Social-based Broadcast in Cognitive Radio Networks: A Network Coding Perspective

Cognitive radio (CR) is a promising technology to improve spectrum utilization. However, spectrum availability is uncertain which mainly depends on primary user's (PU's) behaviors. Broadcast is the most basic way to disseminate data from one source node to all the others in multi-channel cognitive radio networks (CRNs), and the retransmission can be a vital factor for improving broadcast performance. Existing works fail to exploit the unique characteristic of reliable broadcast or the broadcast nature of wireless links, which will lead to redundant transmissions and broadcast performance degradation. In this paper, we propose a social-based scheme for network coding based broadcast in CRNs, in which the source node combines all lost packets into a single one for retransmission by random linear network coding (RLNC), considering channel assignment in CRNs. We evaluate and compare the proposed scheme against other traditional retransmission mechanism with channel assignment. It is shown that the proposed scheme, by integrating social feature with network coding can obtain much better results, with respect to the average number of transmissions per packet.