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Massive MIMO system has been designed to enhance the capacity, data rate, spectral efficiency and maximal energy efficiency as well as system sensitivity towards propagation environment which meets demand of future wireless communication. Using an asymptotic argument of random matrix theory, linear signal processing can be used to achieve the optimal performance of the massive MIMO. So what are the optimal numbers of antennas, actives users, and power transmitted in system? Is the one fundamental question needed to be answered? In this work we described the effect of these parameters using Ergodic achievable rate and energy efficiency by applying linear signal processing; particularly we have used zero-forcing (ZF), and maximum ratio combining or maximum transmission (MRC/MRT) algorithms. We also used minimum mean square error (MMSE) to estimate the CSI. In the context the major problem that encounters the implementation of massive MIMO multi-cell time division duplexing (TDD) network system is called pilot contamination due to limitations of coherence time. In this paper, massive MIMO along with linear precoding algorithms and pilot contamination are described and also included source and possible solutions of this problem and we found that, contrary to MRC/MRT algorithms, ZF can be used to get an optimal performance of massive when the K is equal to or less than BS antennas. Keywords— Massive MIMO, pilot contamination linear precoding, channel state information (CSI), single-cell, multi-cell, Ergodic achievable rate, energy efficiency (EE).

Analysis of Precoding Algorithms and Pilot Contamination Problem for Massive MIMO System