Decoding probability analysis of network-coded data collection and delivery by relay drones

Chatzigeorgiou, Ioannis and Manole, Elena (2020) Decoding probability analysis of network-coded data collection and delivery by relay drones. In: 2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) :. IEEE, GBR. ISBN 9781728144917

Text (Camera_Ready_SysRLNC_for_Relay_Drones)
Camera_Ready_SysRLNC_for_Relay_Drones.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial.
Download (546kB)

Abstract

Relay drones in delay-tolerant applications are dispatched to remote locations in order to gather data transmitted by a source node. Collected data are stored on the drones and delivered to one or multiple bases. This paper considers two schemes for broadcasting data to drones when feedback channels are not available: a data carousel and systematic random linear network coding (RLNC). We propose a theoretical framework for the calculation of the probability that a base will fully or partially recover the transmitted data and the probability that all involved bases will successfully obtain the data, when the bases are either isolated or interconnected. Theoretical results are validated through simulations. Design considerations are also discussed, including the relationship among the field size used by RLNC, the number of relay drones and the requirement for full data recovery or the retrieval of at least part of the data.