Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: AI Based Landscape Sensing Using Radio Signals   In many sensing applications, typically radio signals are emitted by a radar
and from the bounced reflections of the obstacles, inference about the
environment is made. Even though radars can be used to sense the landscapes
around the user-equipment (UE) such as whether UE is in the forested region,
inside buildings, etc., it is not suitable in many wireless applications as
many UEs does not have radars in them. Using radar will also increase the cost
and power requirements on the UEs in applications requiring sensing of the
landscapes. In this paper, we provide a mechanism where basestation (BS) is
able to sense the UE's landscape without the use of a radar. We propose an
artificial intelligence (AI) based approach with suitable choice of the
features derived from the wireless channel to infer the landscape of the UEs.
Results for the proposed methods when applied to practical environments such as
London city scenario yields a precision score of more than 95 percent.

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The categories of this paper are: q-alg
25
The categories of this paper are: patt-sol
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The categories of this paper are: plasm-ph
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The categories of this paper are: funct-an
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The categories of this paper are: nucl-ex
5
The categories of this paper are: gr-qc
4
The categories of this paper are: cond-mat
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The categories of this paper are: nlin
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The categories of this paper are: q-bio
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The categories of this paper are: dg-ga
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The categories of this paper are: supr-con
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The categories of this paper are: mtrl-th
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The categories of this paper are: solv-int
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The categories of this paper are: bayes-an
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The categories of this paper are: quant-ph
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The categories of this paper are: comp-gas