Proactive multicasting with predictable demands

In a recent work, we have introduced the notion of proactive resource allocation in wireless networks whereby the predictability of user demands are leveraged to significantly enhance the spectral efficiency of the network in outage limited regimes. In this paper, we expand the horizon to the important scenario of multicast traffic. Our analysis reveals two additional types of gains that can be leveraged in this proactive multicast scenario. The first can be attributed to the basic nature of multicast traffic in which each request would represent a data source rather than a user, as it would in the unicast case. The second is the demand alignment phenomenon whereby the predictive network would wait to gather as much requests as possible and serve them altogether using the same resources. We analytically derive the impact of these advantages on the system diversity gain, which quantifies the exponential decay rate of the outage probability, and further illustrate the resulting gains via numerical results.