| Wireless communication is one of the most active areas of technological innovations and groundbreaking research ranging from simple cellular phones to highly complex military monitoring devices. The emergence of radios with cognitive capabilities like software defined radios has revolutionized modern communication systems by providing transceivers which can vary their output waveforms as well as their demodulation methods. This adaptability plays a pivotal role in efficient utilization of radio spectrum in an intelligent way while simultaneously not interfering with other radio devices operating on the same frequency band. Thus, it is safe to say that current and future wireless systems and networks depend on their adaptation capability which in turn presents many new technical challenges in hardware and protocol design, power management, interference metrics, distributed algorithms, Quality of Service (QoS) requirements arid security issues. Transmitter adaptation methods have gained importance, and numerous transmitter optimization algorithms have been proposed in recent years. The main idea behind these algorithms is to optimize the transmitted signals according to the patterns of interference in the operating environment such that some specific criterion is optimized. In this context, the objective of this dissertation is to propose transmitter adaptation algorithms in conjunction with power control for wireless systems focusing on performance optimization based on operating constraints. Specifically, this dissertation achieves joint transmitter adaptation and power control in the uplink and downlink of wireless systems with applications to Multiple-Input-Multiple-Output (MIMO) wireless systems and cognitive radio networks. In addition, performance of the proposed algorithms are evaluated in the context of fading channels, taking into consideration the time-varying nature of wireless channels. |
