Show simple item record

dc.contributor.authorAdler, Amir
dc.contributor.authorWax, Mati
dc.date.accessioned2018-04-12T17:23:48Z
dc.date.available2018-04-12T17:23:48Z
dc.date.issued2018-04-12
dc.identifier.urihttp://hdl.handle.net/1721.1/114672
dc.description.abstractWe present a novel convex-optimization-based approach to the solutions of a family of problems involving constant modulus signals. The family of problems includes the constant modulus and the constrained constant modulus, as well as the modified constant modulus and the constrained modified constant modulus. The usefulness of the proposed solutions is demonstrated for the tasks of blind beamforming and blind multiuser detection. The performance of these solutions, as we demonstrate by simulated data, is superior to existing methods.en_US
dc.description.sponsorshipThis work was supported by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF-1231216.en_US
dc.language.isoen_USen_US
dc.publisherCenter for Brains, Minds and Machines (CBMM)en_US
dc.relation.ispartofseriesCBMM Memo Series;077
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/*
dc.subjectConstant modulusen_US
dc.subjectconvex optimizationen_US
dc.subjecttrace normen_US
dc.titleConstant Modulus Algorithms via Low-Rank Approximationen_US
dc.typeTechnical Reporten_US
dc.typeWorking Paperen_US
dc.typeOtheren_US


Files in this item

Thumbnail
Thumbnail

This item appears in the following Collection(s)

Show simple item record