Channel Estimation Evaluation For a Massive MIMO System Considering Spatially Correlated Channels in an Urban Network

Abstract

Channel estimation (CE) is an important process that is done during the pilot transmission phase in each base station. This work addresses this process for the massive multiple-input multiple-output systems by studying the scenario where the channels are spatially correlated. Throughout this work, the spatial correlation between channels is modeled using the exponential correlation model. The minimum mean square error (MMSE) estimator’s performance for uncorrelated and correlated channels is compared and examined using the normalized mean square error (NMSE) metric, where the correlated scenario is presented through two array designs, namely proposed uniform planar array (UPA) and uniform linear array (ULA). In comparison to the uncorrelated situation, the correlated channels scenario is a more practical scenario that represents the real- world environment and provides superior channel estimate quality since the spatial correlation is advantageous for CE. Hence, we proposed a proposed UPA arrangement for correlated channels based on the Kronecker product of the ULA arrangement that outperforms the ULA arrangement and offers superior performance comparedto ULA. Numerical results are offered in order to support our analytical study.