Statistical EIRP Calculation for Satellite Transponder Capacity
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Solution Overview
Problem
Current systems for providing live television programming and bi-directional data services to mobile platforms, such as aircraft, face inefficiencies in managing aggregate emissions to protect co-frequency fixed satellite service systems from interference, leading to artificially high error calculations that decrease transponder capacity and fail to account for improved technological reductions in errors.
Innovation Solution
A method that determines the probability distribution of EIRP for each mobile platform and calculates an aggregate off-axis EIRP density envelope for a predetermined probability level, allowing for more accurate error accounting and reduced margins, thereby optimizing transponder capacity and accounting for varying error characteristics across different terminals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fixed margins are used for each error source based on worst-case scenarios, then reliability of EIRP control is improved, but transponder capacity decreases due to artificially high error calculations
Solution Approach 1:
The patent changes the parameter approach from fixed worst-case margins to statistically derived margins based on actual error probability distributions. By modeling the statistical characteristics of pointing errors, power control errors, and antenna pattern errors, the system calculates margins that reflect real-world performance rather than theoretical worst cases, thereby increasing transponder capacity while maintaining reliable EIRP control
Solution Approach 2:
The patent implements feedback by using measured and modeled error statistics from actual system operation to continuously refine the margin calculations. The system monitors error characteristics and adjusts the statistical parameters accordingly, allowing the margins to adapt to actual system performance and technological improvements rather than relying on static worst-case assumptions
2Object-affected harmful factors
If conservative fixed error rates are overlaid for each mobile platform, then protection against interference is improved, but system efficiency decreases due to inflated error rates
Solution Approach 1:
The patent transforms the approach by changing from fixed conservative error rates to dynamically calculated statistical parameters based on actual error distributions. By modeling the probability distributions of various error sources and combining them statistically rather than conservatively, the system achieves adequate interference protection with significantly reduced margin inflation, thereby improving overall system efficiency
3Reliability
If worst-case location and attitude margins are computed, then reliability of off-axis EIRP density calculation is improved, but device complexity increases due to repeated calculations
Solution Approach 1:
The patent changes the calculation methodology from deterministic worst-case computations to statistical parameter modeling. By characterizing errors through probability distributions and using statistical combination methods, the system achieves reliable off-axis EIRP density calculations with reduced computational burden, avoiding the need for repeated worst-case scenario analyses across all possible locations and attitudes
Data Source
AI summary
In a system for providing data content to and from a plurality of mobile platforms where each of the mobile platforms transmits a return link having an EIRP to a predetermined location via a satellite-mounted transponder, a method for controlling an EIRP of the aggregate return link emissions of the mobile platforms. The method includes the steps of determining a probability distribution of the EIRP of the return link for each of the mobile platforms; and determining a probability distribution of the EIRP for the aggregate return link emissions using the probability distributions of the EIRP of the return link for each of the mobile platforms; determining an aggregate off-axis EIRP density envelope for a predetermined probability level and the probability distribution of the EIRP for the aggregate return link emissions.