Pilot optimization in multicell massive MIMO

Mohammed A. Teeti, Rui Wang, Yingzhuang Liu, Qiang Ni

Abstract: In this paper we consider pilot contamination problem in the uplink of a multi-cell massive MIMO. Each base station (BS) is equipped with M (unlimited) antennas serving K (large but finite) users. Further, we let τ (pilot length) be an arbitrary but small value. As such, pilot optimization is formulated as a multi-objective optimization problem (MOP). It is shown that, when power control is enabled, maximally spaced sequences solve a worst-case signal-to-interference (SIR) problem only under a special channel case, whereas the general channel case doesn't admit a simple solution. Motivated by the epsilon-constraint technique in MOP, we propose a low-complexity algorithm for optimizing pilots of different users from a fixed orthonormal basis in an iterative manner. For only a few iterations, the algorithm shows good convergence property, which is supposed to converge to a Pareto-optimal solution. The numerical results show that the algorithm gives rise to a significant improvement of the cell throughput as well as the per-user mean SIR and per-user mean rate.