Data-Aided Channel Estimation in Large Antenna Systems

This paper is concerned with a uplink scheme for multicell large antenna systems. We study a channel estimation technique where partially decoded data is used to estimate the channel. We show that there are two types of interference components in this scheme that do not vanish even when the number of antennas grows to infinity. The first type, referred to as cross-contamination, is due to the correlation among the data signals from different users. The second type, referred to as self-contamination, is due to the dependency between the channel estimate and the estimation error. Cross contamination is in principle similar to pilot contamination in a conventional pilot-based channel estimation scheme, while self-contamination is unique for the data-aided scheme. For efficient use of the channel, the data part in a signaling frame is typically much longer than the pilot part for a practical system. Consequently, compared with pilot signals, data signals naturally have lower cross correlation. This fact reduces the cross-contamination effect in the data-aided scheme. Furthermore, self-contamination can be effectively suppressed by iterative processing. These results are confirmed by both analyses and simulations.