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With the use of power domain non-orthogonal multiple access (NOMA) and backscatter communication (BAC), future sixth-generation ultra-massive machine-type communications networks are expected to connect large-scale Internet of Things (IoT) devices. However, due to NOMA co-channel interference, power allocation to large-scale IoT devices becomes critical. With existing convex optimization approaches, it is challenging to find the optimal resource allocation in a dynamic environment. To alleviate this problem and increase the sum rate of uplink backscatter devices, this work develops an efficient model-free BAC-NOMA approach to assist the base station with complex resource scheduling tasks in a dynamic environment. We jointly optimize the transmit power of downlink IoT users and the reflection coefficient of uplink backscatter devices using the soft-actor critic algorithm. The proposed algorithm ensures …