Comparative Performance Analysis of Channel Estimation Techniques for Massive MIMO System

The need for an internet connection is growing globally. So, day-by-day people need much higher data rate connection to meet their need but every physical resource in communication like frequency band, transmit signal strength are finite. Within the given limited resource, higher data speed is accomplished by a new technology called massive Multiple Input Multiple Output (massive MIMO) system. Massive MIMO fulfills the high data rate requirement through antenna diversity gain. It is one of the keys to guarantee 5G wireless network technology and it array antenna at both transmitter and receiver sides to providing high spectral and energy efficiencies. In massive MIMO, the signal obtained by the receiver is in different phase and amplitude from the transmission signal. Therefore, the system quality is tremendously depends on the accuracy of the channel estimation. Channel estimation plays a significant role in the performances of massive MIMO system because the dimension of the channels matrix is large, phase changes and noises are added when the signals pass through channel, these reduces the efficiencies of the whole system. To solve these problems, this paper focuses on the comparative analysis of pilot-based channel estimation schemes for massive MIMO system, which includes: Minimum Mean square Error (MMSE), Element Wise Minimum Mean Square Error (EW-MMSE), Maximum Likelihood (ML) and Least Square (LS) estimator with respect to Normalized Mean square Error (NMSE), Signal to Noise Ratio (SNR), number of BS antennas, and number of computational complexities.