Open AccessOn hybrid energy utilization for harvesting base station in 5G networks
Author(s) -
Yu ChihMin,
Tala’t Mohammad,
Feng KaiTen
Publication year - 2020
Publication title -
energy science and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.638
H-Index - 29
ISSN - 2050-0505
DOI - 10.1002/ese3.549
Subject(s) - network packet , markov decision process , computer science , transmission (telecommunications) , mathematical optimization , energy consumption , base station , energy (signal processing) , real time computing , maximum power principle , markov chain , power (physics) , energy storage , solar power , simulation , markov process , computer network , electrical engineering , photovoltaic system , engineering , telecommunications , mathematics , statistics , physics , quantum mechanics , machine learning
In this paper, hybrid energy utilization was studied for the base station in a 5G network. To minimize AC power usage from the hybrid energy system and minimize solar energy waste, a Markov decision process (MDP) model was proposed for packet transmission in two practical scenarios. In this model, one buffer is transmitted with a given number of data packets over finite transmission time intervals. In the two scenarios of packet transmission, solar energy harvesting (SEH) is stored in the first scene, while the other scene uses the energy immediately. The MDP model determines the best actions and decisions for both scenarios. When considering a finite battery size and finite packet buffer, the MDP model defines the actions, states, state transition probabilities, and cost value for each action. In the first scenario, the received solar energy harvester will not be used if it is not enough to transmit the packets in the buffer. In the second scenario, the received solar energy harvester will be used immediately. In both scenarios, the cost value is the weighted sum of AC power and SEH wastage. The simulation results showed the optimum buffer sizes could be determined for the balance between AC power consumption and SEH wastage based on the cost value of the proposed model. Finally, the numerical results indicated that the proposed MDP model could reduce AC power usage by up to 50%.