Water occupies three fourth of earth's surface. The remaining one fourth is land. Although human habitats reside on land, there is no denying of the vital connection between land and water. The future sustainability of human species on this planet depends on wise utilization of all available resources, including that provided by the vast water world. Therefore, it is imperative to explore, understand, and define this massive, varying, and in many areas, unexplored water domain. The water domain exploration and data collection can be conducted using manned or unmanned vehicles, as allowed by the water environment. This dissertation addresses three of the key difficulties that occur during underwater acoustic communication among manned and/or unmanned vehicles and proposes feasible solutions to resolve those difficulties. The focus and the contributions of this research involve the following perspectives: 1) Representation of Underwater Acoustic Communication (UAC) Channels: Providing a comprehensive classification and representation of the underwater acoustic communication channel based on the channel environment. 2) Estimation and Compensation of Doppler Shift: Providing compensation algorithm to mitigate varying Doppler shift effect over subcarriers in UAC Orthogonal Frequency Division Multiplexing (OFDM) systems. 3) Mitigation of Inter-symbol Interference (ISI): Providing feasible solution to long delay spread causing ISI in Ultra-wideband channels.

The area of wireless transceiver design is becoming increasingly important due to the rapid growth of wireless communications market as well as diversified design specifications. Research efforts in this area concentrates on schemes that are capable of increasing the system capacity, providing reconfigurability/reprogrammability and reducing the hardware complexity. Emerging topics related to these goals include Software Defined Radio, Multiple-Input-Multiple-Output (MIMO) Systems, Code Division Multiple Access, Ultra-Wideband Systems, etc. This research adopts space diversity and statistical signal processing for digital interference suppression in wireless receivers. The technique simplifies the analog front-end by eliminating the anti-aliasing filters and relaxing the requirements for IF bandpass filters and A/D converters. Like MIMO systems, multiple antenna elements are used for increased frequency reuse. The suppression of both image signal and Co-Channel Interference (CCI) are performed in DSP simultaneously. The signal-processing algorithm used is Independent Component Analysis (ICA). Specifically, the fixed-point Fast-ICA is adopted in the case of static or slow time varying channel conditions. In highly dynamic environment that is typically encountered in cellular mobile communications, a novel ICA algorithm, OBAI-ICA, is developed, which outperforms Fast-ICA for both linear and abrupt time variations. Several practical implementation issues are also considered, such as the effect of finite arithmetic and the possibility of reducing the number of antennas.