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.