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Towards Deep Learning Augmented Robust D-Band Millimeter-Wave Picocell Deployment

Authors:

Hem Regmi,

Sanjib SurAuthors Info & Claims

ACM SIGMETRICS Performance Evaluation Review, Volume 50, Issue 4

Pages 62 - 64

https://doi.org/10.1145/3595244.3595266

Published: 27 April 2023 Publication History

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Abstract

D-band millimeter-wave, a key wireless technology for beyond 5G networks, promises extremely high data rate, ultra-low latency, and enables new Internet of Things applications. However, massive signal attenuation, complex response to building structures, and frequent non-availability of the Line-Of-Sight path make D-band picocell deployment challenging. To address this challenge, we propose a deep learning-based tool, that allows a network deployer to quickly scan the environment from a few random locations and predict Signal Reflection Profiles everywhere, which is essential to determine the optimal locations for picocell deployment.

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McDowell IBulusu RRegmi HSur S(2023)Outdoor Millimeter-Wave Picocell Placement using Drone-based Surveying and Machine Learning2023 32nd International Conference on Computer Communications and Networks (ICCCN)10.1109/ICCCN58024.2023.10230163(1-10)Online publication date: Jul-2023
https://doi.org/10.1109/ICCCN58024.2023.10230163

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cover image ACM SIGMETRICS Performance Evaluation Review

ACM SIGMETRICS Performance Evaluation Review Volume 50, Issue 4

March 2023

63 pages

ISSN:0163-5999

DOI:10.1145/3595244

Editor:
Zhenhua Liu
Stony Brook University

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Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 27 April 2023

Published in SIGMETRICS Volume 50, Issue 4

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McDowell IBulusu RRegmi HSur S(2023)Outdoor Millimeter-Wave Picocell Placement using Drone-based Surveying and Machine Learning2023 32nd International Conference on Computer Communications and Networks (ICCCN)10.1109/ICCCN58024.2023.10230163(1-10)Online publication date: Jul-2023
https://doi.org/10.1109/ICCCN58024.2023.10230163

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Low Profile CPW Fed Tri-Band Millimeter Wave Antenna Design for Future 5G Application

Five-Band Millimeter-Wave Antenna of Circular/Linear Polarization for Forthcoming Generations of Mobile Handsets

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