A pilot aided channel estimator using DFT based time interpolator for massive MIMO-OFDM systems

Massive multi input multi output orthogonal frequency division multiplexing (MIMO-OFDM) systems are progressively improving the current wireless communication standards towards 5G, due to their high data rates. The channel estimator (CE) employed in these systems is based on 2D-grid type pilot arrangement, which offers better spectral efficiency. The 2D arrangement requires the CE to incorporate a time interpolator (TI) in addition to the usual frequency interpolator (FI). The prime concerns for a TI in massive systems are minimal storage, low computational complexity, and system reliability. The existing low-pass FI or a linear FI can serve as TI; however, each of them does not address all the prime concerns in totality. In this paper, a discrete Fourier transform (DFT) based TI is introduced with three distinguished features; minimum storage space similar to a linear TI, computational complexity at par with linear TI, and improved system reliability compared to low-pass TI. Using system bit error rate (BER) simulations in various Rayleigh fading channels characterized by U-shaped Doppler spectrum, it is verified that the proposed CE incorporating the DFT-based TI indeed provides better system reliability with minimal storage and low computational complexity.