Research On Smart Antenna And Space-time Coding Technologies For Modern Mobile Communication Systems

In modern mobile communications, the performance of communication systems is severely limited by the fading effect of wireless channel, so how to overcome the channel fading and improve the system spectrum efficiency and data rate becomes a very important research topic. Multiple-antenna technique has received wide interest in recent years due to its high data rate, high spectrum efficiency, strong abilities of suppressing the interference and increasing the system capacity and so on. In this dissertation, we focus on the research about the applications of multiple-antenna technique in modern mobile communications, and the main contents include smart antenna technique and space-time coding technique.This dissertation is divided into seven chapters. Chapter 1 introduces the research background and the main works of this dissertation; the research status of multiple-antenna technique in mobile communications is also reviewed in this chapter. In chapter 2, on the basis of introducing the mobile channel characteristics, the channel model and capacity of MIMO system, the basic knowledge about the smart antenna technique, spatial receiver diversity technique, space-time coding technique and spatial duplexing technique are given.Chapter 3 investigates forward link beamforming for smart antenna system. A simple and effective beamforming algorithm for CDMA/TDD system is proposed. The algorithm, based on maximizing received signal power criteria, obtains beamformer weight vector by calculating largest eigenvalue and corresponding eigenvector of spatial channel covariance matrix form desired user. It has low complexity and high reliability. Considering that the above algorithm doesn't adapt to FDD mode, two forward link beamforming algorithms for FDD are proposed. The first one is based on the short-time average channel fading altitude feedback, which feeds back the short-time average channel fading altitude from the mobile, estimates the DOA of the inverse link in terms of inverse link channel covariance matrix, then computes the array vector, and uses the short-term average channel fading altitude and array vector to compute forward link channel covariance matrix to perform forward link beamforming. The second one is based on linear prediction method by using the instantaneous channel fading altitude feedback, which feeds back the parameter of each path with the aid of the Rake receiver of the mobile, and the linear prediction is employed to predict the present channel fading parameter. Then the DOA is estimated in terms of inverse link channel covariance matrix; and the channel covariance matrix of the desired signal is obtained. Finally, by calculating the eigenvector corresponding to the largest eigenvalue of channel matrix, the beamformer weight vector is got. The algorithm 1 is suitable for channel with slow changes, while the algorithm 2 is suitable for channel with fast changes.