DocumentCode :
2144471
Title :
Optimal energy allocation policy for wireless networks in the sky
Author :
Dinh, Thai Hoang ; Niyato, Dusit ; Hung, Nguyen Tai
Author_Institution :
School of Computer Engineering, Nanyang Technological University (NTU), Singapore
fYear :
2015
fDate :
8-12 June 2015
Firstpage :
3204
Lastpage :
3209
Abstract :
Google´s Project Loon [1] was launched in 2013 with the aim of providing Internet access to rural and remote areas. In the Loon network, balloons travel around the Earth and bring access points to the users who cannot connect directly to the global wired Internet. The signals from the users will be transmitted through the balloon network to the base stations connected to the Internet service provider (ISP) on Earth. The process of transmitting and receiving data consume a certain amount of energy from the balloon, while the energy on balloons cannot be supplied by stable power source or by replacing batteries frequently. Instead, the balloons can harvest energy from natural energy sources, e.g., solar energy, or from radio frequency energy by equipping with appropriate circuits. However, such kinds of energy sources are often dynamic and thus how to use this energy efficiently is the main goal of this paper. In this paper, we study the optimal energy allocation problem for the balloons such that network performance is optimized and the revenue for service providers is maximized. We first formulate the stochastic optimization problem as a Markov decision process and then apply a learning algorithm based on simulation-based method to obtain optimal policies for the balloons. Numerical results obtained by extensive simulations clearly show the efficiency and convergence of the proposed learning algorithm.
Keywords :
Batteries; Convergence; Energy states; Internet; Markov processes; Mobile communication; Satellites; Google Loon Project; Internet in the sky; Markov decision process;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications (ICC), 2015 IEEE International Conference on
Conference_Location :
London, United Kingdom
Type :
conf
DOI :
10.1109/ICC.2015.7248817
Filename :
7248817
Link To Document :
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