Publications
Network performance of pLEO topologies in a high-inclination Walker Delta Satellite Constellation
March 4, 2023
Conference Paper
Published in:
IEEE Aerospace Conf. Proc., 4-11 March 2023, 188722.
Summary
Low-earth-orbit satellite constellations with hundreds to thousands of satellites are emerging as practical alternatives for providing various types of data services such as global networking and large-scale sensing. The network performance of these satellite constellations is strongly dependent on the topology of the inter-satellite links (ISLs) in such systems. This paper studies the effects of six different ISL topologies, coupled with three configurations of ground relay terminals, on path failure rate, path latency, and link transmission efficiency in an example highly-inclined Walker Delta constellation with 360 satellites. These network performance parameters are calculated in the presence of satellite failures in the constellation. Trade-offs between ISL connection density and overall performance are examined and quantified. Topologies with 4 active ISLs per satellite are shown to perform significantly better than topologies requiring fewer, especially as the average number of active ISLs per satellite becomes significantly less than three. Latencies for a topology requiring 3 active ISLs per satellite are shown to be between 15 and 60% higher than for a 4-ISL reference topology. Path availabilities for the 3-ISL topology are shown to be on the order of 30% lower for a benchmark case of 10 satellite failures. The performance of near-minimal topologies (e.g., an average of 2.2 active ISLs per satellite) is much worse. Latency reductions of 10-30% and path failure rate improvements on the order of 45% are shown to be obtainable by the inclusion of 2 to 5 strategically located ground relay stations
Summary
Low-earth-orbit satellite constellations with hundreds to thousands of satellites are emerging as practical alternatives for providing various types of data services such as global networking and large-scale sensing. The network performance of these satellite constellations is strongly dependent on the topology of the inter-satellite links (ISLs) in such systems. This...
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Contingent routing using orbital geometry in proliferated low-earth-orbit satellite networks
November 28, 2022
Conference Paper
Published in:
2022 IEEE Military Communications Conf., MILCOM, 28 November - 2 December 2022.
Summary
Optimum adaptive routing in proliferated low-earth-orbit (pLEO) satellite networks requires intensive computation. The very small size, light weight, and low power of individual satellites in such networks makes a centralized, terrestrial, SDN-like approach to routing computation an attractive solution. However, it is highly desirable to have a distributed backup routing capability onboard each satellite that can maintain service if the central computational node(s) fail or lose their pathway(s) to upload routing data frequently to each satellite. This paper presents a routing algorithm based on orbital geometry that has a very low computation and storage requirements and is suitable as a backup routing capability in the event of failure of a centralized routing calculation node or nodes. Path failure rate, path latency, and link resource usage are simulated for a 360-satellite Walker Delta constellation with 4 inter-satellite link (ISL) terminals per satellite, and with up to 10% of the satellites having failed. For the fully intact satellite constellation, path failure rate is zero (identical to a shortest path routing algorithm), while mean latency and average link resource usage are shown to be approximately 12% and 13% higher, respectively, than with shortest path routing. With 10 random satellite failures in the constellation, the geometric algorithm has a path failure rate of less than 0.5%, while the mean latency and link resource usage are approximately 12% and 16% higher, respectively, than with shortest path routing.
Summary
Optimum adaptive routing in proliferated low-earth-orbit (pLEO) satellite networks requires intensive computation. The very small size, light weight, and low power of individual satellites in such networks makes a centralized, terrestrial, SDN-like approach to routing computation an attractive solution. However, it is highly desirable to have a distributed backup routing...
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Failure resilience in proliferated low earth orbit satellite network topologies
November 28, 2022
Conference Paper
Published in:
2022 IEEE Military Communications Conf., MILCOM, 28 November - 2 December 2022.
Summary
The vision of continuous network connectivity for users located anywhere on Earth is increasingly being enabled by satellite constellations with hundreds to thousands of satellites operating in low altitude orbits (typically somewhere between a few hundred and two thousand km). These constellations are often referred to as proliferated Low Earth Orbit (pLEO) constellations. Potential military use of such constellations would require a high degree of resilience against various types of failures. This paper examines how resilience to satellite failures in particular is affected by topology and topology management for a moderate-sized constellation of 360 low-earth-orbit satellites providing 2X-redundant global coverage. We present simulations quantifying the effects of two vs. four inter-satellite links (ISLs) per satellite, and of dynamic post-failure topology reconfiguration vs static topology management. Simulations show differences of 65-80% in mission connectivity between 4-ISL topologies with dynamic topology reconfiguration and 2-ISL topologies with static topology using two different traffic scenarios.
Summary
The vision of continuous network connectivity for users located anywhere on Earth is increasingly being enabled by satellite constellations with hundreds to thousands of satellites operating in low altitude orbits (typically somewhere between a few hundred and two thousand km). These constellations are often referred to as proliferated Low Earth...
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Rate control with autoregressive forecasting for high frequency communication
November 28, 2022
Conference Paper
Published in:
2022 IEEE Military Communications Conf., MILCOM, 28 November - 2 December 2022.
Summary
This work introduces a data-driven framework for rate control and applies it to high frequency (HF) communication systems that propagate via the Earth’s ionosphere. The rate control approach uses statistical techniques to forecast channel state with an autoregressive (AR) model, which has previously been applied to different forms of wireless fading, including "medium" timescale fading at HF. The objective of rate control is to maximize the data rate while constraining the rate of packets decoded in error. We show that under ideal assumptions, the rate controller selects the rate by backing off from the forecast average signal-to-noise ratio (SNR) by a factor of sigmaQ^-1(Beta), where sigma^2 correlates with fading variance, Beta denotes a constraint on decoder errors, and Q(.) is the complementary cumulative distribution function of the Gaussian distribution. Simulation results on an HF channel model show that compared with naive schemes, AR forecasting provides a good balance between achieving high rate and ensuring reliability.
Summary
This work introduces a data-driven framework for rate control and applies it to high frequency (HF) communication systems that propagate via the Earth’s ionosphere. The rate control approach uses statistical techniques to forecast channel state with an autoregressive (AR) model, which has previously been applied to different forms of wireless...
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Robust network protocols for large swarms of small UAVs
March 5, 2022
Conference Paper
Published in:
2022 IEEE Aeropsace Conf., AERO 2022, 18 p.
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Summary
In this work, we detail a synchronized channel hopping network for autonomous swarms of small unmanned aerial vehicles (UAVs) conducting intelligence, surveillance, and reconnaissance (ISR) missions in the presence of interference and jamming. The core component of our design is Queue Length Informed Maximal Matching (QLIMM), a distributed transmission scheduling protocol that exchanges queue state information between nodes to assign subdivisions of the swarm to orthogonal hopping patterns in response to the network’s throughput demands. QLIMM efficiently allocates channel resources across large networks without relying on any centralized control or pre-planned traffic patterns, which is in the spirit of a swarming capability. However, given that the control messaging must scale up with the swarm’s size and the challenging interference environments we consider, fragility could be a concern. To observe under what conditions control fails, we test our protocol against both simulated partial-band noise jamming and background interference. For the latter, we use data collected from a small unmanned aircraft system to characterize the interference seen by a UAV in the 2.4 and 5 GHz bands in both urban and rural settings. These measurements show that the interference can be 15 dB higher at a 50-meter flight altitude when compared to observations on the ground. Using this data, we conduct extensive network simulations of QLIMM in Riverbed Modeler to show that, under moderate jamming and interference, it outperforms traditional channel access methods as well as other scheduling protocols that do not pass queue state information.
Summary
In this work, we detail a synchronized channel hopping network for autonomous swarms of small unmanned aerial vehicles (UAVs) conducting intelligence, surveillance, and reconnaissance (ISR) missions in the presence of interference and jamming. The core component of our design is Queue Length Informed Maximal Matching (QLIMM), a distributed transmission scheduling...
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Capacity bounds for frequency-hopped BPSK
November 29, 2021
Conference Paper
Published in:
2021 IEEE Military Communications Conf., MILCOM, 29 November - 2 December 2021.
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Summary
In some channels, such as the frequency-hop channel, the transmission may undergo abrupt transitions in phase. This can require the receiver to re-estimate the phase on each hop, or for the system to utilize modulation techniques that lend themselves to noncoherent detection. How well the receiver can estimate the phase depends on the channel signal-to-noise ratio and how long phase coherence can be assumed. Although prior work has shown that using any reference symbols to aid the phase estimation process is suboptimal with respect to capacity, their presence may be useful in practice as they can simplify the receiver processing. In this paper, the effects of per-pulse phase uncertainty are examined for systems using binary modulation. Both the fraction of the transmission that may be devoted to reference symbols without substantially reducing the overall channel capacity and the point at which it is better to forego coherent processing in favor of noncoherent demodulation are examined.
Summary
In some channels, such as the frequency-hop channel, the transmission may undergo abrupt transitions in phase. This can require the receiver to re-estimate the phase on each hop, or for the system to utilize modulation techniques that lend themselves to noncoherent detection. How well the receiver can estimate the phase...
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Application of complex split-activation feedforward networks to beamforming
October 31, 2021
Conference Paper
Published in:
55th Asilomar Conf. on Signals, Systems and Computers, ACSSC, 31 October - 3 November 2021.
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Summary
In increasingly congested RF environments and for jamming at closer ranges, amplifiers may introduce nonlinearities that linear adaptive beamforming techniques can't mitigate. Machine learning architectures are intended to solve such nonlinear least squares problems, but much of the current work and available software is limited to signals represented as real sequences. In this paper, neural networks using complex numbers to represent the complex baseband RF signals are considered. A complex backpropagation approach that calculates gradients and a Jacobian, allows for fast optimization of the neural networks. Through simulations, it is shown that complex neural networks require less training samples than their real counterparts and may generalize better in dynamic environments.
Summary
In increasingly congested RF environments and for jamming at closer ranges, amplifiers may introduce nonlinearities that linear adaptive beamforming techniques can't mitigate. Machine learning architectures are intended to solve such nonlinear least squares problems, but much of the current work and available software is limited to signals represented as real...
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Detecting pathogen exposure during the non-symptomatic incubation period using physiological data: proof of concept in non-human primates
September 3, 2021
Journal Article
Published in:
Front Physiol., Vol. 12, September 2021, Article 691074.
Summary
Background and Objectives: Early warning of bacterial and viral infection, prior to the development of overt clinical symptoms, allows not only for improved patient care and outcomes but also enables faster implementation of public health measures (patient isolation and contact tracing). Our primary objectives in this effort are 3-fold. First, we seek to determine the upper limits of early warning detection through physiological measurements. Second, we investigate whether the detected physiological response is specific to the pathogen. Third, we explore the feasibility of extending early warning detection with wearable devices. Research Methods: For the first objective, we developed a supervised random forest algorithm to detect pathogen exposure in the asymptomatic period prior to overt symptoms (fever). We used high-resolution physiological telemetry data (aortic blood pressure, intrathoracic pressure, electrocardiograms, and core temperature) from non-human primate animal models exposed to two viral pathogens: Ebola and Marburg (N = 20). Second, to determine reusability across different pathogens, we evaluated our algorithm against three independent physiological datasets from non-human primate models (N = 13) exposed to three different pathogens: Lassa and Nipah viruses and Y. pestis. For the third objective, we evaluated performance degradation when the algorithm was restricted to features derived from electrocardiogram (ECG) waveforms to emulate data from a non-invasive wearable device. Results: First, our cross-validated random forest classifier provides a mean early warning of 51 ± 12 h, with an area under the receiver-operating characteristic curve (AUC) of 0.93 ± 0.01. Second, our algorithm achieved comparable performance when applied to datasets from different pathogen exposures – a mean early warning of 51 ± 14 h and AUC of 0.95 ± 0.01. Last, with a degraded feature set derived solely from ECG, we observed minimal degradation – a mean early warning of 46 ± 14 h and AUC of 0.91 ± 0.001. Conclusion: Under controlled experimental conditions, physiological measurements can provide over 2 days of early warning with high AUC. Deviations in physiological signals following exposure to a pathogen are due to the underlying host’s immunological response and are not specific to the pathogen. Pre-symptomatic detection is strong even when features are limited to ECG-derivatives, suggesting that this approach may translate to non-invasive wearable devices.
Summary
Background and Objectives: Early warning of bacterial and viral infection, prior to the development of overt clinical symptoms, allows not only for improved patient care and outcomes but also enables faster implementation of public health measures (patient isolation and contact tracing). Our primary objectives in this effort are 3-fold. First...
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Priority scheduling for multi-function apertures with hard- and soft-time constraints
March 6, 2021
Conference Paper
Published in:
2021 IEEE Aerospace Conf., 6-13 March 2021.
Summary
A multi-function aperture (MFA) is an antenna array that supports multiple RF signals for a diverse set of activities. An MFA may support multiple activities simultaneously if they are compatible, and platforms may utilize multiple MFAs to meet field-of-regard and frequency range requirements. Efficient MFA utilization requires a Resource Manager (RM) that routes signals to the correct MFA based on field-of-view and other requirements, and schedules MFA access to resolve conflicts based on request priority. An efficient RM scheduler time-interleaves requests from different activities as needed. Requested access events may be hard-time—that is, the event must be scheduled at a specified time or not at all, or soft-time, indicating it may be scheduled anytime in a specified window. Hard-time events include communications channels with assigned time slots, and soft-time events include asynchronous communications channels. This paper describes and evaluates an optimal algorithm to jointly schedule sequences of hard-time requests, maximizing the number of scheduled events while meeting priority requirements. An extension of this algorithm provides near-optimal schedules for sequences of soft-time or mixed hard- and soft-time events. Algorithms are evaluated by simulation, using two conflict models. The first is based on fixed signal paths that conflict if two paths share a common resource. The second model assumes the RM dynamically assigns resources. As implemented, these algorithms are too slow for real-time operation, and further work is required. They do provide insight into the MFA management problem, a useful metric for evaluating resource sharing and scheduling approaches, and may suggest efficient sub-optimal algorithms.
Summary
A multi-function aperture (MFA) is an antenna array that supports multiple RF signals for a diverse set of activities. An MFA may support multiple activities simultaneously if they are compatible, and platforms may utilize multiple MFAs to meet field-of-regard and frequency range requirements. Efficient MFA utilization requires a Resource Manager...
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Using oculomotor features to predict changes in optic nerve sheath diameter and ImPACT scores from contact-sport athletes
March 4, 2021
Journal Article
Published in:
Front. Neurol., 4 March 2021, Art. No. 584684.
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Summary
There is mounting evidence linking the cumulative effects of repetitive head impacts to neuro-degenerative conditions. Robust clinical assessment tools to identify mild traumatic brain injuries are needed to assist with timely diagnosis for return-to-field decisions and appropriately guide rehabilitation. The focus of the present study is to investigate the potential for oculomotor features to complement existing diagnostic tools, such as measurements of Optic Nerve Sheath Diameter (ONSD) and Immediate Post-concussion Assessment and Cognitive Testing (ImPACT). Thirty-one high school American football and soccer athletes were tracked through the course of a sports season. Given the high risk of repetitive head impacts associated with both soccer and football, our hypotheses were that (1) ONSD and ImPACT scores would worsen through the season and (2) oculomotor features would effectively capture both neurophysiological changes reflected by ONSD and neuro-functional status assessed via ImPACT. Oculomotor features were used as input to Linear Mixed-Effects Regression models to predict ONSD and ImPACT scores as outcomes. Prediction accuracy was evaluated to identify explicit relationships between eye movements, ONSD, and ImPACT scores. Significant Pearson correlations were observed between predicted and actual outcomes for ONSD (Raw = 0.70; Normalized = 0.45) and for ImPACT (Raw = 0.86; Normalized = 0.71), demonstrating the capability of oculomotor features to capture neurological changes detected by both ONSD and ImPACT. The most predictive features were found to relate to motor control and visual-motor processing. In future work, oculomotor models, linking neural structures to oculomotor function, can be built to gain extended mechanistic insights into neurophysiological changes observed through seasons of participation in contact sports.
Summary
There is mounting evidence linking the cumulative effects of repetitive head impacts to neuro-degenerative conditions. Robust clinical assessment tools to identify mild traumatic brain injuries are needed to assist with timely diagnosis for return-to-field decisions and appropriately guide rehabilitation. The focus of the present study is to investigate the potential...
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