Distributed Massive MIMO for LEO Satellite Handover Management
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Solution Overview
Problem
Low Earth Orbit (LEO) satellite networks face challenges such as high handover rates, latency, and limited connectivity due to the mobility of LEO satellites, which affects network performance and quality of service (QoS) for user terminals.
Innovation Solution
A distributed massive multiple-input multiple-output (DM-MIMO) architecture with a cross-layer design and AI-based implementation for power allocation and handover management, optimizing power allocation and handover processes to reduce handover rates and enhance network throughput while considering the quality-of-service demands and power capabilities of LEO satellites.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If LEO satellites are used for communication networks, then connectivity in remote and rural areas is improved, but handover rates increase due to satellite mobility
Solution Approach 1:
The patent segments the satellite network into distributed clusters, where each cluster is managed by a super satellite node. This segmentation allows for localized handover management within clusters, reducing the overall handover rate by keeping user terminals connected to satellites within the same cluster rather than requiring handovers across the entire network.
Solution Approach 2:
The patent introduces super satellite nodes as intermediaries that manage clusters of satellites. These super satellite nodes handle handover coordination and power allocation, acting as mediators between individual satellites and user terminals, thereby reducing direct handover requirements and improving connection stability.
2Productivity
If distributed massive MIMO architecture is implemented, then spectral efficiency is improved, but device complexity increases
Solution Approach 1:
The distributed massive MIMO system is segmented into multiple clusters, each managed by a super satellite node. This segmentation distributes the computational complexity across multiple nodes rather than concentrating it in a single controller, making the overall system more manageable while maintaining high spectral efficiency through coordinated multi-point transmission.
Solution Approach 2:
The patent implements dynamic power allocation and cluster formation that adapts to changing network conditions. The super satellite nodes dynamically adjust power levels and reconfigure clusters based on satellite positions and user terminal requirements, allowing the system to maintain optimal spectral efficiency while managing complexity through adaptive rather than static configurations.
3Duration of action of moving object
If handover management is optimized, then service time is extended, but power allocation complexity increases
Solution Approach 1:
Super satellite nodes serve as intermediaries that centralize power allocation decisions for their respective clusters. This intermediary approach simplifies power management by consolidating control at the super satellite node level rather than requiring complex distributed power allocation across all satellites, while still extending service time through coordinated handover management.
Solution Approach 2:
The patent implements self-service mechanisms where super satellite nodes autonomously perform power allocation and handover management within their clusters without requiring constant external intervention. This self-service capability reduces the operational complexity of power allocation while maintaining extended service times through automated decision-making algorithms.
Data Source
AI summary
Satellites provide connectivity in remote and rural areas as well as providing applications and services elsewhere on earth and in space. Existing satellite networks will be increasingly augmented by ultra-dense deployments of interconnected satellites providing low Earth orbit (LEO) constellations. However, such satellites only offer short-term line-of-sight access requiring ongoing handovers during the duration of a terminal's access. Accordingly, to exploit these LEO constellations the inventors have established methodologies exploiting distributed massive multiple-input multiple-output technology for a user terminal to be connected to a cluster of LEO satellites. Further, distributed joint power allocation and handover management techniques are outlined for improving the power allocation and handover management processes in a cross-layer manner such that enhanced network throughput and reduced handover rate are provided whilst taking into account quality-of-service demands of terminals and the power capabilities of the LEO satellites.