## 3 The Three-Segment Optimization Architecture in LEO  
A typical LEO satellite network has a three-segment architecture:  
* **Ground Segment** includes the Ground-Station (GS) infrastructure, which serves as a control unit for the satellite constellation and manages internal parameters;
* **Space Segment** includes the satellite constellation (as well as the propagating signals from satellite to ground);
* **User Segment** refers to any and all applications that the system serves (i.e., cellular networks, PNT applications, transportation, UAV etc.) as well as to any LEO receiver. Figure 1 provides the 'big picture' regarding this architecture. The space segment is comprised of satellites in the sky. In LEO constellations, these satellites can carry omnidirectional or directional (beamforming) antennas. The latter case is the one most encountered in LEO mega-constellations nowadays, and it is the one illustrated in Figure 1, where each satellite beam can serve a certain end user. The ground segment hosts the GS satellite network and is complemented by a number of GSs, placed all over the Earth, with the main tasks of monitoring, managing, and controlling the platforms and the signals sent by the satellites. The ground segment typically does not interact with the user segment, but only with the space segment. Last but not least, the user segment comprises all user devices enabled with a LEO-supporting chipset; such devices can serve a myriad of applications needing communication, navigation, and/or sensing capabilities. On-board LEO chipsets on such user devices can also support integration with other chipsets, such as 5G chipsets, IoT chipsets, or Inertial Navigation Sensors (INS). In the case of Earth Observation constellations, the GS network is used mostly for sensor-data downloads. In this paper, we assume this three-segment architecture applies to all LEO networks. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Reference**} & **Space Segment** & \begin{tabular}{c} **Ground** \\ **Segment** \\ **Optimization** \\ **Aspects** \\ \end{tabular} & \begin{tabular}{c} **User Segment** \\ **Optimization** \\ **Aspects** \\ \end{tabular} & LEO **Networks** & \
\begin{tabular}{c} **Autonomous** \\ **Vehicles** \\ \end{tabular} &
\begin{tabular}{c} **Cost and/or** \\ **Coverage** \\ **Aspects** \\ \end{tabular} \\ \[PERSON] et al., 2018 [7] & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) \\ \[PERSON] et al., 2018 [10] & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) \\ \[PERSON] et al., 2019 [11] & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) \\ \[PERSON] et al., 2020 [12] & \(\bigtriangleright\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigtriangleright\) & \(\bigtriangleright\) \\ \[PERSON] et al., 2020 [13] & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) \\ \[PERSON] et al., 2020 [14] & \(\bigtriangleright\) & \(\bigcirc\) & \(\bigtriangleright\) & \(\bigtriangleright\) & \(\bigcirc\) & \(\bigtriangleright\) \\ \[PERSON] et al., 2020 [15] & \(\bigtriangleright\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) \\ \[PERSON] et al., 2020 [16] & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) \\ \hline [PERSON] et al., 2021 [17] & \(\bigtriangleright\) & \(\bigtriangleright\) & \(\bigtriangleright\) & \(\bigtriangleright\) & \(\bigcirc\) & \(\bigcirc\) \\ \hline [PERSON] et al., 2021 [18] & \(\bigtriangleright\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) \\ \hline Our survey & \(\bigtriangleright\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) & \(\bigcirc\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Related Work in the Literature and Comparison with Our Survey.