  This paper introduces the novel concept of proactive resource allocation
through which the predictability of user behavior is exploited to balance the
wireless traffic over time, and hence, significantly reduce the bandwidth
required to achieve a given blocking/outage probability. We start with a simple
model in which the smart wireless devices are assumed to predict the arrival of
new requests and submit them to the network T time slots in advance. Using
tools from large deviation theory, we quantify the resulting prediction
diversity gain} to establish that the decay rate of the outage event
probabilities increases with the prediction duration T. This model is then
generalized to incorporate the effect of the randomness in the prediction
look-ahead time T. Remarkably, we also show that, in the cognitive networking
scenario, the appropriate use of proactive resource allocation by the primary
users improves the diversity gain of the secondary network at no cost in the
primary network diversity. We also shed lights on multicasting with predictable
demands and show that the proactive multicast networks can achieve a
significantly higher diversity gain that scales super-linearly with T. Finally,
we conclude by a discussion of the new research questions posed under the
umbrella of the proposed proactive (non-causal) wireless networking framework.
