Interference is a major problem in modern wireless communications systems. No longer are background noise and average power loss the limiting factors in system capacity corruption of the available spectrum by multiple access and nearby interference provides the upper limit to system capacity. If the exponential growth of commercial wireless communications is to continue, systems must effectively deal with the increasingly crowded and corrupted spectrum. Direct Sequence Spread Spectrum modulation (DS-SS) combined with Time Dependent Processing represents a valid approach to meeting the needs of future communications systems. Traditionally, the exploitation of cyclostationarity in digital communications signals has been reserved for the hostile communication environments faced by the military. However, the advent of cost-effective, high-speed DSP chips and associated processing hardware have made Time Dependent Processing a viable commercial technology. This thesis presents several forms of the Time Dependent Adaptive Filter (TDAF) which are able to fully exploit the cyclostationarity and high degree of spectral correlation in certain DS-SS signals. It is shown that these optimal TDAFs are able to combat interference from noise, multipath, signals with dissimilar modulation, and signals with similar modulation (multiple access interference). Performance gains are achieved without a knowledge of the specific type of interference and depend solely on the high degree of spectral correlation in DS-SS signals. It is shown that properly designed DS-SS CDMA systems that utilize the TDAF can achieve spectral efficiencies which are within 10% of FDM/TDM systems. Furthermore, these systems retain the benefits of wideband modulation and universal frequency reuse traditionally associated with CDMA systems. The net result is a tremendous increase in system user capacity and signal reception quality. / Master of Science