2012/10/08 by Ahmad Beirami, Faramarz Fekri, Beirami, Ahmad +1
Computer Science · Engineering · #Cellular Automata and Applications #Cooperative Communication and Network Coding #FOS: Computer and information sciences #Information Theory (cs.IT) #Wireless Communication Security Techniques
paper · pdf · doi:10.48550/arxiv.1210.2144
openalex publication_date 2012/10/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper, we propose \em distributed network compression via memory. We consider two spatially separated sources with correlated unknown source parameters. We wish to study the universal compression of a sequence of length n from one of the sources provided that the decoder has access to (i.e., memorized) a sequence of length m from the other source. In this setup, the correlation does not arise from symbol-by-symbol dependency of two outputs from the two sources (as in Slepian-Wolf setup). Instead, the two sequences are correlated because they are originated from the two sources with unknown correlated parameters. The finite-length nature of the compression problem at hand requires considering a notion of almost lossless source coding, where coding incurs an error probability pe(n) that vanishes as sequence length n grows to infinity. We obtain bounds on the redundancy of almost lossless codes when the decoder has access to a random memory of length m as a function of the sequence length n and the permissible error probability pe(n). Our results demonstrate that distributed network compression via memory has the potential to significantly improve over conventional end-to-end compression when sufficiently large memory from previous communications is available to the decoder.