Content-based multiple access: Combining source and multiple access coding for sensor networks

In this work, we explore the concept of group testing to efficiently acquire data from a distributed sensor field and to reconstruct the sensor field at a central station. We show that group testing techniques are not only an efficient tool to schedule multiple access transmissions, they are also transmission techniques that allow the central node to rapidly discriminate the information from the sensor field when a large number of sources generates data with low aggregate entropy. Our method enables the sensors to reconstruct a map of the entire sensor field with bandwidth requirements that depend on the precision of the reconstructed field and, thus, do not grow linearly with the increased number of nodes when the network density increases.