Todd W. Martin

Optical communications in atmospheric turbulence

Recent experiments conducted under the Optical RF Communications Adjunct program demonstrate and validate the viability of hybrid free space optical communications links in heavy atmospheric turbulence. Long range air-to-mountain link closures were established under extreme atmospheric turbulence. The system implemented adaptive mechanisms such as adaptive optics, an optical automatic gain controller, forward error correction coding, and link-level retransmission to achieve low packet error rates for long distance links with heavy turbulence. The system, experiments, and results are presented and comparisons are made to statistical prediction models.

Hybrid optical radio frequency airborne communications

Optical RF Communications Adjunct Program flight test results provide validation of the theoretical models and hybrid optical radio frequency (RF) airborne system concepts developed by the Defense Advanced Research Projects Agency and the U.S. Air Force Research Laboratory. Theoretical models of the free-space optical communications (FSOC), RF, and network components accurately predict the flight test results under a wide range of day and night operating conditions. The FSOC system, including the adaptive optics and optical modem, can operate under high turbulence conditions. The RF and network mechanisms of Layer 2 retransmission and failover provide increased reliability, reducing end-to-end packet error rates. Overall the test results show that stable, long-range FSOC is possible and practical for near-term operations.

Progress towards reliable free-space optical networks

Free-space optical communications (FSOC) links provide an appealing and complementary enhancement to current radio frequency (RF) systems because of their inherent benefits of high-bandwidth and directional communication. Although FSOC systems can be inoperable through clouds or thick fog, employing them in a hybrid RF/optical link configuration can yield a system that can operate under most weather conditions and provide high-bandwidth, secure, jam-resistant communications under most conditions. Beyond attenuation effects and line-of-sight limitations, FSOC link performance is primarily driven by optical turbulence along the beam path, which leads to severe fluctuation of the communications channel and distortion of the signal wavefront. Many methods have been either modeled or field-tested to reduce this fading with varying degrees of success. The approach taken in the DARPA Free Space Optical Experimental Network Experiment (FOENEX) program is a continuance of systems development work funded and developed by DARPA, the Air Force Research Laboratory (AFRL), and the Naval Research Laboratories (NRL). The use of QoS-based link-level techniques was successfully demonstrated under the AFRL Iron T2 and DARPA ORCA programs. The FOENEX program extends these methods via technology developments at the physical layer as well as implementing the network methods to ensure end-to-end high bandwidth connectivity. This paper focuses on progress to date in networking technologies that will support free space optical networks (FSON) out to 200 km ranges even when individual links are disrupted up to 5% of the time.

A probabilistic situational awareness and reasoning methodology for satellite communications resource management

This paper presents a satellite communications (SATCOM) situational awareness and decision-making methodology that incorporates situational uncertainty with a probabilistic reasoning representation of the SATCOM network and operating environment. The situational awareness and decision model is developed using probabilistic Functional Causal Modeling (FCM) and multiattribute utility theory. The probabilistic FCM is a Bayesian Network developed from the mathematical functions that represent the underlying phenomena of the SATCOM system, operating environment, and operational dynamics. The model provides a formal system for representing cause and effect of system reconfiguration and is built upon well-established engineering models for SATCOM systems. The multiattribute decision model provides a formal basis for in situ decision-making that combines user goals and situational uncertainty. The paper presents the theoretical basis of the technique as well as implementation examples with quantitative analyses. Characteristics of the model components, associated sources of uncertainty, and associated impact on performance and decision making are addressed. The discussion demonstrates the models use for performance prediction as well as inference of SATCOM resource allocations needed to meet performance goals with desired levels of confidence.

A Data Fusion Formulation for Decentralized Estimation Predictions under Communications Uncertainty

Uncertainty in communication channel characteristics is a significant factor for data fusion operations in wireless networks. Burst and random errors, message delays, user mobility, and link outages are significant factors that influence data fusion performance. These factors become even more significant in future mobile ad hoc networking environments. To date, however, those factors are not sufficiently addressed by formulations used for modeling and predicting data fusion performance. A stochastic-based fusion formulation that incorporates the effects of non-deterministic behaviors and stochastic communications characteristics is developed and proposed as a method for predicting estimation capabilities. The resulting stochastic fusion equations enable decentralized estimation capabilities to be evaluated in communication networks having non-idealized channel characteristics and ad hoc connectivity. The method is implemented in a simulation model for decentralized estimation in networks with time-varying ad hoc connectivity. The simulation results demonstrate the ability to closely predict expected fusion performance while greatly reducing model complexity and simulation time relative to current techniques. Those findings demonstrate the efficacy of a stochastic fusion formulation for prediction, and extending the approach to a wider range of data fusion domains and techniques is recommended

A decision and utility theory construct for dynamic spectrum access systems

Dynamic Spectrum Access (DSA) networks seek to opportunistically utilize unused RF capacity rather than relying on static spectrum assignments. The networks change their spectrum access characteristics such as fre- quency, power, and modulation to adapt and allow for access to spectrum while not causing harmful interference to other spectrum users. An essential element of DSA system operation is decision-making under uncertainty due to incomplete or inaccurate situational awareness. This paper describes ongoing eorts in applying decision and utility theory constructs to DSA systems. The construct combines elements of communications theory, formal value and utility axioms of probability and decision theory, and constraint satisfaction. It provides a mechanism that allows DSA systems to quantitatively evaluate options for attaining the desired capacity subject to constraints in radio performance, uncertainty in spectrum dynamics, operating cost, and avoidance of harmful interference to other spectrum users. The resulting construct provides insight into DSA operational trades for evaluating, ranking, and selecting alternative solutions. A decision-theoretic construct is developed and analyzed to illustrate the methodology and resulting trades among alternative utility function classes.

An initial study of DSA cost and capacity trades under imperfect awareness

This paper presents an initial study of imperfect awareness impacts on DSA decision-making and behavior. The investigation utilizes a multiattribute spectrum utility function based on preference and decision theory concepts that enables decision-making under uncertainty. The approach incorporates technical, regulatory, and economic factors into the evaluation process. The analyses explore the implications of imperfect awareness on DSA system behavior in the context of spectrum pricing models and associated trades with spectrum capacity guarantees. Results indicate that DSA systems will prefer fixed pricing models over auction-based pricing for secondary spectrum access unless expected auction costs are lower or significant spectrum benefits are provided. Cost uncertainty associated with auction-based spectrum pricing invokes a risk premium in DSA systems that use a risk averse model. Increases in spectrum quality (capacity gain and/or interference mitigation relief) guarantees may compensate for risk premiums but are found to be insufficient or impractical in some cases. Analytical methods for quantifying the penalties and trades are developed in this paper.

Probabilistic reasoning and risk-constrained dynamic spectrum access

Uncertainties regarding wireless propagation environments pose challenges for spectrum management in general and specifically hinder the implementation of dynamic spectrum sharing systems. Without the ability to reliably evaluate interference risks, spectrum sharing policies specify spectrum access behaviors such as exclusion zones and maximum transmit powers based on risk thresholds applied to statistical results from propagation models and measurements. Because the models can contain significant levels of uncertainty, establishing behavior limits for low interference risk necessarily results in significant spectrum access inefficiencies. It is only by reducing the degree of uncertainty that risk thresholds can be maintained while increasing spectrum access efficiency. Probabilistic reasoning applied to dynamic spectrum sharing systems provides potential to increase spectrum sharing by reducing situational uncertainty. Further, probabilistic reasoning approaches enable risk-constrained spectrum access, a concept in which regulators and spectrum users establish spectrum access rules defining acceptable levels of interference and spectrum access risks. This paper develops the concepts and underlying theory of probabilistic reasoning and risk-constrained spectrum access for spectrum sharing. It further presents simulation results showing that situation-specific probabilistic reasoning combined with risk-constrained spectrum access potentially enables greater spectrum sharing. Specifically, probabilistic reasoning with real-time spectrum sensing is shown to greatly reduce situational uncertainty, which then results in better interference prevention and more effective spectrum sharing as measured by user capacity and overall network density.

Optical RF communications adjunct: Coming of age

The concept of Free Space Optical (FSO) communications has been around since the late 1960s.This paper will describe some recent experimental results that demonstrate and validate hybrid FSO/RF communication links as viable components in a tactical high data rate network. In particular, we will describe air-mountain link closure up to ranges of 200 km under heavy atmospheric turbulence. These links were operated at low packet and bit error rates, with occasional link outages. Like the internet, we used retransmission to minimize the effect of these outages on link throughput. For example, when the FSO system is running, ORCA uses the RF system for retransmission to improve link efficiency. In addition, we will discuss potential losses created by the aircraft aero-optics effects. Finally, we will show comparison between model predictions and experimental data that suggest we can predict link performance if the atmospheric turbulence conditions are known.

Risk-based pricing for secondary spectrum access

Probabilistic reasoning applied to dynamic spectrum sharing systems enables them to characterize situational uncertainties and determine acceptable spectrum access behaviors. Spectrum sharing systems may use sensing data to reduce situational uncertainty and improve spectrum sharing potential. Probabilistic reasoning approaches enable risk-constrained spectrum access, a concept in which spectrum sharing is governed by maintaining acceptable levels of interference and spectrum access risks. Simulations show the potential for greater user density as a function of reduced situational uncertainty. This paper extends the risk-based spectrum access approach to secondary spectrum providers, who need to determine how to best allocate spectrum resources to users. A secondary spectrum provider revenue and cost model is developed that incorporates secondary user density, pricing models, and spectrum provider costs that are functions of interference risk and situational uncertainty. Simulations and analyses demonstrate the relationship among revenue, cost, risk, and situational uncertainty. Analysis shows significant variation in secondary spectrum provider revenue as a function of path loss uncertainty and interference risk.