Channel Estimation Under Staggered Frame Structure for Massive MIMO System

In this paper, a staggered frame structure is proposed for single-cell massive multiple-input multiple-output (MIMO) systems, and the key idea is that different users transmit training pilots at nonoverlapped time. As a result, users do not have to be synchronized strictly to send pilots and orthogonal pilots are not required. Moreover, we also propose two interference suppressed channel estimation methods, i.e., the linear minimum mean square error (LMMSE)-based and orthogonal projection based least squares (OPLS) methods for the staggered frame structure. Specifically, the LMMSE-based method minimizes the mean square error of the estimation, whereas the OPLS method only estimates the part of the user's channel response that is orthogonal to the other users. All conducted simulation results demonstrate that the massive MIMO system with the both proposed methods can achieve high average achievable rate. Furthermore, when the conjugate beamforming is employed, the massive MIMO system could obtain even higher average achievable data rate with the proposed OPLS method than that of the system with perfect channel state information. Moreover, the computational complexity of the proposed OPLS method is very low.