… We consider the downlink of an IRS-assisted NOMA system with K users as shown in Fig.
1. … Considering the dynamics of the system, we propose the use of reinforcement learning to …

… problem in a downlink MIMO-NOMA system to maximize the … Two deep reinforcement
learning-based frameworks are … -agent deep reinforcement learning based power allocation …

… optimization approach based on two reinforcement learning algorithms, namely deep … for
uplink and downlink NOMA to guarantee the quality of service (QoS). In [21], NOMA scheduling …

… instead of NOMA … NOMA, evolving OMA-URLLC to NOMA-URLLC faces numerous
challenges [14]. In [15], the authors designed downlink multiple-input multiple-output (MIMO)-NOMA …

This paper investigates the application of deep deterministic policy gradient (DDPG) to
intelligent reflecting surface (IRS) based unmanned aerial vehicles (UAV) assisted non-…

… We consider a downlink NOMA scenario with multiple base stations (BSs) located geographically
in close vicinity so that they might cause interference on each other, namely BS1, BS2 ··…

… Abstract—Non-orthogonal multiple access (NOMA) is regard… problem in an uplink multi-user
NOMA system to maximize the energy … a two-step deep reinforcement learning (DRL) based …

… In this paper, we consider a downlink multi-carrier NOMA system, where the base station
transmits data to multiple users over wireless channels. In such a system, the signals of …

… We consider a RIS aided NOMA downlink network operating over a … NOMA downlink
transmission, we select one user from each group to make up K user clusters. The NOMA downlink …

… the uplink ipSIC NOMA system, while in In [8], a deep reinforcement learning (DRL… downlink
ipSIC NOMA system. However, there is little research on the decoding order in ipSIC NOMA …