Linear Precoding For Mimo Systems Based On Limited Feedback

It had been shown that the transmitters and receivers which have multiple antennas can obtain significant capacity gain with single antenna system. This gave us the information-theoretic foundation of MIMO system. The throughput and robust will be enhanced by the space diversity, which is introduced by MIMO system. In order to utilize the enhancement of spectrum efficiency brought by space multiplexing, precoding has been used widely as a trade-off between diversity and multiplexing. But precoding can't be used best without the Channel State Information of the Transmitter, so how to obtain this CSIT is very important. That takes us to do research on the linear precoding in MIMO system based on limited feedback in this thesis. In this thesis we first show the importance of CSIT for the capacity enhancement in MIMO system, so precoding with CSIT is the direction of our research. A new problem comes out: how to obtain CSIT. In most communication system today, the reciprocity of channel is difficult to realize, for example, the FDD system. So if we want to get CSIT at the transmitter, we should make use of feedback. However, feeding back the perfect CSIT is not realizable in real communication system, for this take too much resource of the reverse link. So the limited feedback should be use to solve this problem that how to obtain CSIT. In this thesis, we introduced some important methods for precoding in MIMO system. Then we focus on a typical limited feedback based linear precoding scheme-Grassmann manifold codebook based linear precoding. We start from the precoding selection criterion, established a mathematic model in Grassmann manifold, and solve the problem of how to design the codebook. We give a detail description for theoretical basis of this scheme, and do a comparison and analysis for different factors'effect on the performance through simulations.The impact of feedback on reverse link can not be ignored. So we also focus on how to reduce the num of feedback without any decrease on system performance. We use another mathematic tool-subspace tracking to solve this problem. We also establish a mathematic model in Grassmann manifold, but different from the codebook scheme, we analysis the generation of precoding matrix in another way, then we do some simulations and comparison analysis for this scheme.After the above description and analysis, we propose a new linear precoding scheme that can adapt the amount of feedback according to the time-variation property of channel. In this scheme, we combine the codebook and subspace tracking in Grassmann manifold, and get a optimal precoding matrix to send back to the transmitter, in which the amount of feedback is reduced and the impact to reverse link decrease. Simulation results show this conclusion, and the analysis was given.At the end of the thesis, we summarize the whole research and give some advice for the future research.