Atomic fragmentation for efficient opportunistic multicasting over cognitive radio networks

Abstract

Cognitive radio (CR) represents an exciting new paradigm on spectrum utilization and potentially more bandwidth for exploding multimedia traffic and this potential can be further boosted by utilizing well established opportunistic multicasting principles. We focus on the layer encoded video multicast problem in a dynamic CR network. We contribute a data fragmentation mechanism, that fragments data into atomic units, combined with rateless code forward error control (FEC) protection, which enable maximum resource utilization. The resulting zero wasting scheduling scheme enables performance improvement that is showcased by simulation results.