| Wireless communication systems have evolved substantially over the last two decades. The explosive growth of the wireless communications market is expected to continue in the future, as the demand for all types of wireless services is increasing. Beside providing higher data rates, next generation wireless networks (NGWN) are expected to have advanced capabilities such as interoperability, efficient spectrum utilization along with a wide variety of applications over different domains (e.g., public safety and military, aeronautical networks, femtocells, and so on) to the mobile users while serving as many users as possible.;However, these advanced capabilities and services must be achieved under the constraint of limited available resources such as electromagnetic spectrum and power. In addition, NGWNs (and nodes within) need to modify themselves under rapidly changing conditions such as wireless propagation channel characteristics, traffic load, and so on. Moreover, NGWNs are expected to optimize their parameters by evaluating their experiences in the past. All of these characteristics imply that NGWNs should be equipped with cognitive capabilities including sensing, awareness, adaptation and responding to changing conditions along with learning about the past experiences.;In this dissertation, environment, channel, and interference awareness are investigated in detail for NGWN. Methods for being aware of environment, channel, and interference are provided along with some possible ways of adapting several design parameters of NGWNs. In addition, cross-layer optimization issues are addressed from the perspective of both recently emerging technology called cognitive radio (CR) and NGWN. |
