3 research outputs found
On Index Coding and Graph Homomorphism
In this work, we study the problem of index coding from graph homomorphism
perspective. We show that the minimum broadcast rate of an index coding problem
for different variations of the problem such as non-linear, scalar, and vector
index code, can be upper bounded by the minimum broadcast rate of another index
coding problem when there exists a homomorphism from the complement of the side
information graph of the first problem to that of the second problem. As a
result, we show that several upper bounds on scalar and vector index code
problem are special cases of one of our main theorems.
For the linear scalar index coding problem, it has been shown in [1] that the
binary linear index of a graph is equal to a graph theoretical parameter called
minrank of the graph. For undirected graphs, in [2] it is shown that
if and only if there exists a homomorphism from
to a predefined graph . Combining these two results, it
follows that for undirected graphs, all the digraphs with linear index of at
most k coincide with the graphs for which there exists a homomorphism from
to . In this paper, we give a direct proof to this result
that works for digraphs as well.
We show how to use this classification result to generate lower bounds on
scalar and vector index. In particular, we provide a lower bound for the scalar
index of a digraph in terms of the chromatic number of its complement.
Using our framework, we show that by changing the field size, linear index of
a digraph can be at most increased by a factor that is independent from the
number of the nodes.Comment: 5 pages, to appear in "IEEE Information Theory Workshop", 201
The Single-Uniprior Index-Coding Problem: The Single-Sender Case and The Multi-Sender Extension
Index coding studies multiterminal source-coding problems where a set of
receivers are required to decode multiple (possibly different) messages from a
common broadcast, and they each know some messages a priori. In this paper, at
the receiver end, we consider a special setting where each receiver knows only
one message a priori, and each message is known to only one receiver. At the
broadcasting end, we consider a generalized setting where there could be
multiple senders, and each sender knows a subset of the messages. The senders
collaborate to transmit an index code. This work looks at minimizing the number
of total coded bits the senders are required to transmit. When there is only
one sender, we propose a pruning algorithm to find a lower bound on the optimal
(i.e., the shortest) index codelength, and show that it is achievable by linear
index codes. When there are two or more senders, we propose an appending
technique to be used in conjunction with the pruning technique to give a lower
bound on the optimal index codelength; we also derive an upper bound based on
cyclic codes. While the two bounds do not match in general, for the special
case where no two distinct senders know any message in common, the bounds
match, giving the optimal index codelength. The results are expressed in terms
of strongly connected components in directed graphs that represent the
index-coding problems.Comment: Author final manuscrip