TY - CHAP
T1 - Hardware impairment-aware data collection and wireless power transfer using a MIMO full-duplex UAV
AU - Hou, Jiancao
AU - Yang, Zhaohui
AU - Shikh-Bahaei, Mohammad
PY - 2020/6
Y1 - 2020/6
N2 - In this paper, we study a hardware impairment-aware data collection and wireless power transfer (WPT) framework using a multiple-input multiple-output (MIMO) full-duplex (FD) unmanned aerial vehicle (UAV). To enable high energy saving of ground users, we allow a MIMO FD UAV charge battery life time limited ground users while at the same time collect data from them in a flying-and-hovering mode. With the aim of practical implementation, we formulate an energy minimization problem by taking the UAV hardware impairments, its flying-and-hovering time, the number of uploaded data bits, and the energy harvesting causality into account. Due to non-convexity of the problem in terms of UAV trajectory and transmit beamforming for WPT, tracking the global optimality is quite challenging. Alternatively, we exploit a local optimal solution by implementing the proposed fixed-point search combining with successive convex approximation algorithm. In comparison to benchmark schemes, our results illustrate superior performances especially when the hardware impairment effects are taken into account. In addition, the proposed iterative algorithm exhibits fast convergence and fairly low computational complexity.
AB - In this paper, we study a hardware impairment-aware data collection and wireless power transfer (WPT) framework using a multiple-input multiple-output (MIMO) full-duplex (FD) unmanned aerial vehicle (UAV). To enable high energy saving of ground users, we allow a MIMO FD UAV charge battery life time limited ground users while at the same time collect data from them in a flying-and-hovering mode. With the aim of practical implementation, we formulate an energy minimization problem by taking the UAV hardware impairments, its flying-and-hovering time, the number of uploaded data bits, and the energy harvesting causality into account. Due to non-convexity of the problem in terms of UAV trajectory and transmit beamforming for WPT, tracking the global optimality is quite challenging. Alternatively, we exploit a local optimal solution by implementing the proposed fixed-point search combining with successive convex approximation algorithm. In comparison to benchmark schemes, our results illustrate superior performances especially when the hardware impairment effects are taken into account. In addition, the proposed iterative algorithm exhibits fast convergence and fairly low computational complexity.
UR - http://www.scopus.com/inward/record.url?scp=85090294312&partnerID=8YFLogxK
U2 - 10.1109/ICCWorkshops49005.2020.9145419
DO - 10.1109/ICCWorkshops49005.2020.9145419
M3 - Conference paper
AN - SCOPUS:85090294312
T3 - 2020 IEEE International Conference on Communications Workshops, ICC Workshops 2020 - Proceedings
BT - 2020 IEEE International Conference on Communications Workshops, ICC Workshops 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Conference on Communications Workshops, ICC Workshops 2020
Y2 - 7 June 2020 through 11 June 2020
ER -