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Efficient Tensor Sensing for RF Tomographic Imaging on GPUs

1 and 1,2,*
1
Department of Computer Engineering and Science, Shanghai University, Shanghai 200444, China
2
Shanghai Institute for Advanced Communication and Data Science, Shanghai 200444, China
*
Author to whom correspondence should be addressed.
Future Internet 2019, 11(2), 46; https://doi.org/10.3390/fi11020046
Received: 4 January 2019 / Revised: 31 January 2019 / Accepted: 11 February 2019 / Published: 15 February 2019
(This article belongs to the Section Big Data and Augmented Intelligence)
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PDF [612 KB, uploaded 15 February 2019]
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Abstract

Radio-frequency (RF) tomographic imaging is a promising technique for inferring multi-dimensional physical space by processing RF signals traversed across a region of interest. Tensor-based approaches for tomographic imaging are superior at detecting the objects within higher dimensional spaces. The recently-proposed tensor sensing approach based on the transform tensor model achieves a lower error rate and faster speed than the previous tensor-based compress sensing approach. However, the running time of the tensor sensing approach increases exponentially with the dimension of tensors, thus not being very practical for big tensors. In this paper, we address this problem by exploiting massively-parallel GPUs. We design, implement, and optimize the tensor sensing approach on an NVIDIA Tesla GPU and evaluate the performance in terms of the running time and recovery error rate. Experimental results show that our GPU tensor sensing is as accurate as the CPU counterpart with an average of 44.79 × and up to 84.70 × speedups for varying-sized synthetic tensor data. For IKEA Model 3D model data of a smaller size, our GPU algorithm achieved 15.374× speedup over the CPU tensor sensing. We further encapsulate the GPU algorithm into an open-source library, called cuTensorSensing (CUDA Tensor Sensing), which can be used for efficient RF tomographic imaging. View Full-Text
Keywords: radio frequency; tomographic imaging; tensor; GPU radio frequency; tomographic imaging; tensor; GPU
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Xu, D.; Zhang, T. Efficient Tensor Sensing for RF Tomographic Imaging on GPUs. Future Internet 2019, 11, 46.

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