Abstract
Application of the massive multiple-input multiple-output (MIMO) can significantly improve the capacity of the 5G wireless communications. However, for the high computational complexity and complicated spatial structures, channel estimation is a great challenge for the massive MIMO systems. The sparse array-structure-based millimeter wave (MmWave) massive MIMO physical channel model via the angle-of-departure (AoD), angle-of-arrival (AoA) and gains associated with different propagation paths is studied. For the existing partial convergence and discrete variable problem in angle domain channel estimation, Newton global optimization is adopted in this paper, the parameters of which is reconstructed to improve the searching performance and compute speed. The limit boundary searching for channel estimation accuracy is derived to make the proposed study complete. The simulation results are provided to demonstrate that the proposed scheme significantly outperforms the counterparts and can achieve accurate channel estimation performance.
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