TY - GEN
T1 - Energy efficiency optimization with energy harvesting using harvest-use approach
AU - Siddiqui, Arooj Mubashara
AU - Musavian, Leila
AU - Ni, Qiang
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/9/8
Y1 - 2015/9/8
N2 - Energy harvesting is emerging as a promising approach to improve the energy efficiency (EE) and to extend the life of wireless networks. This paper focuses on energy-efficient transmission power allocation techniques for a point-to-point communication channel, equipped with a fixed-power battery, as well as a harvest-use battery. Using the fact that the harvested energy does not consume from the fixed battery, EE is formulated as the ratio of Shannon limit (as a function of the sum of the power consumed from the fixed battery and the harvest-use battery) to the sum of the circuit power and power consumed from the fixed battery. For the considered energy harvest-use technique, a time switching approach is used that in each frame, the node harvests energy for a percentage of frame time and transmits data for the rest of the frame time. Using the fact that the formulated EE is a quasi-concave function in transmission power, we use fractional programming to obtain the optimal power level, Pu, and in-turn, the maximum achievable EE. Analytical derivations show that the maximum achievable EE monotonically increases with harvested power, whereas, Pu monotonically decreases with it. Simulation results show the effects of harvested energy, fixed-battery power limit, and time switching rate on the maximum achievable EE.
AB - Energy harvesting is emerging as a promising approach to improve the energy efficiency (EE) and to extend the life of wireless networks. This paper focuses on energy-efficient transmission power allocation techniques for a point-to-point communication channel, equipped with a fixed-power battery, as well as a harvest-use battery. Using the fact that the harvested energy does not consume from the fixed battery, EE is formulated as the ratio of Shannon limit (as a function of the sum of the power consumed from the fixed battery and the harvest-use battery) to the sum of the circuit power and power consumed from the fixed battery. For the considered energy harvest-use technique, a time switching approach is used that in each frame, the node harvests energy for a percentage of frame time and transmits data for the rest of the frame time. Using the fact that the formulated EE is a quasi-concave function in transmission power, we use fractional programming to obtain the optimal power level, Pu, and in-turn, the maximum achievable EE. Analytical derivations show that the maximum achievable EE monotonically increases with harvested power, whereas, Pu monotonically decreases with it. Simulation results show the effects of harvested energy, fixed-battery power limit, and time switching rate on the maximum achievable EE.
KW - convex optimization
KW - energy efficiency
KW - Energy harvesting
KW - fractional programming
UR - http://www.scopus.com/inward/record.url?scp=84947745848&partnerID=8YFLogxK
U2 - 10.1109/ICCW.2015.7247471
DO - 10.1109/ICCW.2015.7247471
M3 - Conference contribution
AN - SCOPUS:84947745848
T3 - 2015 IEEE International Conference on Communication Workshop, ICCW 2015
SP - 1982
EP - 1987
BT - 2015 IEEE International Conference on Communication Workshop, ICCW 2015
PB - Institute of Electrical and Electronics Engineers (IEEE)
T2 - IEEE International Conference on Communication Workshop, ICCW 2015
Y2 - 8 June 2015 through 12 June 2015
ER -