  We consider the problem of multiple descriptions (MD) source coding and
propose new coding strategies involving both unstructured and structured coding
layers. Previously, the most general achievable rate-distortion (RD) region for
the $l$-descriptions problem was the Combinatorial Message Sharing with Binning
(CMSB) region. The CMSB scheme utilizes unstructured quantizers and
unstructured binning. In the first part of the paper, we show that this
strategy can be improved upon using more general unstructured quantizers and a
more general unstructured binning method. In the second part, structured coding
strategies are considered. First, structured coding strategies are developed by
considering specific MD examples involving three or more descriptions. We show
that application of structured quantizers results in strict RD improvements
when there are more than two descriptions. Furthermore, we show that structured
binning also yields improvements. These improvements are in addition to the
ones derived in the first part of the paper. This suggests that structured
coding is essential when coding over more than two descriptions. Using the
ideas developed through these examples we provide a new unified coding strategy
by considering several structured coding layers. Finally, we characterize its
performance in the form of an inner bound to the optimal rate-distortion region
using computable single-letter information quantities. The new RD region
strictly contains all of the previous known achievable regions.
