2,772 research outputs found
Reduced Dimensional Optimal Vector Linear Index Codes for Index Coding Problems with Symmetric Neighboring and Consecutive Side-information
A single unicast index coding problem (SUICP) with symmetric neighboring and
consecutive side-information (SNCS) has messages and receivers, the
th receiver wanting the th message and having the
side-information . The single unicast index coding problem with
symmetric neighboring and consecutive side-information, SUICP(SNCS), is
motivated by topological interference management problems in wireless
communication networks. Maleki, Cadambe and Jafar obtained the symmetric
capacity of this SUICP(SNCS) and proposed optimal length codes by using
Vandermonde matrices. In our earlier work, we gave optimal length
-dimensional vector linear index codes for SUICP(SNCS) satisfying some
conditions on and \cite{VaR1}. In this paper, for SUICP(SNCS) with
arbitrary and , we construct optimal length
-dimensional vector linear index codes. We
prove that the constructed vector linear index code is of minimal dimension if
is equal to . The proposed
construction gives optimal length scalar linear index codes for the SUICP(SNCS)
if divides both and . The proposed construction is independent
of field size and works over every field. We give a low-complexity decoding for
the SUICP(SNCS). By using the proposed decoding method, every receiver is able
to decode its wanted message symbol by simply adding some index code symbols
(broadcast symbols).Comment: 13 pages, 1 figure and 5 table
On Approximating the Sum-Rate for Multiple-Unicasts
We study upper bounds on the sum-rate of multiple-unicasts. We approximate
the Generalized Network Sharing Bound (GNS cut) of the multiple-unicasts
network coding problem with independent sources. Our approximation
algorithm runs in polynomial time and yields an upper bound on the joint source
entropy rate, which is within an factor from the GNS cut. It
further yields a vector-linear network code that achieves joint source entropy
rate within an factor from the GNS cut, but \emph{not} with
independent sources: the code induces a correlation pattern among the sources.
Our second contribution is establishing a separation result for vector-linear
network codes: for any given field there exist networks for which
the optimum sum-rate supported by vector-linear codes over for
independent sources can be multiplicatively separated by a factor of
, for any constant , from the optimum joint entropy
rate supported by a code that allows correlation between sources. Finally, we
establish a similar separation result for the asymmetric optimum vector-linear
sum-rates achieved over two distinct fields and
for independent sources, revealing that the choice of field
can heavily impact the performance of a linear network code.Comment: 10 pages; Shorter version appeared at ISIT (International Symposium
on Information Theory) 2015; some typos correcte
On Critical Index Coding Problems
The question of under what condition some side information for index coding
can be removed without affecting the capacity region is studied, which was
originally posed by Tahmasbi, Shahrasbi, and Gohari. To answer this question,
the notion of unicycle for the side information graph is introduced and it is
shown that any edge that belongs to a unicycle is critical, namely, it cannot
be removed without reducing the capacity region. Although this sufficient
condition for criticality is not necessary in general, a partial converse is
established, which elucidates the connection between the notion of unicycle and
the maximal acylic induced subgraph outer bound on the capacity region by
Bar-Yossef, Birk, Jayram, and Kol.Comment: 5 pages, accepted to 2015 IEEE Information Theory Workshop (ITW),
Jeju Island, Kore
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