The multi-satellites cooperative transmission can effectively increase the data rate that can be achieved by internet of things (IoT) terminals. However, the dynamic characteristics brought by low Earth orbit (LEO) satellites will seriously decrease the data rate and make the data rate fluctuate. In this paper, dual-stream transmission and downlink power control for multiple LEO satellites-assisted IoT networks are investigated. To mitigate the effects of the frequency offset caused by different LEO satellites, a multi-satellites synchronization scheme is proposed. Then, different power control schemes are given to resist the data rate fluctuation during the transmission. The simulation results show that the proposed schemes can effectively compensate for the varied frequency offset and keep the data rate stable.
Satellite IoT networks (S-IoT-N), which have been a hot issue regarding the next generation of communication, are quite important for the coming era of digital twins and the metaverse because of their performance in sensing and monitoring anywhere, anytime, and anyway, in more dimensions. However, this will cause communication links to face greater traffic loads. Satellite internet networks (SIN) are considered the most possible evolution road, possessing characteristics of many satellites, such as low earth orbit (LEO), the Ku/Ka frequency, and a high data rate. Existing research on load balancing schemes for satellite networks cannot solve the problems of low efficiency under conditions of extremely non-uniform distribution of users (DoU) and dynamic density variances. Therefore, this paper proposes a novel load balancing scheme of adjacent beams for S-IoT-N based on the modeling of spatial–temporal DoU and advanced GA. In our scheme, the PDF of the DoU in the direction of movement of the SSP’s trajectory was modeled first, which provided a multi-directional constraint for the non-uniform distribution of users in S-IoT-N. Fully considering the prior periodicity of satellite movement and the similarity of DoU in different areas, we proposed an adaptive inheritance iteration to optimize the crossover factor and mutation factor for GA for the first time. Based on the proposed improved GA, we obtained the optimal scheme of load balancing under the conditions of the adaptation from the local balancing scheme to global balancing, and a selection of Ser-Beams to access. Finally, the simulations show that the proposed method can improve the average throughput by 3% under specific conditions and improve processing efficiency by 30% on average.
Satellite Internet Network (SIN) will be the next heat issue in the ongoing research of 6G. The users need to keep operating handover between different beams or different satellites in an extremely high frequency for the satellite moving at a high speed in Low Earth Orbit (LEO). Traditional handover thresholds (HT) which are determined by singer factor (such as reference signal receiving power or quality) have serious performance degradation in the scenarios of SIN. It is also hard to correctly describe and model the correlations between multi factors. This paper proposed a novel method to determine the handover threshold based on a reconfigurable factor graph (FG) for LEO SIN. First, we introduce a tensor to make a factor graph with the ability to reconfigure all the factors and correlations in the factor graph, which can solve the problems of sharp changes between factors. Then, we proposed a method to determine the HT for SIN based on reconstructed FG. The simulations show the proposed HT method has better performance than those of RSRQ and elevation.
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