Efficient Performance Bound for Channel Estimation in Massive MIMO Receiver

Abstract

In this paper, we present a new performance bound for uplink channel estimation (CE) accuracy in the Massive Multiple Input Multiple Output (MIMO) system. The proposed approach is based on noise power calculation after the CE unit in a multi-antenna receiver. We decompose a non-line of sight (NLOS) channel into separate taps and calculate the cross-covariance matrix between them. Then a linear minimum mean squared error (MMSE) method is applied with these taps to estimate residual CE error value for each unique scenario, assuming Gaussian distribution of tap amplitudes and antenna noise. An artificial CE is calculated as a sum of the ideal noiseless channel (pre-defined Quadriga model) and the leftover noise after the optimal estimate. The artificial CE is then utilized in the MIMO detector and decoder units to calculate performance bound. Our method outperforms the accuracy of a well-known Cramer-Rao lower bound (CRLB) due to considering more statistics (number of taps and correlation between them) since performance strongly depends on several channel taps and their power ratio. Additionally, we show that our bound can be obtained from the generalized Bayesian CRLB. Simulation results are presented for the 5G QuaDRiGa 2.0 NLOS channel.