Non-linear EH-based UAV-assisted FD IoT Networks: Infinite and Finite Blocklength Analysis
Type
ArticleKAUST Department
Communication Theory LabComputer, Electrical and Mathematical Science and Engineering (CEMSE) Division
Electrical and Computer Engineering Program
Date
2021Permanent link to this record
http://hdl.handle.net/10754/669280
Metadata
Show full item recordAbstract
In this paper, we investigate the non-linear energy harvesting (EH)-based unmanned aerial vehicle (UAV)-assisted full-duplex (FD) Internet-of-Things (IoT) network with infinite and finite blocklength (FBL) codes. The reliability performance of the considered network, having two half-duplex UAVs and an FD IoT device, is analyzed in terms of block error rate (BLER) with given ultra-reliable and low-latency communication constraints. With the assumption of the combined effect of fading and shadowing, the closed-form expressions for BLER and network goodput are obtained over Rician shadowed fading channels considering various shadowing scenarios, EH receiver architecture, IoT device mobility, inter-UAV interference, and self-interference (SI) cancellation capabilities at FD IoT device. The obtained results over Rician shadowed fading for non-linear EH receiver architecture are also compared with the linear EH and over Rician fading channels. The numerical results reveal important observations related to the impact of time-selective fading channels with imperfect channel state information, shadowing severity in the suburban areas, SI cancellation capabilities, blocklength and number of channel uses on the reliability performance of the UAV-assisted FD IoT network. Furthermore, the tightness of the approximation presented is verified through Monte-Carlo simulations.Citation
Raut, P., Singh, K., Li, C.-P., Alouini, M.-S., & Huang, W.-J. (2021). Non-linear EH-based UAV-assisted FD IoT Networks: Infinite and Finite Blocklength Analysis. IEEE Internet of Things Journal, 1–1. doi:10.1109/jiot.2021.3082102Sponsors
The work of Prasanna Raut and Chih-Peng Li was supported by the Ministry of Science and Technology of Taiwan under grants MOST 109-2218-E-110-006 & MOST 109-2221-E-110-050-MY3. The work of Keshav Singh was supported by the Ministry of Science and Technology of Taiwan under Grant MOST 109-2222-E-110-003.Publisher
IEEEJournal
IEEE Internet of Things JournalAdditional Links
https://ieeexplore.ieee.org/document/9437297/https://ieeexplore.ieee.org/document/9437297/
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9437297
ae974a485f413a2113503eed53cd6c53
10.1109/JIOT.2021.3082102