Quantitative Assessment of Technology Infusion in Communications Satellite Constellations

1. Quantitative Assessment of TechnologyInfusion in Communications SatelliteConstellations Unit 3 Olivier de Weck and Darren Chang, MIT, U.S.A. Ryutaro Suzuki, CRL, Tokyo, Japan Eihisa Morikawa, NeLS, Kanagawa, Japan 21st International Communications Satellite Systems Conference, 15-19 April 2003, Yokohama, Japan

2. Outline • Introduction and Motivation • Previous Work in Technology Assessment • Quantitative Technology Infusion Assessment Methodology • Application to Satellite Communications Constellations • Conclusions • Future Work

3. Motivation • The architecture of satellite communications systems (concept) must be carefully selected • Selection of architectures can be done quantitatively based on performance, cost and capacity predictions – see AIAA-2002-1866 • A number of new technologies are currently under development for GEO and LEO Systems, e.g. • Large Deployable Reflector (LDR) Antennas • Optical Inter-satellite Links (OISL) • System Designers/Architects must often choose between competing technologies – need a quantitative method • Generally, better understand the relationship between architectures and technologies

4. Design (Input) Vector Simulator Performance Capacity Cost Conceptual Design Space Can we quantify the conceptual system design problem using simulation and optimization?

5. Key Idea: Pareto Impact

6. Previous Work • Metrics for comsat architecture evaluation: “cost per function” – CPF – [$/min] at a fixed data rate R, BER pb and link margin (Hastings, Shaw….) • Architecture Evaluation and Selection using MDO (multi-disciplinary design optimization) – Miller, Jilla, de Weck • Research in new generations of satellite constellations (e.g. NeLs, R. Suzuki) and new technologies • Technology assessment proposed by Management of Technology (MOT): Utterback, van Wyk, Henderson and Clark • Technology Selection: Mavris, DeLaurentis > Perceive a missing link between architecture evaluation and technology selection

7. Assumptions • Possible to create “high-fidelity” simulations of satellite communications systems during conceptual design • Performance per channel is fixed: • Data Rate • Bit-Error-Rate • Link Fading Margin • Tradeoff between system capacity and lifecycle cost • Architectures are realizable with existing, mature technologies

8. Proposed Methodology

9. Steps 1-3 Step 1: Baseline Trade Space Exploration - Obtain Baseline Pareto Frontier Po Step 2: Technology Identification, Classification, Modeling - Understand technology dependencies: Tc, Td - Technology modeling : physics based, prototype data, empirical relationships (expert interviews) Step 3: Technology Infusion Interface Development

10. Steps 4-6 • Step 4: Individual • Technology Assessment • Step 5: Assessment of allowable combinations of technologies • Step 6: Comparison and • Interpretation • - based on Pareto Impact Metrics (4)

11. Application: LEO Com Sat LEO Constellation 50 satellites 5 planes h=800 km

12. Benchmarking Benchmarking : validating a simulation by comparing the predicted response against reality.

13. Design Trade Space Design Vector 1728 Full Factorial Combinatorial Design Space

14. Baseline Case Baseline Design Space – Uses only Existing, Mature Technologies Channel Perf: R=4.8 [kbps] pb=0.001 LM=16 [dB]

15. Technology Portfolio Technology Dependency Matrix T1: Optical Inter-Satellite Links (OISL) T2: Asynchronous Transfer Mode (ATM) T3: Large Deployable Reflectors (LDR) T4: Digital/Analog Beamforming (DBF)

16. Example: Impact of LDR Large Deployable Reflectors (LDR) ETS-VIII E.g. for DA=6[m] -> GT~39 [dBi], l=0.19[m], TFU=2.45 [M$]

17. Pareto Impact – Example LDR Po is the normalized Pareto front with baseline technologies alone. P3 is the normalized Pareto front with LDR. Decreased utopia point distance

18. LDR has a large effect on dmin and CPF, but caution… benefits only come in for high capacity/throughput. OISL in isolation shows less benefit, however the system here is narrowband (4.8 kbps), expect benefit for broadband. All technologies increase throughput, good for NeLS ! Overview Results - MP

19. Conclusions • Presented a methodology for quantitatively assessing technology impact on Communication Satellites • Choose between mature, existing technologies versus newly emerging, competing technologies • Technology portfolio & technology investment decisions • Use simulation to predict performance, cost and capacity for a set of candidate architectures • Careful benchmarking required • Modular simulation architecture eases investigation of a large set of technologies • Current technologies under development for NeLS make sense for broadband, multimedia system • Engineering Systems Industry Study will be available

20. Future Work • “Harden” and verify this methodology by deploying in an industrial/satellite manufacturer setting, apply to GEO • Uncertainty in effect on Pareto front P due to technology maturity – e.g. measured via NASA’s Technology Readiness Levels (TRL) – probabilistic • Expand work to more than two (2) objectives • How to deal with “disruptive” technologies that enable new architectures – in that case don’t have a baseline Pareto front to compare to, e.g. introduction of ISL when only “bent-pipe” was known. • Understand relationship between Pareto Impact metrics and technology obsolescence