## 1 Introduction  
The explosive number of devices demands data traffic growth and new radio spectrum resources in future 6G systems and the IoT context. Key enabling technologies are (i) the underutilized millimeter wave (mmWave) band (between 30 GHz and 300 GHz), which could be valuable for its wide bandwidth and higher spectral efficiency, and (ii) NOMA, which could be valuable for simultaneously supporting multiple users on the same time-frequency resources. The joint use of the large spectrum available in mmWaves together with massive multiple-input-multiple-output (MIMO) strategies allows ultra-high data rates to be guaranteed through spatial directional transmissions compensating for the high propagation loss of mmWaves communications [1]. This directional nature of mmWaves transmissions needs the support of one radio frequency (RF) chain for each user on the same time-frequency resource. Therefore, the hardware complexity and costs of the mmWave MIMO system increase with an increase in the number of users. Hybrid architectures, which combine phase shifters based on analog precoding and digital precoding, reduce the costs practically by selecting a reduced number of RF chains. However, even if hybrid beamforming structures are implemented, the user's channels are highly correlated in mmWave communications, and thus, the users cannot be separated by linear operations. Such a correlation facilitates integration with NOMA technology. NOMA can simultaneously serve multiple users on the same time-frequency resource by converting their channel gains into multiplexed gains in the power domain and by using successive interference cancellation (SIC) at the receiver to remove intra-channel interference with a decoding order based on the channel conditions [2; 3; 4]. In the literature, different papers analyze the spectral efficiency (SE) and the energy efficiency (EE) maximization problem mainly for a downlink mmWave MIMO with hybrid beamforming [5; 6]. In [3], a power allocation (PA) problem to optimize EE is considered for an uplink NOMA-assisted mmWave MIMO system under users' quality-of-service (QoS) and quality-of-experience requirements [7]. In [4], power allocation and beamforming are jointly considered to maximize the sum rate of a pair of users in a mmWave NOMA system by using an analog beamforming structure indeed of a hybrid mmWave beamforming structure. Simultaneous wireless information and power transfer (SWIPT) techniques are integrated in mmWave massive MIMO-NOMA systems to maximize the energy efficiency in [8], and consequently, each user can extract both information and energy from the received RF signals by using a power splitting receiver. In the 6G vision, low Earth orbit (LEO) satellites and diverse aerial platforms, such as UAVs, are considered to support IoT development in remote areas and in emergency situations thanks to the mobility, flexibility and good channel conditions of UAVs. UAVs have been developed for their monitoring capabilities, implemented by on board sensors, for services in agriculture or security border controls. In addition, UAVs are used as a flying base station (BS) to provide ubiquitous connectivity and effectively increase the coverage and throughput of wireless systems through the optimization of UAVs' positions and trajectories [9]. Recently, UAVs have been considered to act as relays for cooperative communications due to the high probability to establish LoS links with the ground terminals. UAV-assisted relaying systems operate according to the two classical types of transmission protocols, namely decode-and-forwarding (DF) and amplify-and-forwarding (AF) [10]. Several papers consider UAV communications combined with orthogonal multiple access (OMA) to maximize the energy efficiency or throughput by optimizing the source/relay transmit power and the UAV speed and trajectory design as, e.g., in [11].