kumoh national institute of technology
Networked Systems Lab.

W. -P. Nwadiugwu and D. -S. Kim, "Compressed Time-Frequency Channel Beamforming Using Empirical MIMO-UWB RFs for Indoor Jobshop," in IEEE Sensors Journal, vol. 22, no. 6, pp. 5457-5469, 15 March15, 2022, doi: 10.1109/JSEN.2021.3117339.
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Date : 2022-03-16
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Abstract : Most collaborative analog-digital beamforming precoder architectures are commonly deployed for ground to-underground (G2U) layer system sensing. The architectures are designed based on the target systems signal channel links in order to leverage its array and multiplexing millimeter wave (mmWave) gains. Such gains includes link quality, energy consumption, delay and packet accuracy. But recent designs have mostly targeted narrowband-based channels and fewer wideband mmWave domains. In this paper, novel sparse-formulated in time-frequency and compressed process resource block (PRB) beamforming sensing, to decode-and-forward (DF) packets by joint-relaying it over radio frequency (RF) mmWave is proposed. The model is deployed into an indoor jobshop with remote sensing capability. The routing paths transmission energy is minimized using an optimized three-way next-hop node selection over empirically characterized MIMO-ultrawideband RFs of dissimilar soils volumetric water content (VWC) and burial depths. The novel collaborative time-frequency PRB-based approach is further exploited for estimating the wideband mmWave channels. Results are corroborated by calibrating the systems minimum transmission energy (MTE), packet-reception-ratio (PRR), link quality indicator (LQI), and end-to-end delay profiles using the latest vector network analyzer (VNA) 8722ES device.

Publication Date: MARCH 15, 2022
Print ISSN: 1530-437X
Online ISSN: 1558-1748