The Feasibility of Scalable Video Streaming over Femtocell Networks

TL;DR

This paper explores scalable video streaming over femtocell cognitive radio networks, proposing algorithms for different scenarios and analyzing their performance bounds to improve network efficiency.

Contribution

It introduces a unified framework for scalable video streaming in femtocell CR networks, with optimal and near-optimal algorithms for various interference scenarios.

Findings

Optimal distributed algorithm for single femtocell case

Near-optimal greedy algorithm for interfering femtocells

Performance bounds established for proposed algorithms

Abstract

In this paper, we consider femtocell CR networks, where femto base stations (FBS) are deployed to greatly improve network coverage and capacity. We investigate the problem of generic data multicast in femtocell networks. We reformulate the resulting MINLP problem into a simpler form, and derive upper and lower performance bounds. Then we consider three typical connection scenarios in the femtocell network, and develop optimal and near-optimal algorithms for the three scenarios. Second, we tackle the problem of streaming scalable videos in femtocell CR networks. A framework is developed to 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-opitmal solutions, and prove a closed-form lower bound on its performance.