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where b denotes the bias value.
Since the best bias value changes depending on some factors, no learning (fixed bias value) has more outage UEs than no learning (best bias value).
The number of connected UEs at each common bias value.
No learning scheme (best bias value) can always be better than no learning scheme (fixed bias value).
In this article, each UE learns the bias value that minimizes the number of outage UEs individually by Q-learning and can set the appropriate bias value independently.
From now on, we compare three schemes: the proposed Q-learning scheme, no learning scheme (best bias value), and no learning scheme (fixed bias value).
In this figure, no learning (best bias value) represents the minimum value of the number of outage UEs among the schemes using common bias value.
No learning scheme (best bias value) searches the bias value that minimizes the number of outage UEs with trial and error method every time.
Wear mechanism transitions, wear rate variations, and coefficients were recorded for each bias value applied.
This result shows that setting UE's own bias value improves cell-edge UE throughput largely.
Step (5) Each UE uses chosen set's bias value as an action.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com