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5G Positioning and Mapping With Diffuse Multipath
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DOI：10.1109/TWC.2020.3031180.png)
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Abstract
En 中文
5G mmWave communication is useful for positioning due to the geometric connection between the propagation channel and the propagation environment. Channel estimation methods can exploit the resulting sparsity to estimate parameters (delay and angles) of each propagation path, which in turn can be exploited for positioning and mapping. When paths exhibit significant spread in either angle or delay, these methods break down or lead to significant biases. We present a novel tensor-based method for channel estimation that allows estimation of mmWave channel parameters in a non-parametric form. The method is able to accurately estimate the channel, even in the absence of a specular component. This in turn enables positioning and mapping using only diffuse multipath. Simulation results are provided to demonstrate the efficacy of the proposed approach.
Keywords:
Tensors
5G mobile communication
Channel estimation
Delays
Transmission line matrix methods
Wireless communication
Estimation
Massive MIMO
localization
beamspace ESPRIT
tensor decomposition
subspace
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