3 research outputs found

    Impact of Rough Surface Scattering on Stochastic Multipath Component Models

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    Multipath-assisted positioning makes use of specular multipath components (MPCs), whose parameters are geometrically related to the positions of the transceiver nodes. Diffuse scattering from rough surfaces affects the observed specular reflections in the angular and delay domains. Based on the effective roughness approach, the angular delay power spectrum can be calculated as a function of location parameters, which-in a next step-could be useful to accurately characterize the position-related information of MPCs. The calculated power spectra follow reported characteristics of stochastic multipath models, i.e. Gaussian shape in the angular domain and an exponential shape in the delay domain. The resulting angular and delay spreads are in an equivalent range to values reported in literature

    5G Positioning and Mapping with Diffuse Multipath

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    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 breakdown 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

    A survey on 5G massive MIMO Localization

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    Massive antenna arrays can be used to meet the requirements of 5G, by exploiting different spatial signatures of users. This same property can also be harnessed to determine the locations of those users. In order to perform massive MIMO localization, refined channel estimation routines and localization methods have been developed. This paper provides a brief overview of this emerging field
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