Uplink Channel Estimation Of Massive MIMO In TDD System

In modern communication systems, we use multiple input multiple output (MIMO)technology to increase the achievable rate and reliability，according to its transmitdiversity and spatial multiplexing. In order to achieve higher transmitting rate andreliability, more antennas equipped with transmitter or receiver is one of the best ways.Therefore, Massive MIMO is proposed by Thomas L. Marzetta in2008.Massive MIMO use antenna arrays with a few hundred antennas, whichsimultaneously serve many tens of terminals in the same time-frequency resource block.In order to keep the signal detection and precoding possible, channel impulse response(CIR) estimation is essential in Massive MIMO system. Hence, this paper focuses onthe channel estimation of Massive MIMO.In this paper, Massive MIMO technology is introduced and analyzed firstly. Then,pilot contamination is analyzed because of its impact on the performance of MassiveMIMO. Under the pilot contamination situation, pilot shifted channel estimator andBayesian channel estimator, which is based on the second order statistics of CIR, areprovided in this paper. These two methods are effective in avoiding the interference ofpilot contamination. Finally, this paper provides two channel estimators which areconnected with signal detection algorithms. The first estimator is based on eigenvaluedecomposition (EVD) of covariance matrix of receiving signal, and the detectionalgorithm is iterative least squares with projection (ILSP). The second channel estimatoris connected with randomized Markov chain Monte Carlo (RMCMC) detectionalgorithm, and the channel estimation is based on MCMC sampling method. In oursimulation results, these two estimators can improve the accuracy of initial channelestimation.