Chapters authored
War-Gaming Applications for Achieving Optimum Acquisition of Future Space Systems By Tien M. Nguyen, Andy T. Guillen, Sumner S. Matsunaga, Hien T.
Tran and Tung X. Bui
This chapter describes an innovative modeling and simulation approach using newly proposed Advanced Game-based Mathematical Framework (AGMF), Unified Game-based Acquisition Framework (UGAF) and a set of War-Gaming Engines (WGEs) to address future space systems acquisition challenges. Its objective is to assist the DoD Acquisition Authority (DAA) to understand the contractor’s perspective and to seek optimum Program-and-Technical-Baseline (PTB) solution and corresponding acquisition strategy under both the perspectives of the government and the contractors. The proposed approach calls for an interdisciplinary research that involves game theory, probability and statistics, and non-linear programming. The goal of this chapter is to apply the proposed war-gaming frameworks to develop and evaluate PTB solutions and associated acquisition strategies in the context of acquisition of future space systems. Our simulation results suggest that our optimization problem for the acquisition of future space systems meets the affordability and innovative requirements with minimum acquisition risk.
Part of the book: Simulation and Gaming
Application of Random Walk Model for Timing Recovery in Modern Mobile SATCOM Systems By Tien M. Nguyen, Hung H. Nguyen, Tom Freeze and Andy Guillen
In a modern mobile satellite communication (SATCOM) system, a ground terminal receiver receives a radio frequency signal that is demodulated to generate a baseband digital signal waveform containing a self-clocking bit stream of digital data. The received baseband digital signal waveform is recovered and tracked using a timing recovery loop (TRL). The traditional TRLs use early-and-late gates, digital transition tracking, filter-and-square, and delay-and-multiply functions. In bit timing detection, the bit stream is self-clocking and the timing differential dithers about correct bit timing in the TRLs. For mobile satellite communication environments, the traditional TRLs drop lock when the loop signal-to-noise ratio (SNR) is smaller than a threshold value or the residual Doppler frequency is larger than the operating loop bandwidth. After dropping lock, the traditional TRLs experience long hang up time due to the need to reacquire the timing pulses. Recently, random walk filters (RWF) have been adapted to improve the bit clock locking stability and are applied to recover bit timing information of a digital data stream. This chapter describes random walk model for timing jitter and discusses how RWF solution can address the timing recovery challenges in mobile satellite communication environments.
Part of the book: Recent Trends in Communication Networks
Future Satellite System Architectures and Practical Design Issues: An Overview By Tien M. Nguyen
This chapter discusses existing and future trends on the design and build of “Modular” and “Open” satellite Bus and mission payload along with practical design issues associated with the use of Modular Open System Approach (MOSA). Existing modular Bus and mission payload architectures for typical commercial, civilian, and military satellite systems will be discussed. The chapter provides space industry views on “Open” versus “Close” interfaces design and addresses the challenges associated with open interfaces using Open System Architecture (OSA) approach using MOSA principles. The system interfaces discuss in this chapter include (i) internal to satellite Bus and mission Payload (PL), (2) between satellite Bus and mission payload, and (3) external to both satellite Bus and mission payload.
Part of the book: Satellite Systems
SOS Enterprise, SOSE CONOPS, SOSE Architecture Design Approach: A Perspective on Space and Airborne Systems By Tien M. Nguyen
The objective of this chapter is to (i) define System-of-Systems Enterprise (SOSE), SOSE Concept of Operations (CONOPS), and SOSE Architecture (SOSEA) CONOPS assessment, and (ii) discuss their differences using examples from existing space and airborne systems. The chapter also describes the SOS design challenges and presents an SOSE Architecture design approach addressing these challenges. In addition, DOD Architecture Framework Version 2.02 (DODAF-v2.02) views will be discussed along with a recommendation for a set of key DODAF views to capture system architecture artifacts with practical examples involving SOS Enterprise architectures for notional space-based communications system and manned airborne Intelligence, Surveillance, and Reconnaissance (ISR) platform.
Part of the book: Systems-of-Systems Perspectives and Applications
System-of-Systems Enterprise CONOPS Assessment Decision Support Tools By Thomas O. Freeze, Tien M. Nguyen and Charles H. Lee
This chapter discusses the implementation of System-of-Systems Enterprise Architecture (SOSEA) CONOPS assessment framework and models in Matlab, and presents preliminary results concerning SOSEA resiliency in the presence of a notional Radio Frequency Interference (RFI) scenario. The chapter provides an overview of the SOSEA CONOPS Assessment Framework, and discusses related SOS Resiliency Models including Resilient Assessment Index Against RFI (RAI-RFI), Spectrum Resiliency Assessment Index (SRAI), and Resilient Capacity (RC).
Part of the book: Systems-of-Systems Perspectives and Applications
Systems-of-Systems MS&A for Complex Systems, Gaming and Decision for Space Systems By Tien M. Nguyen
This chapter discusses advanced modeling, simulation and analysis (MS&A) approaches for supporting complex space system, gaming and decision support system (DSS) using systems-of-systems perspective. The systems-of-systems MS&A approaches presented here also address capability-based approach for supporting US defense acquisition life cycle with a laser focus on the pre-award acquisition phase and combined game theory and wargaming for acquiring complex defense space systems. The chapter also provides an overview of existing models and tools for the design, analysis and development of the government reference system architecture solution and corresponding acquisition strategy in a complex defense systems-of-systems environment. Although, the proposed MS&A approaches presented here are focused on defense space systems, but the approaches are flexible and robust that can be extended to any civilian and commercial applications.
Part of the book: Simulation Modeling
Program Management Integrated with Data and Decision Sciences By Tien M. Nguyen, John D.T. Nguyen, My T.N. Nguyen, Charles H. Lee and Tam Nguyen
Program management (PM) complexity depends on the budget size and program types. In general, the program types can be classified into three categories, namely, defense, commercial, and civilian types. This chapter presents and discusses an approach for integrating the PM discipline areas with emerging data science and decision science1 (DDS) for any program type. Additionally, we describe the key PM areas and present a corresponding generalized model consists of a list of multiple PM discipline areas that can be tailored for any program types. To demonstrate the PM-DDS integration approach, we focus on three key PM areas and corresponding PM discipline areas related to schedule, cost, and risk management. These three discipline areas are analyzed to identify appropriate program elements that can be enhanced using existing DDS technology enablers (TEs). We also propose a flexible PM-DSS integration framework by leveraging existing machine learning operations (MLOps) framework. The proposed integration framework is expected to allow for enhancing the program planning and execution by reducing the program risk using a wide range of DDS TEs, including big data analytics, artificial intelligence, machine learning, deep learning, neural networks, and artificial intelligent.
Part of the book: Project Management
Ground-Based HPA Pre-Distorter Using Machine Learning and Artificial Intelligent for Satellite Communication Applications By Tien M. Nguyen, Charles H. Lee, Sean Cantarini, Xuanyu Huang, Jennifer Gudgel, Chanel Lee, Cristal Gonzalez, Genshe Chen, Dan Shen, John D.T. Nguyen and Khanh D. Pham
This chapter describes an innovative design and implementation approach of a ground-based pre-distorter framework using machine learning and artificial intelligence (ML-AI) technology for high power amplifier (HPA) pre-distortion. The ML-AI technology enabler proposed is a combined multi-objective reinforce learning-and-adaptive neural network (MORL-ANN) and an operating environment predictor (OEP). The proposed framework addresses the signal distortions caused by a nonlinear HPA on the ground transmitter and a nonlinear HPA located at a satellite communication (SATCOM) transponder (TXDER). The TXDER’s HPA is assumed to operate under unknown conditions. The objective is twofold, namely, to demonstrate (i) an advanced decision science technique using ML-AI for future SATCOM applications and (ii) the feasibility of the proposed ground-based ML-AI framework using an end-to-end SATCOM emulator. A new OEP concept using a deterministic and Bayesian approach to improve the MORL-ANN pre-distorter (PD) performance will also be presented.
Part of the book: Data and Decision Sciences
View all chapters