Abstract
The increasing amount of mobile terminals has brought significant traffic load to base stations, which will lead to data failure. Considering the increasing ability of mobile terminals, cooperation between mobile terminals will help increase the spectrum efficiency and reduce latency. In this work, we have raised a novel node selection and transmission fusion method using artificial intelligence. First of all, we draw the status of mobile terminals reflected by thermal pattern, then we propose the deep learning method to indicate the status of every node and make an optimized selection of target node, at last, we perform the multi stage transmission for wireless information fusion to enhance the spectrum efficiency. Simulation results have proved that our suggested method could help select the proper node to adopt transmission among all candidates and the average throughput is increased up to 32% from the system level simulation.
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This work is funded by National Nature Science Foundation of China under grant of 61701503. The author would also like to thank all the reviewers, their suggestions help improve my work a lot.
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Gao, Y. et al. (2020). A Novel AI Based Optimization of Node Selection and Information Fusion in Cooperative Wireless Networks. In: Bi, Y., Bhatia, R., Kapoor, S. (eds) Intelligent Systems and Applications. IntelliSys 2019. Advances in Intelligent Systems and Computing, vol 1038. Springer, Cham. https://doi.org/10.1007/978-3-030-29513-4_2
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DOI: https://doi.org/10.1007/978-3-030-29513-4_2
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