TY - GEN
T1 - Sum Throughput Optimization for Wireless Powered Sensor Networks
AU - Chu, Zheng
AU - Le, Tuan Anh
AU - To, Duc
AU - Nguyen, Huan X.
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/1
Y1 - 2017/7/1
N2 - This paper investigates a wireless powered sensor network (WPSN), where multiple sensor nodes are deployed to monitor certain external environment. A multi-antenna power beacon (PB) provides the power to these sensor nodes during wireless energy transfer (WET) phase, and then the sensor nodes employ the harvested energy to transmit their own monitoring information to one fusion center (FC) during wireless information transfer (WIT) phase. We maximize the system sum throughput of the sensor network considering two different scenarios, i.e., PB and the sensor nodes belong to the same/different service operator(s). For the first scenario, we propose an approach to jointly design the energy beamforming and the energy time allocation which is a convex optimization problem. We further develop a closed- form solution for the proposed sum throughput maximization. For the second scenario, where PB and the sensor nodes belong to the different service operators, we formulate the sum throughput maximization as Stackelberg-game-based and Social welfare schemes, in which we are then able to derive their equilibriums in closed-form solutions. Finally, numerical results are provided to validate the performance of our proposed schemes.
AB - This paper investigates a wireless powered sensor network (WPSN), where multiple sensor nodes are deployed to monitor certain external environment. A multi-antenna power beacon (PB) provides the power to these sensor nodes during wireless energy transfer (WET) phase, and then the sensor nodes employ the harvested energy to transmit their own monitoring information to one fusion center (FC) during wireless information transfer (WIT) phase. We maximize the system sum throughput of the sensor network considering two different scenarios, i.e., PB and the sensor nodes belong to the same/different service operator(s). For the first scenario, we propose an approach to jointly design the energy beamforming and the energy time allocation which is a convex optimization problem. We further develop a closed- form solution for the proposed sum throughput maximization. For the second scenario, where PB and the sensor nodes belong to the different service operators, we formulate the sum throughput maximization as Stackelberg-game-based and Social welfare schemes, in which we are then able to derive their equilibriums in closed-form solutions. Finally, numerical results are provided to validate the performance of our proposed schemes.
UR - http://www.scopus.com/inward/record.url?scp=85046437340&partnerID=8YFLogxK
U2 - 10.1109/GLOCOM.2017.8253950
DO - 10.1109/GLOCOM.2017.8253950
M3 - Conference contribution
AN - SCOPUS:85046437340
T3 - 2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings
SP - 1
EP - 6
BT - 2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE Global Communications Conference, GLOBECOM 2017
Y2 - 4 December 2017 through 8 December 2017
ER -