TY - GEN
T1 - Resource Management in Energy Harvesting Powered LoRa Wireless Networks
AU - Hamdi, Rami
AU - Qaraqe, Marwa
PY - 2021/8/6
Y1 - 2021/8/6
N2 - Long Range (LoRa) wireless networks, which is made up of low-powered connected devices, is a key technology for next generation wireless networks that support internet of things applications. Specifically, LoRa devices (LDs) may be powered by energy harvesting sources for greening wireless communications systems. Furthermore, LoRa modulation is based on the chirp spreading modulation (CSM) which consists of assigning various orthogonal spreading factors (SFs) among the LDs in the network. Hence, this paper investigates energy-efficient resource allocation in LoRa wireless networks, where the LDs are powered by independent energy harvesting sources. First, the problem of maximizing the number of scheduled LDs under quality of service constraints and making use of the available harvested energy, is formulated. Next, the relationship between the assigned SF, the instantaneous channel coefficients and the available energy at the batteries is analytically established. Hence, the optimal energy management, device scheduling, and SF assignment algorithm is proposed. Simulations results shows that the proposed resource allocation approaches offer efficient use of renewable energy which allows to enhance the rate of successful transmissions.
AB - Long Range (LoRa) wireless networks, which is made up of low-powered connected devices, is a key technology for next generation wireless networks that support internet of things applications. Specifically, LoRa devices (LDs) may be powered by energy harvesting sources for greening wireless communications systems. Furthermore, LoRa modulation is based on the chirp spreading modulation (CSM) which consists of assigning various orthogonal spreading factors (SFs) among the LDs in the network. Hence, this paper investigates energy-efficient resource allocation in LoRa wireless networks, where the LDs are powered by independent energy harvesting sources. First, the problem of maximizing the number of scheduled LDs under quality of service constraints and making use of the available harvested energy, is formulated. Next, the relationship between the assigned SF, the instantaneous channel coefficients and the available energy at the batteries is analytically established. Hence, the optimal energy management, device scheduling, and SF assignment algorithm is proposed. Simulations results shows that the proposed resource allocation approaches offer efficient use of renewable energy which allows to enhance the rate of successful transmissions.
KW - device scheduling
KW - energy harvesting
KW - energy management
KW - LoRa
KW - SF assignment
UR - http://www.scopus.com/inward/record.url?scp=85115728344&partnerID=8YFLogxK
U2 - 10.1109/ICC42927.2021.9500638
DO - 10.1109/ICC42927.2021.9500638
M3 - Published conference contribution
AN - SCOPUS:85115728344
T3 - IEEE International Conference on Communications
BT - ICC 2021 - IEEE International Conference on Communications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Conference on Communications, ICC 2021
Y2 - 14 June 2021 through 23 June 2021
ER -
