Adaptive Pilot Pattern for Massive MIMO Systems

Abstract

This work proposes a new adaptive pilot pattern used for pilot arrangement at the mobile station and a new channel estimation at the base station. It addresses the bit error rate (BER) performance optimization of wireless channel estimation in massive multiple-input multiple-output systems. First, we propose a new adaptive pilot pattern (APP) that offers a lower BER than the conventional pilot patterns. Then, we suggest a new channel estimation algorithm based on the APP. It is called the shifted APP-channel estimation (SACE). As a result, APP guarantees an optimal BER performance for the different system configurations, channel models, and carrier frequencies. It offers better BER performance than conventional pilot patterns, such as the long-term evolution (LTE) pilot pattern. Moreover, the shifted APP-based channel estimation algorithm solves the error floor caused by the usage of multiple subcarriers. It also offers a signal-to-noise ratio (SNR) improvement that reaches 17 dB at BER $= 10^{-2}$ compared to the conventional minimum mean square error (MMSE) channel estimation.

Keywords

• Channel estimation
• massive MIMO
• pilot overhead
• pilot pattern