Authors: Elsa Dupraz, Thomas Maugey, Aline Roumy, Michel Kieffer

Title: Rate-storage regions for Massive Random Access,  submitted for review to IEEE Transactions on Information Theory (version ArXiv)

Abstract: This paper introduces a new source coding paradigm called Massive Random Access (MRA). In MRA, a set of correlated sources is jointly encoded and stored on a server, and clients want to access to only a subset of the sources. Since the number of simultaneous clients can be huge, the server is only authorized to extract a bitstream from the stored data: no re-encoding can be performed before the transmission of the specific client’s request. In this paper, we formally define the MRA framework and we introduce the notion of rate-storage region to characterize the performance of MRA. From an information theoretic analysis, we derive achievable rate-storage bounds for lossless source coding of i.i.d. and non i.i.d. sources, and rate-storage distortion regions for Gaussian sources. We also show two practical implementations of MRA systems based on rate-compatible LDPC codes. Both the theoretical and the experimental results demonstrate that MRA systems can reach the same transmission rates as in traditional point to point source coding schemes, while having a reasonable storage cost overhead. These results constitute a breakthrough for many recent data transmission applications in which only a part of the data is requested by the clients.