TY - GEN
T1 - Lifetime Maximization for UAV-Assisted Data Gathering Networks in the Presence of Jamming
AU - Rahmati, Ali
AU - Hosseinalipour, Seyyedali
AU - Guvenc, Ismail
AU - Dai, Huaiyu
AU - Bhuyan, Arupjyoti
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/5
Y1 - 2020/5
N2 - Deployment of unmanned aerial vehicles (UAVs) is recently getting significant attention due to a variety of practical use cases, such as surveillance, data gathering, and commodity delivery. Since UAVs are powered by batteries, energy efficient communication is of paramount importance. In this paper, we investigate the problem of lifetime maximization of a UAV-Assisted network in the presence of multiple sources of interference, where the UAVs are deployed to collect data from a set of wireless sensors. We demonstrate that the placement of the UAVs play a key role in prolonging the lifetime of the network since the required transmission powers of the UAVs are closely related to their locations in space. In the proposed scenario, the UAVs transmit the gathered data to a primary UAV called leader, which is in charge of forwarding the data to the base station (BS) via a backhaul UAV network. We deploy tools from spectral graph theory to tackle the problem due to its high non-convexity. Simulation results demonstrate that our proposed method can significantly improve the lifetime of the UAV network.
AB - Deployment of unmanned aerial vehicles (UAVs) is recently getting significant attention due to a variety of practical use cases, such as surveillance, data gathering, and commodity delivery. Since UAVs are powered by batteries, energy efficient communication is of paramount importance. In this paper, we investigate the problem of lifetime maximization of a UAV-Assisted network in the presence of multiple sources of interference, where the UAVs are deployed to collect data from a set of wireless sensors. We demonstrate that the placement of the UAVs play a key role in prolonging the lifetime of the network since the required transmission powers of the UAVs are closely related to their locations in space. In the proposed scenario, the UAVs transmit the gathered data to a primary UAV called leader, which is in charge of forwarding the data to the base station (BS) via a backhaul UAV network. We deploy tools from spectral graph theory to tackle the problem due to its high non-convexity. Simulation results demonstrate that our proposed method can significantly improve the lifetime of the UAV network.
KW - Cheeger constant
KW - energy efficiency
KW - jammer
KW - lifetime maximization
KW - UAV
KW - wireless sensor networks
UR - https://www.scopus.com/pages/publications/85090391365
U2 - 10.1109/SPAWC48557.2020.9154318
DO - 10.1109/SPAWC48557.2020.9154318
M3 - Conference contribution
AN - SCOPUS:85090391365
T3 - IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
BT - 2020 IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 21st IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2020
Y2 - 26 May 2020 through 29 May 2020
ER -