In recent years, there has been an explosive increase in the number of mobile communication users. The realization of wireless communications including cellular phones, radio paging, and other portable communication technology requires high speed and high quality information exchange between mobile terminals located around the world. However, the interuser interference problem, which is one of the major drawbacks of multiple access systems reduces the system capacity and impairs the quality. To overcome such problems in mobile communications, more efficient signal processing techniques such as high resolution direction of arrival (DOA) estimation, appropriate vector channel modeling, and beamforming for wireless mobile communication environment are essential in the near future.
Estimation of unknown signal parameters with sensor array measurements has drawn much interest and been investigated quite extensively. In DOA estimation, if the locations of point sources are perturbed due to some reasons in a statistical way as in the environment of wireless mobile communications, a new model appropriate for such environment should be used instead of the point source model. In this dissertation, an angle-perturbed source model is proposed and an estimation method based on eigen-decomposition technique is investigated under the model. The asymptotic distributions of the estimation errors are considered to analyze the statistical properties.
There has been a rapid increase in the number of mobile users, making the multi-user interference problem more severe. To overcome this problem, application of adaptive antenna array techniques to additionally increase the channel capacity has been discussed. Antenna arrays can extract the desired signal waveform from all the received signals by properly weighted combining the outputs to suppress co-channel interference. To accomplish this, estimation of unknown signal parameters from sensor array measurements is necessary. In this...