Pilot contamination mitigation by pilot assignment and adaptive linear precoding for massive MIMO multi-cell systems

According to research, the performance of the massive MIMO system is constrained by pilot contamination. Recent developments in massive MIMO provide a variety of methods for the reduction of pilot contamination with diverse performances. There is a trade-off between the complexity of the system, the time-frequency resources needed to estimate the channel, and the effectiveness of pilot contamination mitigation. Limited research exists on the analysis of the combined effect of the three parameters, despite the impact of the parameters on the performance of massive MIMO multi-cell networks. Therefore, in this research, an algorithm consisting of a combined adaptive linear precoding and pilot assignment methods was designed for the reduction of pilot contamination in the massive MIMO multi-cellular network. The Maximum ratio Transmission (MRT) and Zero Forcing (ZF) precoding schemes were incorporated in the algorithm to diminish interfering signals from other cells while amplifying the intended signal, to improve the BER at low computational complexity. Pilot assignment methods of frequency reuse and the Zadoff-Chu sequence facilitated the optimal allocation of resources and reduced interference to improve spectral efficiency. The pilot assignment method ensures an optimal number of pilots are assigned to guarantee the efficient use of resources while precoding schemes eliminate interference. The effectiveness of the proposed algorithm was evaluated based on the ability to reduce BER, increase spectral efficiency, and reduce computational complexity. The results show improved performance of the proposed algorithm, compared to the conventional MRT and ZF precoders. Accordingly, this study contributes to the investigation of the impact of integrating adaptive linear precoding and pilot assignment methods for pilot contamination mitigation in massive MIMO systems.