Non-Reciprocity Compensation For Time-varying TDD-MIMO Channel Using SVM Channel Prediction

Due to its significant gain in system spectral efficiency and capacity, MIMO technique has been one of the popular techniques for the next-generation wireless communication system. With the help of channel reciprocity, TDD-MIMO system can pre-process data at transmitter applying the channel state information (CSI) obtained by reverse-link estimation without additional feedback. Unfortunately, the channel reciprocity of time-varying channel would be destroyed.This thesis analyzes the impact of time-varying channel on channel reciprocity in TDD-MIMO communication systems. And then the least squares support vector machines (LS-SVM) based channel prediction method is proposed, to compensate non-reciprocity of time-varying TDD-MIMO channel. The main contributions are as follows:1 System capacity of TDD-MIMO system under time-varying environment is derived. Simulation results show that time-varying channel destroys the channel reciprocity and degrades the system capacity of TDD-MIMO systems.2 A new channel prediction method is proposed to compensate the channel non-reciprocity, which is based on LS-SVM. Simulation results show that, the channel reciprocity is compensated effectively and the system capacity can be significantly improved.3 The LS-SVM based prediction method aided by polynomial fitting is developed to compensate the channel non-reciprocity. Simulation results show that, compared to the method only using LS-SVM, this method can compensate the channel reciprocity in longer range.