## 3 The Three-Segment Optimization Architecture in LEO
Each of the segments has processes that require optimization; Table 2 summarizes the optimization-related problems that have been actively addressed in the scientific community in recent years for each segment of the above-mentioned architecture. These optimization problems are shown together with examples of optimization objectives, parameters of interest, as well as common metrics used in the optimization process. An important note is that, while the optimization objective of each problem varies, any optimization objective can be categorized according to the target problem, e.g., as shown in Table 2.  
Below, we group the optimization criteria related to LEO networks under three main optimization classes. We show some examples for each category, and we specify if the example cost functions are to be maximized (max.) or minimized (min. ):  
1. **Coverage-related aspects:** * Min. Satellite Revisit Time: This revisit time is the time elapsed between consecutive observations of the same point on Earth by a satellite. The lower this time, the better the performance. * Max. Satellite Availability: The availability refers to the percentage of time that the service performance provided by the satellite reaches the user equipment in a desired location. Therefore, the higher the availability, the better the system performance. * Min. Satellite Orbit Drift: Deviation of the satellite from the planned orbit due to atmospheric drag and gravity. 2. **Cost-related aspects:** * Min. Production Cost: This refers to the production and maintenance cost of satellites, GS, and tools; the lower, the better. * Min. Launch Cost: This is the cost related to launching satellites to the desired orbits; the lower, the better. * Min. De-orbiting Cost: This is the cost to de-orbit a satellite (i.e., take satellite out of the constellation) after its lifespan ended; the lower, the better. Figure 1: Typical LEO Network Three-Segment Architecture. Max. Satellite Lifespan: This is the time a satellite spends operating in acceptable conditions; the higher, the better. 3. **Performance-related aspects:** * Min. Latency: The time delay before a full data transfer takes place for a communication, sensing, or navigation task. The lower the time, the better the performance. * Max. Stability: The property that is inversely related to the need for change within the system. The higher the stability, the better the performance. * Max. Throughput: The amount of data (signals, supported number of users, etc.) passing through the system; it is of particular importance for communication-related applications, and typically, the higher, the better. However, some navigation and sensing applications do not require high throughputs; in such cases, throughputs targets may be removed from the optimization parameters. * Max. Signal-to-Noise Ratio (SNR) or C/N\({}_{0}\): SNR and \(C/N_{0}\) are measures of the signal quality after unwanted modifications that the signal may suffer during transmission, capture, storage, conversion, and processing. The higher the SNR and C/N\({}_{0}\), the better; a minimum value for SNR or \(C/N_{0}\) typically needs to be guaranteed for good functioning of the system. While Table 2 cannot cover every possible problem related to the LEO segments, it provides a very good example of both the scope and the complexity of the entire system's optimization. This paper focuses on the example problems listed Table 2 and on various aspects related to those problems, with the note that additional optimization problems such as those related to packet routing and medium access control may exist, but they fall outside the scope of the current paper. Figure 2 provides a map for the optimization processes with respect to each of the three architectural segments, with a focus on autonomous transportation regarding the user segment.