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A Near-Optimal Iterative Linear Precoding With Low Complexity for Massive MIMO Systems
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DOI：10.1109/LCOMM.2019.2911472.png)
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Abstract
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The linear zero-forcing (ZF) precoding can achieve the near-optimal sum-rate performance when the favorable channel propagation is obtained in downlink massive multiple-input multiple-output (MIMO) systems. However, it involves high complexity with the matrix inversion. To significantly reduce the complexity of ZF precoding, we propose a weighted two-stage (WTS) precoding scheme with low complexity based on an iterative method. Specifically, the proposed WTS precoding converts the complicated matrix inversion into two-half iteration stages, and the result of each stage is weighted by a coefficient to further speed up the convergence and reduce the complexity. A theoretical analysis demonstrates that the proposed WTS precoding enjoys a fast convergence rate and low complexity. Simulation results indicate that the proposed WTS precoding can achieve better bit error rate (BER) and sum-rate performance with a smaller number of iterations than the recently proposed schemes.
Keywords:
Massive MIMO
precoding
low complexity
iteration method
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