Power allocation and transmitter switching for broadcasting with multiple energy harvesting transmitters
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Power allocation and transmitter switching for broadcasting with multiple energy harvesting transmitters Hongbin Chen1* , Feng Zhao1 , Rong Yu2 and Xiaohuan Li3
Abstract With the advancement of battery technology, energy harvesting communication systems attracted great research attention in recent years. However, energy harvesting communication systems with multiple transmitters and multiple receivers have not been considered yet. In this paper, the problem of broadcasting in a communication system with multiple energy harvesting transmitters and multiple receivers is studied. First, regarding the transmitters as a ‘whole transmitter,’ the optimal total transmission power is obtained and an optimal power allocation policy is extended to our system setup, with the aim of minimizing the transmission completion time. Then, a simpler power allocation policy is developed to allocate the optimal total transmission power to the data transmissions. As transmitter switching can provide flexibility and robustness to an energy harvesting communication system, especially when a transmitter is broken or the energy harvested by a transmitter is insufficient, a transmitter switching policy is further developed to choose a suitable transmitter to work whenever necessary. The results show that the proposed power allocation policy performs close to the optimal one and outperforms some heuristic ones in terms of transmission completion time. Besides, the proposed transmitter switching policy outperforms some heuristic ones in terms of number of switches. Keywords: Rechargeable wireless communications; Energy harvesting; Power allocation; Transmitter switching
1 Introduction Recently, energy harvesting or rechargeable sensor networks emerge as a new paradigm of sensor networks, in which the nodes can harvest energy from nature [1-3]. Before this, sensor network nodes are powered by batteries with limited energy storage, which are hard to recharge or replace. Therefore, the key challenge is to save energy and prolong network lifetime while guaranteeing the application-specific performance [4]. In contrast, the harvested energy relaxes the energy constraint, thus extending network lifetime in energy harvesting sensor networks. However, the energy that can be harvested from the environment is unstable and varies over time. Hence, the harvested energy should be carefully utilized in order to maximize the utility of energy harvesting sensor networks. *Correspondence: [email protected] 1 Key Laboratory of Cognitive Radio and Information Processing, Guilin University of Electronic Technology, Ministry of Education, Guilin 541004, China Full list of author information is available at the end of the article
A lot of excellent works on energy management in energy harvesting sensor networks have been done. For example, two-stage communication power management algorithms were proposed for maximizing the utility of energy harvesting sensors, considering the energy neutrality constraint, the fixed power loss effects of ci
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