The Air Force Satellite Control Network (AFSCN) is a worldwide network of ground stations that supports a variety of users from NASA to the National Recon naissance Office (NRO). The network performs tracking, telemetry, and commanding (TT&C) for these users. Users, located at Satellite Operations Centers (SOCs), must compete for time on the AFSCN (see Figure 1).
One value that determines the success of an uplink or downlink is the signal to noise ratio (SNR). SNR is the power of the transmitted signal over the noise power. Both uplink and downlink require minimum SNR to be considered successful. If the minimum SNR is not met, the data cannot be extracted from the signal.
Currently, the users do not know what the SNR performance will be over a given contact because there is currently no SNR prediction capability in the AFSCN. The spacecraft operators, or users, schedule time on the AFSCN with no regard to the estimated SNR. This presents an issue. With no way to estimate or predict the performance of an upcoming support, the users cannot accurately request time on the network because they do not have a quantitative representation of the estimated performance of the contact. If the users had an estimate of how the link would perform, they would be better prepared to schedule contacts more efficiently.
SNR is largely dependent on the signal power from the transmitter. With the ability to predict the SNR of a downlink, the users would be able to optimize the power level to the amount required to achieve the desired SNR. This is a huge advantage as power consumption is an important factor in spacecraft operations.
There are apparent advantages to predicting link performance. So why doesn’t the AFSCN have this capability? During the design phase of spacecraft programs, a worst-case link budget is used. In other words, the spacecraft is designed to obtain the needed SNR in worst-case scenarios. Therefore, varying SNR is not normally considered an important issue because the needed performance can be obtained in most conditions. As a result, there is no SNR predictive capability within the AFSCN.
Having SNR prediction capability would allow the spacecraft operators to more accurately predict the amount of time needed for a support and potentially result in power savings for the spacecraft. Guiding the research are the following questions: How can link performance be predicted? Where in the current AFSCN architecture would performance prediction be applied? Lastly, how would the AFSCN and its users benefit from link prediction capability?