The Estimation Of MIMO Channel And Research Of Spatial Correlation

With the development of mobile communication, the demands for the limited frequency resource are booming. The major challenge in today's wireless communication is how to serve the explosively increasing demand of multimedia service within the limited bandwidth. Among those emerging technologies, multiple-input multiple-output (MIMO) communication architecture has showed its infinite potential to improve spectral efficiency dramatically. By deploying multiple antenna elements at both transmitter and receiver, MIMO has been regarded as an inevitable promising approach to exploit maximum spatial resources among many emerging technologies. It can enormously increase the wireless communication system capacity and the data rate without additional system bandwidth and transmitting power. The dissertation focuses on the MIMO channel estimation based on the superimposed(implicit) training and its spatial fading correlation. The main contents of the dissertation are expressed as follows:First we introduce the background and elements of MIMO techniques. Comparison is given between other techniques and MIMO wireless communications to demonstrate necessity and inevitability of research on MIMO. Then provide the problem to be resolved existing in MIMO communication in detail, pointing out the research direction of our work.Then we introduce the model of space time wireless channel and its characteristic such as doppler spread, which is the groundwork of the MIMO channel estimation in the next chapter. Chapter 3 mainly study the problem of MIMO channel estimation based on superimposed(implicit) training. In this chapter, the traditional channel estimation method is given first, then compared with the new estimation method based on superimposed(implicit) training and express the advantages of their own. In the last part of this chapter we combined the advantages of different method, made an improvement on channel estimation method based on the DFT of superimposed sequence. Our improved method was able to unaffected by unknown dc offset at the receiver while keep the same lower MSE compared the unimproved one. In chapter 4,we study the spatial correlation of MIMO subchannels and its affect on the diversity gain on condition that antenna array distribute in small scale, give a common way to analyze the problem based on the concept of power angle spectrum(PAS). Mainly compared the performance of the uniform circular array(UCA) and uniform linear array(ULA), Proved that the uniform circular array (UCA) provide a better diversity gain than uniform linear array(ULA) when more than two transmit antennas being used on condition that antenna array distribute in small scale and the power angle spectrum(PAS) distribute in uniform. In the last chapter, we summarize the previous work we have done and give a prospect of MIMO communication.