  We consider a noisy Slepian-Wolf problem where two correlated sources are
separately encoded and transmitted over two independent binary memoryless
symmetric channels. Each channel capacity is assumed to be characterized by a
single parameter which is not known at the transmitter. The receiver has
knowledge of both the source correlation and the channel parameters. We call a
system universal if it retains near-capacity performance without channel
knowledge at the transmitter. Kudekar et al. recently showed that terminated
low-density parity-check (LDPC) convolutional codes (a.k.a. spatially-coupled
LDPC ensembles) can have belief-propagation thresholds that approach their
maximum a-posteriori thresholds. This was proven for binary erasure channels
and shown empirically for binary memoryless symmetric channels. They also
conjectured that the principle of spatial coupling is very general and the
phenomenon of threshold saturation applies to a very broad class of graphical
models. In this work, we derive an area theorem for the joint decoder and
empirically show that threshold saturation occurs for this problem. As a
result, we demonstrate near-universal performance for this problem using the
proposed spatially-coupled coding system. A similar result is also discussed
briefly for the 2-user multiple-access channel.
