Engineering topics
Liao, Jason
Publications and source records attributed to Liao, Jason.
DSN Wide Area Network Architecture, Capacity and Performance
This paper discusses the architecture of the wide area network that connects key communications facilities within the National Aeronautic and Space Administration (NASA) Deep Space Network (DSN). Several considerations are given to the design of this wide area network to ensure a timely, reliable, and secure data delivery between the mission users and their spacecraft. The network star configuration simplifies data delivery to users and minimizes operational cost. The dual-path connections maximize the system reliability, with geographical diversity in data routing to avoid single point of failure. Data encryption enhances the protection of mission users’ data. The system bandwidth is determined by balancing the needs to minimize the operating bandwidth cost and to have sufficient bandwidth to be able to deliver data to all users within the required. The DSN uses a class base weighted fair queuing (CBWFQ) method in its data delivery. This scheme guarantees a minimum bandwidth to each class of users and allows users to also access any unused bandwidth by other groups. The paper will also show performance of system reliability and bandwidth margin.
Characterization of Operational Performance of Ka-Band Links in Deep Space Network
This paper presents a characterization of performance of 32-GHz Ka-band link in an operational environment. The data come from tracking of Kepler spacecraft by the NASA Deep Space Network (DSN) in the past few years. Ka-band link offers a significant signal-to-noise advantage compared to the more common X- or S-band; however, it is subject to more signal fluctuation caused by the weather. Kepler is the first mission supported by the DSN that solely rely on the higher deep space Ka-band communications link to return its high-rate science data. A well characterization of the operational performance of Kepler would benefit future Ka-band missions, especially for those operating with smaller link margin. The study examines how weather conditions at the DSN facilities (e.g., winds, clouds, rains) affect the received signal, particularly on telemetry data. It addresses questions such as how often the weather affects the link and how much degradation the link could suffer. Among the 22 Ka-band passes in 2012, heavy clouds affected one pass and two passes were impacted by high winds. The adverse weather caused at time as much as 3-dB instantaneous change in the signal to noise ratio (SNR). Estimates of degradation to the SNR as a function of wind speeds are captured based on observations. This study also quantifies the probability distribution of the variation of received signal power. With such information, future missions can better plan their link design. An optimal link design aims for just having enough margin to realize the data return with a targeted probability, with neither having too much margin that it reduces the downlink data rate nor insufficient reserve that causes frequent data outages. The study tries to provide some answers to the questions such as how much does SNR vary from one tracking pass to the next, and what is the cumulative distribution of signal fluctuation. Regarding the signal variation over many tracking passes, we found that the averaged symbol SNR (SSNR) for each pass changed by as much as 4 dB. Some variations were due to geometry such as the changing distance between spacecraft and Earth and different antenna pointing elevations. Other variations seem to be random in nature, reflecting the randomness of operational environments. Some passes were found to be quite stable, with a standard deviation of symbol SNR around 0.25 dB while others had greater variation, up to 1.4 dB. Overall, the cumulative distribution of the symbol SNR reflects that 50% of the fluctuations was less than 0.6 dB, 90% of fluctuation was within 1.6 dB and 95% within 2.2 dB. Some of the challenges in data processing, validation and modeling were captured in this paper. We observed some inconsistent measurements where operational data significantly deviate from a normal expectation. These inconsistent measurements made it hard to develop an accurate and consistent performance model, such as the degradation of signal SNR as a function of high wind. The difficulty was compounded by the fact that there were only a few Ka-band passes observed in high winds.
Performance Analysis of Operational Ka-Band Link with Kepler
This paper presents some observations on the signal behavior from an analysis of Kepler Ka-band link. The goal is to characterize the link performance with operational data obtained from the Deep Space Network (DSN) tracking of Kepler spacecraft. Kepler is the first mission supported by the DSN that uses Ka-band as a primary means to return science data. We examine how operational data may differ from the expectation. Operational data often show many surprises where data variations occur without an apparent cause. We try to quantify the signal power fluctuation so that future missions can adequately plan for the link design, especially for missions that operate with lower margin. We also attempt to quantify the effect of rains/heavy clouds and high winds.
Identification of Abnormal System Noise Temperature Patterns in Deep Space Network Antennas Using Neural Network Trained Fuzzy Logic
This paper presents the development of a fuzzy logic function trained by an artificial neural network to classify the system noise temperature (SNT) of antennas in the NASA Deep Space Network (DSN). The SNT data were classified into normal, marginal, and abnormal classes. The irregular SNT pattern was further correlated with link margin and weather data. A reasonably good correlation is detected among high SNT, low link margin and the effect of bad weather; however we also saw some unexpected non-correlations which merit further study in the future.