RL models

Applications in 5G

Adoption of Model in healthcare delivery



RL algorithm based on long short-term memory (RL-LSTM) cells.

In LTE unlicensed (LTE-U) networks, proactive resource allocation is formulated as a non-cooperative game that allows small base stations to learn which unlicensed channel to use based on long-term WLAN behavior and LTE-U traffic loads.

These models can be adopted on electronic medical records of deceased patients to estimate life expectancy.

[35] [37] [39]


Gradient follower (GF), the modified Roth-Erev (MRE), and the modified Bush and Mosteller (MBM)

To reduce intra/inter-tier interference, enable femtocells to sense the radio environment and tune their parameters in HetNets autonomously and opportunistically.

These models can be used for a variety of critical care and chronic illness treatment plans, automated medical diagnostics, and many other scheduling or control issues relating to the healthcare system.



RL with Network assisted feedback

Selection of Heterogeneous Radio Access Technologies (RATs).

These models are utilized to create effective solutions in a variety of healthcare settings where diagnosis choices or treatment plans typically involve a long period of time with delayed feedback.