Single sensor blind time-frequency activity estimation of a mixture of radio signals via CP tensor decomposition

Christopher Mueller-Smith, Predrag Spasojevic

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

3 Scopus citations

Abstract

We consider reception of non-persistently excitated radio signals that overlap in time and frequency from a group of transmitters to a single receiver. The signals can be categorized as using a linear modulation or a non-linear modulation that can be approximated as a finite sum of linearly modulated signals. An analysis of a particular slice of the fourth-order cumulant spectra (trispectra) of this signal mixture reveals that the structure of their combined trispectrum can be modeled as a 3-dimensional tensor formed by a sum of rank 1 tensors corresponding to the trispectra of the component signals which fits the Canonical Decomposition/Parallel Factors (CP) tensor model. We develop an algorithm to decompose the trispectrum tensor which allows us to blindly estimate the power spectra, activity (in time) sequences, and number of signals contributing to an approximation of nonlinear signals. We then simulate the algorithm to verify results and quantify performance.

Original languageEnglish (US)
Title of host publicationProceedings - 2014 IEEE Military Communications Conference
Subtitle of host publicationAffordable Mission Success: Meeting the Challenge, MILCOM 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages617-622
Number of pages6
ISBN (Electronic)9781479967704
DOIs
StatePublished - Nov 13 2014
Event33rd Annual IEEE Military Communications Conference, MILCOM 2014 - Baltimore, United States
Duration: Oct 6 2014Oct 8 2014

Publication series

NameProceedings - IEEE Military Communications Conference MILCOM

Other

Other33rd Annual IEEE Military Communications Conference, MILCOM 2014
Country/TerritoryUnited States
CityBaltimore
Period10/6/1410/8/14

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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