An Information Theoretic Overview of Uplink Cloud Radio Access Networks

15/05/2018 - 15:00 - 16:00

We consider transmission over a cloud radio access network focusing on the framework of oblivious processing at the relay nodes (radio units), i.e., the relays are not cognizant of the users' codebooks.This approach is motivated by future wireless communications (5G and beyond) and the theoretical results not only provide basic insights but sometimes determine exactly the optimal relay nodes processing strategy. In particular, it is demonstrated that compress-and-forward, and variants of it, generally perform well and are optimal when the outputs at the relay nodes are
conditionally independent on the users’ inputs. Here, we show that relaying a-la Cover-El Gamal, i.e., compress-and-forward with joint decompression and decoding, which reflects ``noisy network coding'', is optimal. The proof of optimality establishes, and utilizes, connections with the Chief Executive Officer (CEO) source coding problem under a logarithmic loss distortion measure. It is also shown that for the Gaussian case, obliviousness implies at most a constant gap penalty, when compared to cut-set bounds. Furthermore, we identify and elaborate on some interesting connections with the distributed information bottleneck problem for which we characterize optimal tradeoffs between rates (i.e., complexity) and information (i.e., accuracy) in the discrete and vector Gaussian models. In the concluding outlook, some interesting problems are mention such as the characterization of the optimal input distributions under users' power limitations and rate-constrained compression at the relay nodes.


Joint work with: I.E. Aguerri (Paris Research Center, Huawei France)
A. Zaidi (Universite Paris-Est, Paris) and G. Caire (USC-LA and TUB, Berlin)
The research is supported by the European Union's Horizon 2020 Research And
Innovation Programme: no. 694630.

Shlomo Shamai, The Viterbi Faculty of Electrical Engineering, Technion-Israel Institute of Technology
BIU Engineering Building 1103, Room 329