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DTSTART:20380118T221407
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DTSTART:19930206T230000
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DTSTAMP:20221011T223401Z
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DTSTART;TZID=America/Bogota:20221011T150000
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DESCRIPTION:The increasingly crowded spectrum has spurred the design of joi
 nt radar-communications systems that share hardware resources and efficien
 tly use the radio frequency spectrum. We study a general spectral coexiste
 nce scenario\, wherein the channels and transmit signals of both radar and
  communications systems are unknown at the receiver. In this dual-blind de
 convolution (DBD) problem\, a common receiver admits a multi-carrier wirel
 ess communications signal that is overlaid with the radar signal reflected
  off multiple targets. The communications and radar channels are represent
 ed by continuous-valued range-time and Doppler velocities of multiple tran
 smission paths and multiple targets. We exploit the sparsity of both chann
 els to solve the highly ill-posed DBD problem by casting it into a sum of 
 multivariate atomic norms (SoMAN) minimization. We devise a semidefinite p
 rogram to estimate the unknown target and communications parameters using 
 the theories of positive-hyperoctant trigonometric polynomials (PhTP). Our
  theoretical analyses show that the minimum number of samples required for
  perfect recovery scale logarithmically with the maximum of the radar targ
 ets and communications paths rather than their sum. We show that our SoMAN
  method and PhTP formulations are also applicable to more general scenario
 s such as unsynchronized transmission\, the presence of noise\, and multip
 le emitters. Numerical experiments demonstrate great performance enhanceme
 nts during the parameter recovery under different scenarios\n\nSpeaker(s):
  PhD(c) Edwin Vargas\, \n\nBucaramanga\, Santander\, Colombia\, 680002\, V
 irtual: https://events.vtools.ieee.org/m/324690
LOCATION:Bucaramanga\, Santander\, Colombia\, 680002\, Virtual: https://eve
 nts.vtools.ieee.org/m/324690
ORGANIZER:henarfu@uis.edu.co
SEQUENCE:3
SUMMARY:Dual-Blind Deconvolution for Overlaid Radar-Communications Systems
URL;VALUE=URI:https://events.vtools.ieee.org/m/324690
X-ALT-DESC:Description: <br /><p>The increasingly crowded spectrum has spur
 red the design of joint radar-communications systems that share hardware r
 esources and efficiently use the radio frequency spectrum. We study a gene
 ral spectral coexistence scenario\, wherein the channels and transmit sign
 als of both radar and communications systems are unknown at the receiver. 
 In this dual-blind deconvolution (DBD) problem\, a common receiver admits 
 a multi-carrier wireless communications signal that is overlaid with the r
 adar signal reflected off multiple targets. The communications and radar c
 hannels are represented by continuous-valued range-time and Doppler veloci
 ties of multiple transmission paths and multiple targets. We exploit the s
 parsity of both channels to solve the highly ill-posed DBD problem by cast
 ing it into a sum of multivariate atomic norms (SoMAN) minimization. We de
 vise a semidefinite program to estimate the unknown target and communicati
 ons parameters using the theories of positive-hyperoctant trigonometric po
 lynomials (PhTP). Our theoretical analyses show that the minimum number of
  samples required for perfect recovery scale logarithmically with the maxi
 mum of the radar targets and communications paths rather than their sum. W
 e show that our SoMAN method and PhTP formulations are also applicable to 
 more general scenarios such as unsynchronized transmission\, the presence 
 of noise\, and multiple emitters. Numerical experiments demonstrate great 
 performance enhancements during the parameter recovery under different sce
 narios</p>
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