Abstract

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.

Highlights

  • Massive MIMO, which is a system where base stations with a large number of antennas and tens of single-antenna user terminals (UT) deployed in each cell, has attracted attentions for its high spectrum efficiency [1]

  • We propose an estimation algorithm based on the weighted total least-squares method with errors-invariables (EIV) model to alleviate the influence of pilot contamination and channel aging

  • In [7], an iterative least square projection (ILSP) method based on diagonal Jacket matrix is proposed to resolve the effects of pilot contamination as diagonal Jacket matrix has many advantages such as reducing the computational complexity and an energy harvest

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Summary

Introduction

Massive MIMO, which is a system where base stations with a large number of antennas and tens of single-antenna user terminals (UT) deployed in each cell, has attracted attentions for its high spectrum efficiency [1]. As time goes by, the channel varies, and it is different from the estimated state This phenomenon is the so-called channel aging. In [7], an iterative least square projection (ILSP) method based on diagonal Jacket matrix is proposed to resolve the effects of pilot contamination as diagonal Jacket matrix has many advantages such as reducing the computational complexity and an energy harvest. Less work has been done to solve the problem of channel aging and pilot contamination jointly. The effects of channel aging and pilot contamination are Mathematical Problems in Engineering. The channel estimate error that is caused by channel aging and pilot contamination can be derived. The effects of channel aging and pilot contamination, which are inherent in Massive MIMO system, can be eliminated jointly with the proposed algorithm. E[] is the expectation operation and “⊗” is the Kronecker product of two matrices

System Model
Weighted Total Least-Squares Algorithm for Signal Estimation
Simulation
Conclusion

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