Optimization of LoRa SF Allocation Based on Deep Reinforcement Learning

Table 3

DQN algorithm parameters.

Parameter	Value
Greedy policy	0.9
Batch size	256
Reward discount	0.9
Target update frequency	100
Memory capacity	5000
Actions	18
States	7