… Additionally, We utilize MSE loss function (12) to evaluate the accuracy of the training for
the target network. Therefore, the proposed loss function is based on θ and θ to check the …

… of the prominence of NOMA and DL and surveys several DL-enabled NOMA systems. This
… indicators of NOMA systems. In addition, we outline the integration of DL-based NOMA with …

… In this work, we use an artificial neural network (ANN) to assign an OMA or NOMA access …
we also evaluate the accuracy and training time of the three most relevant learning algorithms …

… -carrier NOMA system is still unclear. In this paper, we propose a deep reinforcement learning
… We also evaluate the minimal rate performance via different methods versus the power …

… learning tasks. First of all, we establish a unified multi-task deep neural network (DNN) framework
for NOMA… We implement DeepNOMA, evaluate its learning performance, and compare …

… learning (DL)-aided NOMA system, in which several NOMA … we exploit it to address wireless
NOMA channels in an end-to… to evaluate the data detection capacity of DL based on NOMA. …

… In this section, we evaluate the performance of the MIMO NOMA power allocation scheme
for M = 3 users in the dynamic anti-jamming communication game via simulations. If not …

… 5, we evaluate the impact of the number of clusters M on the performance of the IRS-aided
NOMA networks. The number of clusters is determined by the distance and correlation among …

… We further evaluate the system throughput and ESR to assess the overall performance of …
the QoS for the primary network, we must choose a practical value for the NOMA-based CSAT …

… Based on above discussions, in this paper, we propose a data-driven DL network to detect
users’ symbols jointly in CNOMA. The main contributions of this paper are summarized as …