Error Correction for Index Coding With Coded Side Information

Index coding is a source coding problem in which a broadcaster seeks to meet the different demands of several users, each of whom is assumed to have some prior information on the data held by the sender. If the sender knows its clients' requests and their side-information sets, then the number of packet transmissions required to satisfy all users' demands can be greatly reduced if the data is encoded before sending. The collection of side-information indices as well as the indices of the requested data is described as an instance of the index coding with side-information (ICSI) problem. The encoding function is called the index code of the instance, and the number of transmissions employed by the code is referred to as its length. The main ICSI problem is to determine the optimal length of an index code for and instance. As this number is hard to compute, bounds approximating it are sought, as are algorithms to compute efficient index codes. Two interesting generalizations of the problem that have appeared in the literature are the subject of this work. The first of these is the case of index coding with coded side information, in which linear combinations of the source data are both requested by and held as users' side-information. The second is the introduction of error-correction in the problem, in which the broadcast channel is subject to noise. In this paper we characterize the optimal length of a scalar or vector linear index code with coded side information (ICCSI) over a finite field in terms of a generalized min-rank and give bounds on this number based on constructions of random codes for an arbitrary instance. We furthermore consider the length of an optimal error correcting code for an instance of the ICCSI problem and obtain bounds on this number, both for the Hamming metric and for rank-metric errors. We describe decoding algorithms for both categories of errors

Enabling decentralized wireless index coding in practice

Index coding is a problem in theoretical computer science and network information theory that studies the optimal coding scheme for transmitting multiple messages across a network to receivers with different side information. The ultimate goal of index coding is to reduce transmission time in a communication network by minimizing the number of messages based on shared information. Index coding theory extends to several key engineering problems in network communication including peer to peer communication, distributed broadcast networks, and interference alignment. Although the theoretical connection between index coding and wireless networks is valuable, we focus on finding index coding strategies for a realistic wireless network. More specifically, we investigate how index coding can be applied to an OFDMA downlink network during the retransmission phase. An orthogonal frequency-division multiple access (OFDMA) downlink network is a network where data is sent downward from a designated higher-level transmitter to a group of receiving nodes. In addition, receivers can often decode the other receivers' physical layer signals on the other sub-channels that can be exploited as side information. If this side information is sent back to the transmitter, it can then be coded to cancel the interference in subsequent retransmission phases resulting in fewer retransmission messages. In this report, we explain the coding model and characterize the benefits of index coding for retransmissions within an OFDMA downlink network. In addition, we demonstrate the results of applying this index coding scheme in such network in both simulation and in an active wireless mesh network.Electrical and Computer Engineerin

Capacity of Coded Index Modulation

We consider the special case of index coding over the Gaussian broadcast channel where each receiver has prior knowledge of a subset of messages at the transmitter and demands all the messages from the source. We propose a concatenated coding scheme for this problem, using an index code for the Gaussian channel as an inner code/modulation to exploit side information at the receivers, and an outer code to attain coding gain against the channel noise. We derive the capacity region of this scheme by viewing the resulting channel as a multiple-access channel with many receivers, and relate it to the 'side information gain' -- which is a measure of the advantage of a code in utilizing receiver side information -- of the inner index code/modulation. We demonstrate the utility of the proposed architecture by simulating the performance of an index code/modulation concatenated with an off-the-shelf convolutional code through bit-interleaved coded-modulation.Comment: To appear in Proc. IEEE Int. Symp. Inf. Theory (ISIT) 2015, Hong Kong, Jun. 2015. 5 pages, 4 figure

Design and Analysis of Efficient Index Coding Methods for Future Wireless Communications

This thesis considers the problem of efficient broadcast in a system where a single server transmits a set of messages to a number of users via a noiseless broadcast channel. Each user requests one specific message and may know some of the other messages a priori as its side information. This problem is known as the index coding problem and was first introduced by Birk and Kol [Birk and Kol, 1998], in the context of satellite communications. Exploiting the side information of the receivers along with the coding techniques at the server can reduce the number of transmissions to satisfy all the receivers. The simple model in index coding can establish a useful framework for studying other research areas, including network coding, distributed storage systems, and coded caching. In this thesis, index coding is approached from a new perspective to propose a new scalar linear coding scheme called the update-based maximum column distance (UMCD) coding scheme. In the beginning, the receivers are sorted based on the size of their side information. Then, in each transmission, a linear combination of the messages is designed to instantaneously satisfy one of the receivers with the minimum size of side information. Then, the problem is updated by eliminating all receivers who are able to decode their requested message from the coded messages received so far along with the messages in their side information. This process is repeated until all receivers can successfully decode their requested message. Concrete instances are provided to show that the proposed UMCD coding scheme has a better broadcast performance compared to the most efficient existing coding schemes, including the recursive coding scheme (Arbabjolfaei and Kim, 2014) and the interlinked-cycle cover coding scheme (Thapa et al., 2017). Also in this thesis, the insufficiency of linear coding and the necessity of nonlinear codes for index coding problem are investigated, with two main contributions. First, while the insufficiency of linear coding has been proved for network coding (Dougherty et al., 2005), groupcast index coding (Effros et al., 2015), and asymmetric-rate unicast index coding (Maleki et al., 2014), it remained an open problem for symmetric-rate unicast index coding. In this thesis, we settle this open question by constructing two symmetric-rate unicast index coding instances of sizes 33 and 36 for which optimal linear coding is outperformed by nonlinear codes. Second, while it has been known that the insufficiency of linear coding is due to the dependency of its rate on the field size, this dependency has been illustrated only over fields with characteristic two. In this thesis, we extend this limit to the fields with characteristic three by constructing two index coding instances of size 29. It is shown that while for the first instance, linear coding is optimal only over fields with characteristic three, for the second instance, linear coding over any fields with characteristic three can never be optimal. Finally in this thesis, a new coding scheme called the independent user partition multicast (IUPM) is proposed for the groupcast index coding. It is proved that the proposed IUPM coding scheme includes the two most efficient coding schemes, namely the user partition multicast (Shanmugam et al., 2015) and the packet partition multicast (Tehrani et al., 2012), as special cases. Then, a new polynomial-time algorithm for solving the general groupcast index coding problem is proposed. We show that the proposed heuristic algorithm can outperform the approximation partition multicast coding scheme (Unal and Wagner, 2016) for a class of groupcast index coding instances