Self-Optimizing Mobile Satellite Resource Allocation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current Mobile Satellite Systems (MSS) face labor-intensive manual interventions to address transient traffic congestion, which hampers quick response to demand fluctuations, leading to inefficient resource allocation and network instability.
Innovation Solution
A self-optimizing MSS network system that uses automated methods to dynamically reallocate resources, including carrier shaping, cell shaping, cell type selection, and beam shaping, to automatically adjust Radio Access Network resources based on demand, thereby alleviating congestion without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual intervention by system operators is used to respond to traffic congestion, then the system can adapt to demand changes, but the response time is slow and labor intensive
Solution Approach 1:
The system performs self-optimization by automatically detecting congestion conditions and reallocating resources without requiring manual intervention from operators. The congestion detection module identifies congested cells, and the resource reallocation module automatically adjusts RAN resources, enabling the system to serve itself and eliminate human delay in responding to traffic changes.
Solution Approach 2:
The system implements a closed-loop feedback mechanism where the congestion detection module continuously monitors network conditions, feeds this information to the resource reallocation module, which then adjusts resources and monitors the impact. This feedback loop enables rapid automatic response to congestion without manual intervention.
2Productivity
If manual intervention by system operators is used to reallocate resources, then resource allocation can be optimized, but the process is labor intensive and time consuming
Solution Approach 1:
The system automatically performs resource reallocation through the resource reallocation module, which receives congestion information and autonomously adjusts RAN resources without operator involvement. This self-service capability maintains optimization effectiveness while eliminating the labor-intensive aspect of manual resource management.
Solution Approach 2:
The patent replaces the mechanical process of manual operator intervention with an automated electronic system. The congestion detection module, resource reallocation module, and monitoring mechanisms work together as an automated control system, substituting human operational complexity with computational algorithms that execute resource reallocation decisions automatically.
3Device complexity
If open loop approach to RAN resource allocation is used, then the system structure is simple, but the system cannot quickly respond to transient congestion periods
Solution Approach 1:
The system transitions from an open-loop approach to a closed-loop feedback system. The congestion detection module continuously monitors network conditions and feeds real-time information to the resource reallocation module, enabling the system to detect and respond to transient congestion periods quickly while maintaining relatively simple system architecture through modular design.
Solution Approach 2:
The system implements dynamic resource reallocation where RAN resources are automatically adjusted in response to changing traffic conditions. The resource reallocation module dynamically modifies resource allocation based on real-time congestion detection, enabling quick response to transient periods while keeping the overall system structure simple through automated decision-making.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Systems, methods, and apparatus for self-optimizing Mobile Satellite System (MSS) resources are disclosed. In one or more embodiments, the disclosed method involves determining, with at least one processor, a communication demand for at least one cell in a MSS network. The method further involves determining, with at least one processor, whether the communication demand for at least one cell exceeds the capacity threshold for at least one cell. Further, the method involves reallocating, with at least one processor, when the communication demand for at least one cell exceeds the capacity threshold for at least one cell, at least a portion of the MSS resources such that at least one cell is able to meet the communication demand.