Research On Key Technologies For Software Antenna

With the development of wireless communication industry, wireless data traffic is increasing quickly. How to transfer more date by limited bandwidth is at the center of concern in wireless communication field. Software antenna technology can increase capacity of wireless communication system greatly without extra bandwidth. Thus, it is a next generation wireless technology with bright prospect. Different with smart antenna that employ fixed beam forming algorithm, software antenna can configure its beamforming algorithm automatically according to different circumstance. There are mainly three classes of beamforming algorithms. They are direction of arrival based beamforming (DOB) algorithm, temporal reference beamforming (TRB) algorithm and signal structure based beamforming (SSBF) algorithm. Different beamforming algorithm has different performance under different circumstance. Some algorithms even fail to work under specific circumstance. Different algorithms are stored as software in software antenna system. Software antenna can achieve optimal performance by invoking the best performance algorithm under different circumstance. It has the merit of smart antenna and can greatly avoid shortcomings of smart antenna. The software antenna technology is in its infant stage and there are still many key technologies to be study. The key technologies to build software antenna system include beamforming algorithm classification and selection strategy, environment identification and classification methods. This dissertation focuses on key technology of software antenna. The main work as followings: This dissertation investigated about the radio transmission model. The radio transmission environment is very complex in mobile communication. This dissertation researched various radio transmission phenomena and typical microcell and macrocell models and simulated the base station's transmission environment of macrocell. Performance of Different beamforming algorithm was compared under different radio environment. DOB and TRB algorithms were simulated. The numeric simulation results illustrate that DOB algorithms'performance is greatly affected by space-spread environment and TRB algorithms are sensitive to training signal restoration. Based on the result of comparison, a strategy for algorithm selection was proposed. The environment classification and identification are the foundation of algorithm selection. This dissertation proposed an improved MUSIC algorithm to identify environment. Numeric calculation result shows that the proposed algorithm can't only retrieve the space character of signal channel but also the time character of signal channel. Signals that received by antenna array have linear structure. Signals can be identified blindly by employ linear structure of signals. This dissertation proposed a new environment identification algorithm by employ blind signal identification technology. This algorithm can identify several users with different channel order simultaneously and retrieve channel's space character and time character of each user. Direction of arrival (DOA) calculation is important for DOB algorithms. This dissertation discussed several DOA algorithms and studies the agents that affect MUSIC algorithm's precision. The error of antenna array affect the performance of subspace based DOA algorithm and beamforming algorithm. Those algorithms even can't work because of the error. This dissertation set up mathematic models for coupling error, position error and gain error. A subspace algorithm was proposed according to the character of position error. Its precision can full fill the requirement of subspace based DOA algorithms. This dissertation also discussed the correction algorithm of mutual coupling error. To avoid the bad effect of mutual coupling error for MVDR beamforming, an improved MVDR algorithm was proposed. The beamforming algorithm classification and selection strategy, the environment identification method and the array correction algorithm are helpful for the realization of smart antenna.