics of 'Learning beyond local view: Value and information in the bits'. Together they form a unique fingerprint.

Cite this