Joint Estimation of Channel Parameters in Massive MIMO Systems via PARAFAC Analysis

Wei X, Peng W, Wing Kwan Ng D, Schober R, Jiang T (2018)


Publication Language: English

Publication Type: Conference contribution

Publication year: 2018

Event location: Maui, HI US

ISBN: 978-1-5386-3652-7

DOI: 10.1109/ICCNC.2018.8390299

Abstract

In this paper, we investigate channel parameter estimation for massive multiple-input multiple-output (MIMO) systems, where a large base station (BS) antenna array is used to provide multiplexing and diversity gains. We propose a Parallel Factor (PARAFAC)-based joint estimation scheme, which exploits the low-rank property of massive MIMO channels caused by the physical finite scattering environment. Specifically, we first parameterize the channel in terms of fading coefficients, directions of arrival (DOAs), and delays, thereby the channel is characterized via three equivalent PARAFAC models. Subsequently, we certify the identifiability of the three parameters of the PARAFAC models by exploiting the low-rank property. Then, we develop the proposed PARAFAC-based estimation scheme, which jointly estimates the three channel parameters using an alternating least squares (ALS) algorithm. Moreover, we analyze the computational complexity of the proposed scheme in terms of the required number of floating-point operations (FLOPs). Simulation results show that the proposed scheme achieves both a high performance and a low computational complexity.

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APA:

Wei, X., Peng, W., Wing Kwan Ng, D., Schober, R., & Jiang, T. (2018). Joint Estimation of Channel Parameters in Massive MIMO Systems via PARAFAC Analysis. In IEEE (Eds.), Proceedings of the 2018 International Conference on Computing, Networking and Communications (ICNC). Maui, HI, US.

MLA:

Wei, Xiao, et al. "Joint Estimation of Channel Parameters in Massive MIMO Systems via PARAFAC Analysis." Proceedings of the 2018 International Conference on Computing, Networking and Communications (ICNC), Maui, HI Ed. IEEE, 2018.

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