By Topic

On Medium Grain Scalable Video Streaming over Femtocell Cognitive Radio Networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Donglin Hu ; Dept. of Electr. & Comput. Eng., Auburn Univ., Auburn, AL, USA ; Shiwen Mao

Femtocells are shown highly effective on improving network coverage and capacity by bringing base stations closer to mobile users. In this paper, we investigate the problem of streaming scalable videos in femtocell cognitive radio (CR) networks. This is a challenging problem due to the stringent QoS requirements of real-time videos and the new dimensions of network dynamics and uncertainties in CR networks. We develop a framework that captures the key design issues and trade-offs with a stochastic programming problem formulation. In the case of a single FBS, we develop an optimum-achieving distributed algorithm, which is shown also optimal for the case of multiple non-interfering FBS's. In the case of interfering FBS's, we develop a greedy algorithm that can compute near-optimal solutions, and prove a closed-form lower bound on its performance. The proposed algorithms are evaluated with simulations, and are shown to outperform three alternative schemes with considerable margins.

Published in:

Selected Areas in Communications, IEEE Journal on  (Volume:30 ,  Issue: 3 )