Adaptive network coding over cognitive relay networks

We consider network coded cooperation for cognitive relay networks. The primary system comprises multiple sources and multiple destinations, whereas the secondary system comprises multiple sources, multiple relays and a single destination. We derive a closed form expression for the end-to-end outage probability for the secondary system while assuming the presence of interference constraints between the two sub-systems. Based on the diversity order analysis, we propose a framework for adaptive network coding. The proposed scheme involves using a small encoding set size for low link quality and a large encoding set for good link quality. Having a small set size increases the probability of having relay cooperation, which comes at the expense of some loss in coding gain, whereas using a large encoding set size decreases the probability of having relay cooperation, but achieves some network coding gains. Therefore, there is a fundamental trade-off between the probability of relay cooperation and the achievable network coding gains. Using numerical results, we show that the proposed adaptive network coding achieves up to 5 dB gain at target outage 10^-3 as compared to conventional fixed network coding schemes.