… In this section, we evaluate the performance of the proposed DNN based solution. To obtain
the training data, we randomly generate independent and identically distributed Rayleigh …

… In the experiment, we use a wireless MEC network with K = 10 WDs. To evaluate the
performance of the proposed algorithm more clearly, we take the normalized computation rate Q ˆ ( …

… adopt the power-domain NOMA to complete the superposition … We use power-domain
NOMA to enable signals from different … Extensive numerical results are collected to evaluate the …

… 1) We establish an end-to-end neural network model of grant-free NOMA … evaluate the
ultimate reliability performance of DL-aided grant-free NOMA, here we adopt a larger network …

… NOMA systems. We first provide a short overview of the DL methods that are useful in NOMA
and other wireless networking … assignment decision is evaluated with the help of Q learning. …

… In general, we aim to propose a learning-based mechanism for the smart reconfigurable
THz MIMO-NOMA network to jointly coordinate both multiple APs and RISs, which has the flow …

… The proposed deep learning-based resource allocation framework is defined and developed
in Section III. In Section IV, we evaluate the performance of our proposed algorithm through …

… Computation time: We carefully evaluate the computation time of ADI prediction, NOMA
grouping and DNN-based BC under a computer configuration CPU i5-9600K, GPU NVIDIA …

… its performance when adopted in grant-free NOMA networks, in this paper we characterized
the performance of a ZCbased grant-free network. First, a stochastic geometry model is …

… of NOMA user partitioning and RIS phase shifting, aiming at maximizing the sum data rate of
the mobile users (MUs) in NOMA downlink networks… self-adjusting learning model where the …