Abstract-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 energyefficient transmission power allocation techniques for a pointto-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, P u, and in-turn, the maximum achievable EE. Analytical derivations show that the maximum achievable EE monotonically increases with harvested power, whereas, P u 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. Index Terms-Energy harvesting, energy efficiency, convex optimization, fractional programming. Green wireless communication technologies have attracted significant attention in the last few years as to provide possible solutions to energy limitation problems in information and communication technologies (ICT) [1] . Specifically, due to the increase in the number of mobile users, demand for higher data rates, and the base station (BS) is required to increase its transmission power, which in turn, results in higher greenhouse gases, pollution, and also higher costs [2] . Furthermore, the battery technology has not progressed with the same pace, which has resulted in increasing gap between increasing demand for power and the battery advancements [3] . These facts have motivated research in investigating new ways to get energy from re-usable sources. Energy efficiency (EE), which is defined as the data transferred per unit energy consumed, with unit of b/J/Hz, has recently received a great deal of interest [4], [5] . Improving EE or maximizing throughput, has been investigated widely in literature, e.g., [6] , [7] , which show that increasing EE in many cases results in decreasing rate. In this trend, recently, energy harvesting has emerged as a new technology to improve EE, while maintaining the spectral efficiency (SE) [8] . Energy harvesting has indeed the capability of reducing the carbon consumption of high data rate wireless systems by reusing the energy which is available at the surrounding environment [9] . In addition, energy harvesting techniques are used to increase the life of battery limited devices, e.g,
In REF , the authors study the transmission power allocation strategy to achieve the energy-efficient transmission.
Energy efficiency optimization with energy harvesting using harvest-use approach
2015 IEEE International Conference on Communication Workshop (ICCW)
2015 IEEE International Conference on Communication Workshop (ICCW)
Computer Science