# Hierarchical Resource Management for Mega-LEO Satellite Constellation
## 4 Hierarchical Resource Management Architecture
Subsequently, we will optimize the transmission of these data through advanced scheduling algorithms and network protocols to achieve robust QoS guarantees. Similar to terrestrial mobile base stations (BSs), SBSs are the primary entities responsible for resource management in the MLSCS. They directly schedule and employ resources such as time slots, directional beams, radio spectrum, and power to provide access to services. Furthermore, unlike terrestrial mobile communication systems, the MLSCS exhibits the following characteristics:  
* Compared with terrestrial mobile base stations, LEO satellites have distinct characteristics. They move quickly and cover large areas. However, LEO satellites have a very short residence time over any given location, meaning their service area changes rapidly. This leads to frequent changes in the users they can serve. * Service demands are not uniformly distributed across all areas. In hotspots or emergent situations, it is necessary to implement multi-satellite collaboration to provide enhanced services, such as increased capacity, improved coverage, or larger data rates. * User handover between beams (the areas of coverage for individual satellite signals) and satellites is not solely determined by signal strength measurements. It also involves multi-satellite resource negotiation, which takes into account various factors such as satellite availability, capacity, and service priorities. * Dynamic change in the areas covered by LEO satellites makes status data, such as spatial spectrum and service demands, incomplete or non-real-time (NRT), which makes resource optimization and scheduling more difficult. * Due to their short residence time, SBSs have insufficient cognitive ability regarding propagation circumstances and service situations. Therefore, it is necessary to coordinate multi-satellite cognition to support system resource scheduling. * The most critical problem is that SBSs have limited resources, including computing, caching, and transmission resources. To achieve optimal system resource scheduling, terrestrial assistance is necessary. However, if NCC pre-schedules all resources, the resulting processing delays and complexity would be too high to meet real-time service demands. Based on the above analysis, the hierarchical resource management architecture of MLSCS is proposed here, to achieve optimal scheduling of system resources and fulfill real-time service demands. The radio resource scheduling architecture within MLSCS is divided into three layers, as shown in Figure 3.
* Radio resource scheduling center (RRSC). It is responsible for system resource scheduling, integrating several functions: (1) It collects network situation information, including details on global telecommunication policies and available resources. (2) Using historical data, it optimizes service area planning and global spectrum scheduling. (3) It schedules SBSs for hotspot and emergent areas to ensure coverage and capacity. (4) It configures the resource scheduling strategy and guides SBSs in scheduling resources efficiently. * Satellite resource scheduling (SRS). SRS is located at the SBSs and is user-oriented. Taking the configuration of the RRSC as constraints, the beams, slots, spectrum and power (modulation parameters) are scheduled at SBSs, considering user demand and capacity to provide access services for users. At the same time, the downlink data are scheduled to realize the dissemination of user data according to priority. * User service scheduling (USS). The scheduling of terminal service data occurs at user terminals. Based on their service demands, user terminals submit resource requests to SBSs. The SBSs, in turn, prioritize and manage links and data based on the QoS requirements, which include factors such as latency, bandwidth, and reliability. This management ensures that different service types, such as voice, video, and data, receive the necessary resources to meet their specific demands, thereby achieving resource optimization for user terminals.