Reduction Pilot Contamination in Downlink Multi-Cell for Massive MIMO Systems

Massive multiple- input–multiple- output has become an important fifth-generation (5G) wireless communication system because it improves transmitted spectral efficiency. In this paper, we obtained the maximal spectral efficiency by improving transmission performance in cell edges. This was achieved by using pilot reuse sequences from all available pilots in order to mitigate the pilot contamination and to suppress interference between adjacent cells. In addition, we investigated the impacts of pilot contamination on the received signal-to-interference-noise ratios (SINR) of users and employed different pilot reuse. We propose a new method called cell-edge-aware maximum ratio transmission (MRT), zero forcing (ZF), and return zero forcing (R-ZF). These were the precoders that employed less spatial dimensions and were able to suppress adjacent cells interference of the maximally vulnerable active user. We conclude that the large pilot reuse value between neighboring cells increased the gain, avoided interference between adjacent cells, and gave the maximal spectral efficiency. Consequently, the R-ZF was better than ZF and MRT because it was able to suppress the SINR

Channel Rectification and Signal Estimation Based on EIV Model in Massive MIMO System

The performance of Massive MIMO is severely limited by channel estimation error, which is caused by pilot contamination and channel aging. In this paper, we propose an estimation algorithm based on the weighted total least-squares method with errors-in-variables (EIV) model to alleviate the influence of pilot contamination and channel aging. Then, a channel rectification method has been investigated to diminish the inaccuracy of channel estimation. Comparing with the traditional methods, it not only helps to make the signal estimation more accurate, but also provides opportunities to correct the channel model with estimation error and update the aged channel statement information. Simulations are provided to verify the efficacy of this method

Effect of pilot contamination on channel estimation in massive MIMO systems

In this paper, we consider the uplink transmission in Massive MIMO systems with OFDM over frequency selective channels. Channel state information (CSI) is essential for exploiting the potential benefits of such systems. So far, few researches have addressed the effect of pilot contamination (PC) on channel estimation. In this paper, analytical expressions on the mean square error (MSE) of two classical channel estimation algorithms in the presence of PC are presented. It is shown that minimum mean square error (MMSE) is more resistant to PC compared to least square (LS). Increasing the number of pilot subcarriers, for both algorithms, does not contribute to better suppression to PC. However, from the results given herein, a clue for mitigating PC can be obtained. The performance of LS and MMSE algorithms in the presence of PC could be improved as the increase in the length of channel impulse response (CIR) and OFDM subcarriers, respectively