This paper focuses on the performance evaluation of an energy harvesting (EH) equipped dual-hop relaying system for which the end-to-end signal-to-noise ratio (SNR) and the overall system throughput are analysed. The transmitter and the relay nodes are equipped with both fixed and EH batteries. The source for harvesting at the transmitter is the solar energy, and at the relay node, the interference energy in the radio frequency is the harvesting source. Time switching scheme is used at the relay to switch between EH and decoding information. Harvest-use approach is implemented, and we investigate the effects of the harvesting energy in enhancing the performance of the relaying system by deriving estimated closed-form expressions for the cumulative distribution function of each link's individual SNR and of the end-to-end SNR. The analytical expression for the ergodic capacity is also derived. These expressions are validated through Monte-Carlo simulations. It is also shown that with the additional EH at the transmitter (source and relay), a significant improvement in the system throughput can be achieved when fixed batteries are running on low powers.
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, it harvests energy for a period of 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, fixedbattery power limit, and time switching rate on the maximum achievable EE.
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