Faster Communication for Interplanetary Spacecraft

Professor John Villasenor, Director
The Image Communication Laboratory

Over the last several decades, NASA has launched a succession of unmanned probes that have explored the moon, the inner and outer planets, comets, and asteroids. Collectively, these missions have added immensely to our knowledge of the solar system and to many of the process that have shaped our own planet.

While these missions have been as diverse as the interplanetary bodies they have explored, they all share one common theme – the need to transmit data reliably over the vast distances from the spacecraft back to receiving stations here on Earth.

Professor John Villasenor and the researchers in his laboratory have been working in collaboration with Dr. Chris Jones, a researcher at NASA's Jet Propulsion Laboratory in Pasadena, CA, on methods that can lead to faster data transmissions -- and therefore an even richer return of information -- from future interplanetary missions. As Dr. Jones, who earned his Ph.D. in communications at UCLA, explains, "The transmission environment for these spacecraft is uniquely challenging. The distances are enormous, and the rapid changes in velocity that can occur during critical phases, such as a descent to the surface of Mars, cause rapid frequency shifts in the radio signal."

Dr. Dong-U Lee, a staff researcher in the laboratory elaborates: "Traditionally, the portion of a radio receiver that acquires the signal is treated completely separately from the portion that does the channel decoding, which aims to correct errors introduced during transmission. In our work we are throwing that assumption away. Some of the newer and most intriguing channel decoders are iterative, meaning that each block of signals is processed multiple times. We're taking information from the channel decoder, and feeding it back to the 'upstream' sections of the radio receiver that determine the exact time of arrival of the signals."

While the work is still in a relatively early stage, the results so far suggest that such joint processing can improve the system performance by a dB or more. This can correspond to an improvement in signal reliability in the range of one order of magnitude (i.e. a factor of 10), which leads directly to significantly improved quality of images and other data.