# Intelligent Beam-Hopping-Based Grant-Free Random Access in Secure IoT-Oriented Satellite Networks
## 3 Beam-Hopping-Based Grant-Free Random Access
### Optimization of Activation Factors by Exploiting Space-Time Distribution Constraint
The theoretical value mentioned is the lowest access delay under different active probabilities \(v\) obtained through multiple different simulations using three frequency-hopping access methods. The proposed scheme in this paper outperforms 2-step RA in terms of delay under all device numbers, especially in the low-to-medium access probability region (0.1 to 0.5). However, when the access probability continues to increase, the delay of BH-GFRA gradually stabilizes, but it is still higher than the theoretical performance of the proposed scheme. Regardless of the number of devices, the theoretical delay of the proposed scheme is significantly lower than that of the 2-step RA and BH-GFRA schemes. The performance advantage of the proposed scheme is more obvious when the number of devices is small, while the increasing trend of its delay is effectively suppressed when the number of devices is large, showing strong robustness. Figure 5 shows the trend of the access success rate with the normalized load for different numbers of devices and access algorithms. The theoretical analysis in the figure compares two access algorithms (BH-GFRA and 2-step RA). The theoretical access success rate curves show a decreasing trend with device numbers of 1000, 500, and 100, but overall maintain a high success rate, especially in the low-load area (normalized load close to 0.1 to 0.4), where the access success rate is close to 1. As the load increases, the theoretical access success rate gradually decreases, and the success rate increases slightly when the number of devices increases. When the BH-GFRA algorithm is under 1000 devices, its access success rate gradually decreases. When the load is high (e.g., the normalized load is above 0.7), its \begin{table}
\begin{tabular}{l l} \hline \hline
**Parameter** & **Value** \\ \hline Height of orbit & 600 km \\ Ka band & 20 GHz \\ Number of device & 100, 500, 1000 \\ Time slot duration & 10 ms \\ Simulation duration & 10 min \\ Number of orbits & 30 \\ Number of satellites & 80 \\ Bandwidth & 20 MHz \\ Number of beam positions/GFRA group & 24 \\ Number of preambles & 64 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Simulation parameters. Figure 6 presents a comparison of the block error rate (BLER) for all schemes when the load probability is optimized for different service iterations under time and space constraints. Figure 5(a) illustrates that the activation probability optimization for the sparse data transmission service is approximately 0.3, which indicates a relatively low device activity level. In this instance, the BLER of the proposed orthogonal frequency-hopping scheme is increased in comparison with the packet, existing grant-based RA, and random frequency-hopping systems, respectively. In contrast, Figure 5(b) illustrates that for the time-sensitive transmission service, the activation probability is approximately 0.7 after iteration, indicating a relatively high device activity level. In this instance, the BLER of the proposed orthogonal frequency-hopping scheme is superior to that of the random frequency-hopping and packet schemes, exhibiting an improvement of 1.2 and 1 dB, respectively. It is noteworthy that in Figure 5(b), the BLER of the existing grant-based RA tends to stabilize when the signal-to-noise ratio reaches a certain threshold. This indicates that improvements in signal quality cannot increase the capacity of the access framework. This also reflects the higher upper limit capacity of the framework proposed in this paper. Figure 5: Access success rate. Figure 6: BLER for different values of \(v\). ## 6 Conclusions

This research primarily examines the BH-GFRA architecture for extensive device access in the satellite Internet of Things (IoT) context. This study examines the modification of user data transmission techniques via the hopping pattern of the hop beam and various resource-hopping methods, aiming to minimize collision risk while adhering to restrictions of access latency and access success rate.