Mahesh Babu Vaddi

Optimal Scalar Linear Index Codes for One-Sided Neighboring Side-Information Problems

The capacity of symmetric neighboring and consecutive side-information single unicast index coding problem (SNC-SUICP) with number of messages equal to the number of receivers was given by Maleki, Cadambe and Jafar. In this paper, we construct binary matrices of size

Optimal vector linear index codes for some symmetric side information problems

m \times n~(m \geq n)

Optimal Scalar Linear Index Codes for Some Symmetric Multiple Unicast Problems

such that any

Optimal Index Codes for a New Class of Interlinked Cycle Structure

n

Low-Complexity Decoding for Symmetric, Neighboring and Consecutive Side-information Index Coding Problems.

adjacent rows of the matrix are linearly independent over every field. By using such matrices, we give an optimal scalar linear index code for the one-sided SNC-SUICP considered by Maleki, Cadambe and Jafar for any given number of messages and one-sided side- information. The constructed codes are independent of field size and hence works over every field.

A Lifting Construction for Scalar Linear Index Codes.

This paper deals with vector linear index codes for multiple unicast index coding problems where there is a source with K messages and there are K receivers each wanting a unique message and having symmetric (with respect to the receiver index) two-sided antidotes (side information). Starting from a given multiple unicast index coding problem with K messages and symmetric one-sided antidotes for which a scalar linear index code ℭ is known, we give a construction procedure which constructs a sequence (indexed by m) of multiple unicast index coding problems with symmetric two-sided antidotes (for the same source) for all of which a vector linear code ℭ(m) is obtained from ℭ. Also, it is shown that if ℭ is optimal then ℭ(m) is also optimal for all m. To our knowledge, this is the first paper which gives a method to construct a sequence of optimal vector linear index codes.