i want to implement D2D communication in omnet++ with simuLTE. my topic is Distributed traffic offloading approach using Machine learning and content distribution in d2d network to reduce latency and power consumption. which technique is most suitable for my work? can i use Q learning? or how federated learning can be used in this work?
I suggest you follow : https://eprints.gla.ac.uk/144139/7/144139.pdfPreprint Distributed Artificial Intelligence Solution for D2D Communi...
Article Traffic and Computation Co-Offloading With Reinforcement Lea...
and
http://repositorio.uchile.cl/bitstream/handle/2250/132644/Energy-Efficiency-Oriented-Traffic-Offloading-in-wireless-networks.pdf?sequence=1
Distributed approach can be applied to any machine that can connect to the network, have local memory, and communicate by passing messages. By distributing requests and workloads, compared with a standard single system, a distributed system can support more requests and computing tasks. ML or machine learning use algorithm to create ability for improvement via training. Today, ML algorithms are trained using following three prominent methods or types : supervised learning, unsupervised learning, and reinforcement learning. You may adopt any of these types according to your own requirement.
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