174,912 research outputs found
On the Capacity Region for Index Coding
A new inner bound on the capacity region of a general index coding problem is
established. Unlike most existing bounds that are based on graph theoretic or
algebraic tools, the bound is built on a random coding scheme and optimal
decoding, and has a simple polymatroidal single-letter expression. The utility
of the inner bound is demonstrated by examples that include the capacity region
for all index coding problems with up to five messages (there are 9846
nonisomorphic ones).Comment: 5 pages, 6 figures, accepted to the 2013 IEEE International Symposium
on Information Theory (ISIT), Istanbul, Turkey, July 201
On the Capacity Region for Secure Index Coding
We study the index coding problem in the presence of an eavesdropper, where
the aim is to communicate without allowing the eavesdropper to learn any single
message aside from the messages it may already know as side information. We
establish an outer bound on the underlying secure capacity region of the index
coding problem, which includes polymatroidal and security constraints, as well
as the set of additional decoding constraints for legitimate receivers. We then
propose a secure variant of the composite coding scheme, which yields an inner
bound on the secure capacity region of the index coding problem. For the
achievability of secure composite coding, a secret key with vanishingly small
rate may be needed to ensure that each legitimate receiver who wants the same
message as the eavesdropper, knows at least two more messages than the
eavesdropper. For all securely feasible index coding problems with four or
fewer messages, our numerical results establish the secure index coding
capacity region
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
Linear Codes are Optimal for Index-Coding Instances with Five or Fewer Receivers
We study zero-error unicast index-coding instances, where each receiver must
perfectly decode its requested message set, and the message sets requested by
any two receivers do not overlap. We show that for all these instances with up
to five receivers, linear index codes are optimal. Although this class contains
9847 non-isomorphic instances, by using our recent results and by properly
categorizing the instances based on their graphical representations, we need to
consider only 13 non-trivial instances to solve the entire class. This work
complements the result by Arbabjolfaei et al. (ISIT 2013), who derived the
capacity region of all unicast index-coding problems with up to five receivers
in the diminishing-error setup. They employed random-coding arguments, which
require infinitely-long messages. We consider the zero-error setup; our
approach uses graph theory and combinatorics, and does not require long
messages.Comment: submitted to the 2014 IEEE International Symposium on Information
Theory (ISIT
Broadcast Rate Requires Nonlinear Coding in a Unicast Index Coding Instance of Size 36
Insufficiency of linear coding for the network coding problem was first
proved by providing an instance which is solvable only by nonlinear network
coding (Dougherty et al., 2005).Based on the work of Effros, et al., 2015, this
specific network coding instance can be modeled as a groupcast index coding
(GIC)instance with 74 messages and 80 users (where a message can be requested
by multiple users). This proves the insufficiency of linear coding for the GIC
problem. Using the systematic approach proposed by Maleki et al., 2014, the
aforementioned GIC instance can be cast into a unicast index coding (UIC)
instance with more than 200 users, each wanting a unique message. This confirms
the necessity of nonlinear coding for the UIC problem, but only for achieving
the entire capacity region. Nevertheless, the question of whether nonlinear
coding is required to achieve the symmetric capacity (broadcast rate) of the
UIC problem remained open. In this paper, we settle this question and prove the
insufficiency of linear coding, by directly building a UIC instance with only
36users for which there exists a nonlinear index code outperforming the optimal
linear code in terms of the broadcast rate
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