My topic is on offloading/handoff in wireless heterogeneous networks. I want to try Machine learning techniques. I am looking around to find which kind of data I need and how to get it. Can I use simulated data to make predictions? which tools can I use to get or simulate this kind of data
please download this paper
www.eurecom.fr/en/publication/4395/download/cm-publi-4395.pdf
An up to date research topic is data offloading in cellular networks through device-to-device communication, a key enabling technology for the 5G. In such networks data packets can be directly forwarded between devices (e.g., cellphone) enabling to offload the data demand of the base station.
Several predictions could be applied to such networks. For instance, since the devices must be near to each other to communicate directly (D2D), you could use machine learning techniques to predict when, or what are the chances of two given devices getting in communication range in the near future and therefore decide if it is worth to cache a given content instead of transmitting it through the base station directly, enabling the base station offloading. For a more detailed description please take a look at the following paper:
http://ieeexplore.ieee.org/document/7553021/
For this type of project you can use real user contact proximity traces. Several are available at:
crawdad.org
Hope it helps!
Best,
Ivan.
Leveraging D2D multihop communication through social group meeting awareness
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