Principles of Proactive Resource Allocation in Wireless Communication Networks

The excessively growing demand on the wireless data services has raised major concerns of a potential degradation, if not a total collapse, of satisfactory mobile communications. On the other hand, the available spectrum for wireless communications has been reported to suffer from a daily underutilization problem that lasts from midnight to early morning hours. Such a discrepancy between the wireless traffic levels over the course of the day is essentially tied to the human activity patterns, whereby end users exhibit high demand characteristics during the day time creating the so-called peak hour load, and concurrently idle at the late night time yielding substantially low demand and the so-called off-peak hour load. Major research efforts have been exerted over the past few years to develop a radical remedy to such a problem threatening the future of high-quality wireless communications. However, almost all of the emerging solutions, including cognitive radio communications, time-dependent pricing, and WiFi offloading, rely on influencing the economical responsiveness of wireless users to delay their demand from the peak to the off-peak time. The resulting gains of these proposed solutions hinge on the tradeoff between the offered pricing incentives and the flexibility of the users to change their activity patterns. In this dissertation we bring to attention an unexploited degree of freedom in the realm of wireless resource allocation. That is, the human behavior is highly predictable. Motivated by the recent findings that affirm this observation, we propose