## 6 IoRT Systems Based on Hybrid NTN Networks
### Enhanced Throughput/Transmission Rate  
In [128], the authors present a simulation of a scenario involving a large number of UAVs hovering in the sky and a GEO-deployed relay satellite. They delve into analyzing and optimizing the performance of IoRT networks with UAV access and GEO satellite backhaul. To address the modeling challenges posed by the complex two-tier network, they developed a two-level queue system composed of multiple UAV queues on the first level and the satellite queue on the second level. To design the two-level transmission service for each UAV group, they introduce the stochastic network calculus (SNC)-based min-plus convolution and the leftover service, which are used as mathematical tools to effectively address the complexities of the network structure. The simulation results demonstrate that the proposed approach is effective in maximizing throughput while guaranteeing delay bounds. Satellite and UAV integrated networks have the potential to enable a variety of IoRT applications. With regard to IoRT applications, the authors of [64] investigate methods for enhancing downlink transmission. Radio frequency technology is used for satellite-to-UAV links, and free-space optical (FSO) technology is used for UAV-to-IoRT connectivity. To address the scarcity of statistical Channel State Information (CSI), the authors devise an \begin{table}
\begin{tabular}{p{42.7 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Ref.** & **NTN Architecture** & **Description** \\ \hline
[125] & LEO-UAV & A cognitive network architecture together with a cooperative beamforming scheme aiming to optimize energy efficiency under constrained energy resources. \\ \hline
[126] & LEO-UAV & Iterative-based algorithms are proposed to maximize systems’ energy efficiency in two-hop link communication for hybrid NTN-based IoRT networks. \\ \hline
[127] & LEO-UAV & Effective techniques have been developed to optimize UAV trajectories and transmit powers, aiming to maximize data upload volume while minimizing UAV energy consumption. \\ \hline \hline \end{tabular}
\end{table} 
Table 10: IoRT systems based on hybrid NTN networks: **enhancement of energy efficiency**. optimization problem aimed at maximizing the system's Ergodic Sum Rate (ESR) while adhering to power and IoRT device rate constraints. To address this nonconvex problem, a beamforming scheme based on the Alternating Direction Method of Multipliers (ADMM) is proposed. To reduce implementation complexity, a suboptimal zero-forcing approach is introduced. For the proposed BF schemes, closed-form ESR expressions are derived, and simulations are employed to validate the theoretical analysis. Addressing the critical absence of 5G coverage in maritime regions, ref. [129] proposes a nearshore network leveraging on-shore terrestrial base stations and tethered UAVs in virtual clusters. Employing non-orthogonal multiple access for efficient data transmission to maritime IoT devices, the network forms a hybrid satellite-UAV-terrestrial architecture. To mitigate interference, a joint power allocation problem is formulated to maximize network sum rates. Large-scale channel state information extracted from maritime IoT device locations is employed to optimize system overhead. An iterative power allocation algorithm is introduced, demonstrating the potential for enhanced coverage in maritime on-demand networks based on NOMA. Due to the limited transmission power of smart devices in IoRT networks, UAVs can be used as relays to transmit data from smart devices to LEO satellites in Space-Air-Ground (SAG)-IoRT systems. To maximize system capacity, the authors of [130] propose a joint optimization approach that considers smart device connection scheduling, power control, and UAV trajectory. To achieve maximum system capacity, researchers alternately iterate smart device connection scheduling, power control, and UAV trajectory design. The proposed iterative solution outperforms both the static UAV scheme and the dynamic UAV scheme with a circular trajectory.