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Title: Presentation for LDRD FY19 proposal: An Innovative Secure millimeter wave (mmWave) Machine to Machine (M2M) Communication Network for Operating Drones

Abstract

We propose to prove the principle that a novel 5G wireless network using newly available millimeter wave (mmWave) frequency bands can operate Unmanned Aerial Vehicles (UAVs) with Machine to Machine (M2M) communication. If successful, this proposed network will provide a superior alternative to existing methods with improved radio frequency (RF) coverage and resiliency against cyberattacks. The use of UAVs or drones for non-military applications has been advancing rapidly for a large number of applications in the United States. They include public safety search and rescue of natural disaster victims, surveillance of remote critical infrastructure, surveys of environmental quality in protected regions, and detection of threats during major public events. The proposed approach involves research with modeling, simulation, and experimentation to validate the hypothesis in the following thrusts: 1) Using mmWave beams with antennas tilted upward for RF coverage in the sky to analyze the security, reliability, and spectral efficiency of this wireless network for UAV/drone operation; 2) Adding non orthogonal multiple access (NOMA) to analyze increase in security and spectral efficiency when compared to existing methods; 3) Adding intra-drone communication among the swarm of drones to analyze further increase in reliability and spectral efficiency; 4) Concluding the proof of principle/conceptmore » with modeling and experiment to demonstrate that a swarm of drones controlled with this advanced network can be effectively used during the simulated recovery of a critical infrastructure e.g. a cyber compromised power grid that requires a black restart. The experiments will be executed at the North Carolina State University (NCSU) using NCSU’s 28 GHz mmWave system. A conceptual Invention Record Disclosure (IDR) has been filed and we expect Intellectual Property (IP) from this proposed research to advance the IRD towards patent filing by INL with support from NCSU. Successful outcome from this work will pave the way for significant future research needed to mature the technology for a nationwide secure and reliable network supporting a large number of government and public safety drones.« less

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3]
  1. Idaho National Laboratory
  2. Associate Professor, NCSU
  3. Professor, NCSU
Publication Date:
Research Org.:
Idaho National Lab. (INL), Idaho Falls, ID (United States)
Sponsoring Org.:
USDOE Laboratory Directed Research and Development (LDRD) Program
OSTI Identifier:
1498778
Report Number(s):
INL/MIS-18-45835-Rev000
DOE Contract Number:  
AC07-05ID14517
Resource Type:
Program Document
Country of Publication:
United States
Language:
English
Subject:
99 - GENERAL AND MISCELLANEOUS; mmWave; Machine to Machine (MM); Drone; Cellular communications

Citation Formats

Bhuyan, Arupjyoti, Guvenc, Ismail, and Dai, Huaiyu. Presentation for LDRD FY19 proposal: An Innovative Secure millimeter wave (mmWave) Machine to Machine (M2M) Communication Network for Operating Drones. United States: N. p., 2018. Web.
Bhuyan, Arupjyoti, Guvenc, Ismail, & Dai, Huaiyu. Presentation for LDRD FY19 proposal: An Innovative Secure millimeter wave (mmWave) Machine to Machine (M2M) Communication Network for Operating Drones. United States.
Bhuyan, Arupjyoti, Guvenc, Ismail, and Dai, Huaiyu. Tue . "Presentation for LDRD FY19 proposal: An Innovative Secure millimeter wave (mmWave) Machine to Machine (M2M) Communication Network for Operating Drones". United States. https://www.osti.gov/servlets/purl/1498778.
@article{osti_1498778,
title = {Presentation for LDRD FY19 proposal: An Innovative Secure millimeter wave (mmWave) Machine to Machine (M2M) Communication Network for Operating Drones},
author = {Bhuyan, Arupjyoti and Guvenc, Ismail and Dai, Huaiyu},
abstractNote = {We propose to prove the principle that a novel 5G wireless network using newly available millimeter wave (mmWave) frequency bands can operate Unmanned Aerial Vehicles (UAVs) with Machine to Machine (M2M) communication. If successful, this proposed network will provide a superior alternative to existing methods with improved radio frequency (RF) coverage and resiliency against cyberattacks. The use of UAVs or drones for non-military applications has been advancing rapidly for a large number of applications in the United States. They include public safety search and rescue of natural disaster victims, surveillance of remote critical infrastructure, surveys of environmental quality in protected regions, and detection of threats during major public events. The proposed approach involves research with modeling, simulation, and experimentation to validate the hypothesis in the following thrusts: 1) Using mmWave beams with antennas tilted upward for RF coverage in the sky to analyze the security, reliability, and spectral efficiency of this wireless network for UAV/drone operation; 2) Adding non orthogonal multiple access (NOMA) to analyze increase in security and spectral efficiency when compared to existing methods; 3) Adding intra-drone communication among the swarm of drones to analyze further increase in reliability and spectral efficiency; 4) Concluding the proof of principle/concept with modeling and experiment to demonstrate that a swarm of drones controlled with this advanced network can be effectively used during the simulated recovery of a critical infrastructure e.g. a cyber compromised power grid that requires a black restart. The experiments will be executed at the North Carolina State University (NCSU) using NCSU’s 28 GHz mmWave system. A conceptual Invention Record Disclosure (IDR) has been filed and we expect Intellectual Property (IP) from this proposed research to advance the IRD towards patent filing by INL with support from NCSU. Successful outcome from this work will pave the way for significant future research needed to mature the technology for a nationwide secure and reliable network supporting a large number of government and public safety drones.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {7}
}

Program Document:
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