TY - JOUR
T1 - Age of Information in a Cellular Internet of UAVs
T2 - Sensing and Communication Trade-Off Design
AU - Zhang, Shuhang
AU - Zhang, Hongliang
AU - Han, Zhu
AU - Poor, H. Vincent
AU - Song, Lingyang
N1 - Funding Information:
Manuscript received January 8, 2020; revised April 26, 2020; accepted June 11, 2020. Date of publication June 30, 2020; date of current version October 9, 2020. This work was supported by the National Nature Science Foundation of China under Grant 61625101 and Grant 61941101. The associate editor coordinating the review of this article and approving it for publication was D. Lopez-Perez. (Corresponding author: Lingyang Song.) Shuhang Zhang and Lingyang Song are with the Department of Electronics, Peking University, Beijing 100871, China (e-mail: shuhangzhang@pku.edu.cn; lingyang.song@pku.edu.cn).
Publisher Copyright:
© 2002-2012 IEEE.
PY - 2020/10
Y1 - 2020/10
N2 - In this paper, we consider the cellular Internet of unmanned aerial vehicles (UAVs), where UAVs sense data with onboard sensors for multiple sensing tasks and transmit the data to the base station (BS). To quantify the 'freshness' of the data at the BS, we bring in the concept of the age of information (AoI). The AoI is determined by the time for UAV sensing and that for UAV transmission, which gives rise to a trade-off within a given period. To minimize the AoI, we formulate a joint sensing time, transmission time, UAV trajectory, and task scheduling optimization problem. This NP-hard problem can be decoupled into two subproblems. We first propose an iterative algorithm to optimize the sensing time, transmission time, and UAV velocity for completing a specific task. Afterwards, we design the order in which the UAV performs data updates for multiple sensing tasks. The convergence and complexity of the proposed algorithm, together with the trade-off between UAV sensing and UAV transmission, are analyzed. Simulation results show that the AoI with the proposed algorithm is about 15% lower than that of the greedy algorithm, and over 40% lower than that of the random algorithm.
AB - In this paper, we consider the cellular Internet of unmanned aerial vehicles (UAVs), where UAVs sense data with onboard sensors for multiple sensing tasks and transmit the data to the base station (BS). To quantify the 'freshness' of the data at the BS, we bring in the concept of the age of information (AoI). The AoI is determined by the time for UAV sensing and that for UAV transmission, which gives rise to a trade-off within a given period. To minimize the AoI, we formulate a joint sensing time, transmission time, UAV trajectory, and task scheduling optimization problem. This NP-hard problem can be decoupled into two subproblems. We first propose an iterative algorithm to optimize the sensing time, transmission time, and UAV velocity for completing a specific task. Afterwards, we design the order in which the UAV performs data updates for multiple sensing tasks. The convergence and complexity of the proposed algorithm, together with the trade-off between UAV sensing and UAV transmission, are analyzed. Simulation results show that the AoI with the proposed algorithm is about 15% lower than that of the greedy algorithm, and over 40% lower than that of the random algorithm.
KW - Age of information
KW - cellular Internet of UAVs
KW - sensing and transmission trade-off
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U2 - 10.1109/TWC.2020.3004162
DO - 10.1109/TWC.2020.3004162
M3 - Article
AN - SCOPUS:85092767565
SN - 1536-1276
VL - 19
SP - 6578
EP - 6592
JO - IEEE Transactions on Wireless Communications
JF - IEEE Transactions on Wireless Communications
IS - 10
M1 - 9130055
ER -