## 5 IoRT Systems Based on Space-Borne NTN Networks
### Enhanced Data Transmission Reliability
The study in [106] highlights the transformative potential of satellites to significantly enhance the performance of IoRT networks, enabling seamless connectivity and robust data transmission across remote areas. By leveraging a Reinforcement Learning (RL) framework, the authors effectively address the challenge of optimizing resource allocation and IoRT data scheduling in dynamic and unpredictable environments. To overcome the limitations of traditional RL algorithms, they propose customized feature functions tailored to the unique characteristics of satellite-based IoRT networks and employ function approximation techniques to enhance the accuracy of resource allocation decisions. Their proposed state-action-reward-state-action-based RL strategy proves highly effective in simulations. The utilization of a linear combination of proposed features specifically designed for decision-making and the prevention of battery overflow results in effective energy management and reduced energy consumption. Excessive propagation delay is also a significant challenge in satellite-based IoT (S-IoT). In this particular context, conventional Hybrid Automatic Repeat request (HARQ) strategies are frequently unsuccessful as a result of limited feedback efficiency. To tackle this challenge, a novel Network Code HARQ (NC-HARQ) transmission protocol is introduced in [107]. Enabling efficient multi-hop communication is its primary objective, particularly in S-IoT environments where feedback mechanisms are inadequate or absent. In order to evaluate the performance of the NC-HARQ protocol in terms of Age of Information (AoI), a four-state Markov model is utilized. This model facilitates the derivation of closed-form expressions for the mean AoI in the context of end-to-end two-hop transmission. The results of the simulation illustrate that the NC-HARQ protocol is more effective than several modern HARQ schemes, as indicated by the significantly decreased average AoI levels. In [108], the authors highlight the very limited choice of available technologies and the challenges of developing data collection and control systems in remote areas. They conduct a critical review and analysis of various protocols and technologies used for IoT data transmission, and they propose a hybrid IoT-satellite network to address these limitations. This network intends to gather data employing a terrestrial LoRa LPWAN, with backhaul connectivity provided via the Iridium satellite system. Different data presentation formats for low-speed satellite channels were evaluated through simulations. Furthermore, the authors introduce GDEP (Gateway Data Encoding and Packaging), a data encoding and packaging technique that is able to reduce the number of Short Burst Data (SBD) containers, improving network efficiency. In order to improve the efficiency of accessing and utilizing resources in a massive machine-type communication scenario, the authors of [109] suggest a collision avoidance technique as the first step in random access for LEO satellite Internet of Things. The proposed method allows for quick identification of collisions and accurate estimation of load while also being resistant to non-orthogonal interference. An analysis is performed on the probability of detecting the preamble, the probability of detecting collisions, and the accuracy of load monitoring. This analysis results in the development of an optimal set of probabilities for selecting preambles, which maximizes the precision of load monitoring. To address the issue of data staleness caused by the slow sensor transmission rate and the high bit error rate of the satellite-to-ground link, ref. [110] introduces an age-optimalhybrid temporal-spatial generalized deduplication and automatic repeat request (HARQ-GD) protocol designed for high-sampling data collection in the satellite-integrated Internet of Things. By integrating temporal and spatial data correlations, encoding and decoding algorithms, and packet format optimization, the HARQ-GD protocol successfully mitigates data staleness.