Effect of Gaussian Correlated Channel on Uplink Channel Estimation for Massive MIMO with Nested Array at the Base Station

2020 National Conference on Communications (NCC) Pub Date : 2020-02-01 DOI:10.1109/NCC48643.2020.9055992

Md. Afaque Azam, A. Mukherjee, A. Dutta

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引用次数: 1

Abstract

mmWave massive MIMO can support high data rate on account of enhanced spectral efficiency. Uplink channel estimation is an important intermediate problem. Usually channels between the base station and the user equipment is assumed IID, Rayleigh and flat fading. However, the antennas are closely packed together in a massive MIMO and local scatterers are present around the user equipment. This means that a correlated channel model is more realistic. In this paper, a Gaussian one ring scattering model for the channel is used. The uplink Linear Minimum Mean Square Error (LMMSE) channel estimator performance is analyzed, with a pilot reuse factor of L > 1. The upper limit of the estimation performance for varying degrees of correlation and pilot length is derived and verified by numerical experiments. In place of usual dense uniform linear array, a sparse nested array is employed at the base station. It is verified experimentally that the sparse array performs better when the channels are highly correlated. However, both arrays showed similar performance for the usual IID case when the correlation is small ((σφ>> 0.5).

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高斯相关信道对基地台嵌套阵列大规模MIMO上行信道估计的影响

毫米波大规模MIMO技术由于提高了频谱效率，可以支持高数据速率。上行信道估计是一个重要的中间问题。通常基站与用户设备之间的信道假定为IID、瑞利和平衰落。然而，在大规模MIMO中，天线紧密地挤在一起，用户设备周围存在局部散射体。这意味着相关通道模型更为现实。本文采用高斯单环散射模型对通道进行分析。分析了导频复用系数为1bbbb1的上行链路线性最小均方误差信道估计器的性能。推导了不同相关程度和导频长度下的估计性能上限，并通过数值实验进行了验证。在基站中采用稀疏嵌套阵列代替通常的密集均匀线性阵列。实验证明，当信道高度相关时，稀疏阵列的性能更好。然而，当相关性较小(σφ>> 0.5)时，两个阵列表现出相似的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2020 National Conference on Communications (NCC)

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