Skip navigation
  • Home
  • Browse
    • Communities
      & Collections
    • Browse Items by:
    • Publication Date
    • Author
    • Title
    • Subject
    • Department
  • Sign on to:
    • My MacSphere
    • Receive email
      updates
    • Edit Profile


McMaster University Home Page
  1. MacSphere
  2. Open Access Dissertations and Theses Community
  3. Open Access Dissertations and Theses
Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/16273
Full metadata record
DC FieldValueLanguage
dc.contributor.advisorChen, Jun-
dc.contributor.authorKhezeli, Kia-
dc.date.accessioned2014-10-31T19:53:09Z-
dc.date.available2014-10-31T19:53:09Z-
dc.date.issued2014-11-
dc.identifier.urihttp://hdl.handle.net/11375/16273-
dc.description.abstractA converse method is developed for the source broadcast problem. Specifically, it is shown that the separation architecture is optimal for a variant of the source broadcast problem and the associated source-channel separation theorem can be leveraged, via a reduction argument, to establish a necessary condition for the original problem, which uni es several existing results in the literature. Somewhat surprisingly, this method, albeit based on the source-channel separation theorem, can be used to prove the optimality of non-separation based schemes and determine the performance limits in certain scenarios where the separation architecture is suboptimal.en_US
dc.language.isoen_USen_US
dc.subjectNetwork Information Theoryen_US
dc.subjectBroadcast Channelsen_US
dc.subjectJoint Source Channel Codingen_US
dc.subjectGaussian Broadcast Channelen_US
dc.subjectSeparation Theoremen_US
dc.subjectSide Informationen_US
dc.titleA Source-Channel Separation Theorem with Application to the Source Broadcast Problemen_US
dc.typeThesisen_US
dc.contributor.departmentElectrical and Computer Engineeringen_US
dc.description.degreetypeThesisen_US
dc.description.degreeMaster of Applied Science (MASc)en_US
Appears in Collections:Open Access Dissertations and Theses

Files in This Item:
File Description SizeFormat 
thesis.pdf
Open Access
Main article 509.53 kBAdobe PDFView/Open
Show simple item record Statistics


Items in MacSphere are protected by copyright, with all rights reserved, unless otherwise indicated.

Sherman Centre for Digital Scholarship     McMaster University Libraries
©2022 McMaster University, 1280 Main Street West, Hamilton, Ontario L8S 4L8 | 905-525-9140 | Contact Us | Terms of Use & Privacy Policy | Feedback

Report Accessibility Issue