Skip to main content

Optimal Power Allocation and Scheduling of Real-Time Data for Cognitive Radios


Abstract In this dissertation, I propose potential techniques to improve the quality-of-service (QoS) of real-time applications in cognitive radio (CR) systems. Unlike best-effort applications, real-time applications, such as audio and video, have a QoS that need to be met. There are two different frameworks that are used to study the QoS in the literature, namely, the average-delay and the hard-deadline frameworks. In the former, the scheduling algorithm has to guarantee that the packet's average delay is below a prespecified threshold while the latter imposes a hard deadline on each packet in the system. In this dissertation, I present joint power allocation and scheduling algorithms for each framework and show their applications in CR systems... (more)
Created Date 2016
Contributor Ewaisha, Ahmed (Author) / Tepedelenlioglu, Cihan (Advisor) / Ying, Lei (Committee member) / Bliss, Daniel (Committee member) / Kosut, Oliver (Committee member) / Arizona State University (Publisher)
Subject Electrical engineering / Cognitive Radios / Lyapunov Optimization / Power Allocation / Resource Allocation / Scheduling / Stochastic Optimization
Type Doctoral Dissertation
Extent 157 pages
Language English
Copyright
Reuse Permissions All Rights Reserved
Note Doctoral Dissertation Electrical Engineering 2016
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


  Full Text
1.1 MB application/pdf
Download Count: 371

Description Dissertation/Thesis