| Description |
The rapid evolution of digital communication has enabled the realization of technologies that were little more than science fiction less than three decades ago. Ever increasing data rates and wireless capabilities have created instant access to virtually unlimited information for more than half of the world's population. The soon to be realized 5G network promises more than just ultra reliable and ultra fast data rates; various physical devices will soon be able to communicate with one another to improve the economic, social, and environmental well-being of citizens. One of the most glaring problems to solve with this exciting prospect, however, is the scarcity of spectrum available to support the massive increase in communicating devices. In order to coordinate the spectral resources and improve spectral efficiency, waveforms that transmit below other users in a network are a necessity. The so-called \underlay waveforms" must be robust to other users' interference while mitigating their own interference characteristic on other users, making spread spectrum waveforms the obvious choice. The bottleneck hindering their utilization and performance is the ability to correctly detect and time-align to the desired transmissions in this harsh environment. The focus of this dissertation is to develop algorithms that focus on and improve the packet detection and timing acquisition (PD/TA) of spread spectrum communications as an underlay waveform. Specifically, this dissertation makes two major contributions: (i) the proposal of a novel PD/TA algorithm that operates without the necessity of estimating noise parameters; (ii) a proposed modification to the standard matched filter (SMF) that suppresses partial-band interference without explicit knowledge of the interferers' location. The combination of these two contributions has yielded a powerful PD/TA technique that provides profoundly reliable results in the harsh environments of interest. |
