… In the following, we simulate different hyper-parameters (eg, the learning layer and the
network structure) to find the optimal configuration. Then, we evaluate the performance of DRLA …

… learning on other more complicated NOMA techniques. Meanwhile, with the benefit of the
MIMO technique, MIMO-NOMA … To evaluate the performance gap, the proposed MIMO-NOMA-…

… We evaluate the performance of the proposed method by means of computer simulations,
considering the system model from Section II with the parameters defined in Table 5 from …

… Then, we test the robustness of the performance of the proposed deep learning-based
MIMO-NOMA framework. To evaluate the performance of the developed CDNN structure, we …

… Towards this end, we propose two distributed Q-learning aided uplink grant-free non-orthogonal
multiple access (NOMA) schemes (including all-devices distributed Q-learning (ADDQ) …

… This paper presents a performance evaluation of the cooperative NOMA using a deep
learning based methodology. The signal from the base station (BS) is transmitted to the far users …

… We evaluate the performance of the proposed DL approaches in terms of the RMSE and
run-time prediction. The RMSE is considered to determine the difference between the forecast …

… Furthermore, the robustness of the DL technique is additionally evaluated for its dominance
… NOMA scheme is developed with the help of hybrid-cascaded Deep Neural Network (DNN) …

… -driven approach through deep learning (DL) to … NOMA scheme, wherein the primary network
consists of a source node S, a near-user D1 and a faruser D2, while the secondary network …

… Therefore, we approximate the SIC decoding order by leveraging deep learning to training
through large amounts of data. We further simulate and evaluate our proposed DLPA scheme…