## 5 Simulation Results and Analysis  
In this section, MATLAB is used to simulate and analyze the performance of the proposed ADMM-based resource allocation and interference coordination strategy. The simulated network consists of multiple edge nodes and backhaul networks, with edge networks composed of multiple users, access points, and small data centers. Users communicate with access points via wireless links, while access points and small data centers are connected via wired links. The backhaul network comprises multiple LEO and GEO satellites, where access points can request resources from the cloud via the satellite network or communicate with other access points. The satellite-earth propagation was modeled to accurately reflect real-world communication conditions. The following factors were considered. Free-space path loss (FSPL) is calculated as follows. \[FSPL(dB)=20\log_{10}(d)+20\log_{10}(f)+32.45 \tag{23}\]  
where \(d\) is the distance between the satellite and the ground station in kilometers, and \(f\) is the frequency in MHz. Atmospheric attenuation and rain attenuation are modeled based on using the ITU-R P.618-13 recommendation to account for signal degradation [38]. The network service nodes are pre-loaded with video resources from the cloud, cached within the network. Each user randomly requests a video file, and the following parameters, based on ITU's EPFD limits, are used for the simulation, as shown in Table 3. The bandwidth values for LEO and GEO satellites were chosen based on the frequency bands typically allocated for satellite communications, such as the Ku-band (12-18 GHz) and Ka-band (26.5-40 GHz), as per ITU-R recommendations. These bands are widely used in satellite networks for high-speed data transmission. The transmission power levels were selected to balance the trade-off between maintaining adequate signal strength and minimizing interference. The values align with power levels reported in recent studies on LEO-GEO coexistence. In this paper, the specific values chosen for the satellite parameters (Table 3) reflect realistic operational thresholds and commonly referenced industry standards. For instance, the LEO orbit height of 1200 km represents a practical trade-off between reduced latency and wide coverage, aligning with typical commercial LEO constellations; the GEO orbit height of 35,786 km corresponds to the standard geostationary ring, ensuring minimal relative orbital motion from the ground perspective. Similarly, the inclination angle of 87\({}^{\circ}\) approximates near-polar orbits often employed to achieve global coverage. Antenna gains for both LEO and GEO satellites (25 dBi) and ground stations (45 dBi for LEO, 30 dBi for GEO) are derived from typical engineering designs in the literature, balancing transmit power demands with hardware constraints. These selections ensure that our simulation environment is both realistic and representative of state-of-the-art satellite network deployments, thus strengthening the applicability of our resource allocation and interference coordination findings. In this paper, we compare our proposed scheme with a baseline and other peers [11; 39; 40]. * Proposed: the scheme proposed in this paper. * Cache only: the scheme proposed in [39] where only cache is deployed. * Satellite only: the scheme proposed in [11] where only the satellites have caching and computing capability. * Ground only: the scheme proposed in [40] where only the satellites have caching and computing capability. * Baseline: the scheme that the network nodes only provide forwarding service. Figure 4 shows the average user vMOS under different normalized computing capacities. The normalized computing capacity refers to the ratio of the tested computing resource capacity to the default value. As seen in the figure, as the computing capacity increases, the overall performance of the network improves.