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Release of Book on "Machine Learning for Future Wireless Communications"

We are pleased to annouce that the print version of the novel Wiley/IEEE Press book "Machine Learning for Future Wireless Communications" has been released. For "Part I - Spectrum Intelligence and Adaptive Resource Management", we have contributed the chapter "Machine Learning for Resource-Efficient Data Transfer in Mobile Crowdsensing" which reports key results of subprojects A4 and B4 of the collaborative research center SFB 876. In particular, we present novel context-aware and context-predictive methods that utilize machine learning to opportunistically schedule vehicular sensor data transmissions with respect to the anticipated resource efficiency. The proposed approach is not only able to boost the end-to-end data rate of vehicular data transmissions, it simultaneously reduces the power consumption of the mobile devices and contributes to a more efficient usage of the limited network resources.

MachineLearning

More information about the book itself can be found at:

B. Sliwa, R. Falkenberg, C. Wietfeld, "Machine learning for resource-efficient data transfer in mobile crowdsensing", Chapter in Machine Learning for Future Wireless Communications (F. L. Luo, ed.), John Wiley & Sons Inc, February 2020