  The anticipated increase in the count of IoT devices in the coming years
motivates the development of efficient algorithms that can help in their
effective management while keeping the power consumption low. In this paper, we
propose LoRaDRL and provide a detailed performance evaluation. We propose a
multi-channel scheme for LoRaDRL. We perform extensive experiments, and our
results demonstrate that the proposed algorithm not only significantly improves
long-range wide area network (LoRaWAN)'s packet delivery ratio (PDR) but is
also able to support mobile end-devices (EDs) while ensuring lower power
consumption. Most previous works focus on proposing different MAC protocols for
improving the network capacity. We show that through the use of LoRaDRL, we can
achieve the same efficiency with ALOHA while moving the complexity from EDs to
the gateway thus making the EDs simpler and cheaper. Furthermore, we test the
performance of LoRaDRL under large-scale frequency jamming attacks and show its
adaptiveness to the changes in the environment. We show that LoRaDRL's output
improves the performance of state-of-the-art techniques resulting in some cases
an improvement of more than 500% in terms of PDR compared to learning-based
techniques.
