Views Read Edit View history. Fountain codes are flexibly applicable at a fixed code rate , or where a fixed code rate cannot be determined a priori, and where efficient encoding and decoding of large amounts of data is required. The thesis is divided into two parts. To this end, we commence by considering the concatenation of Luby transform LT codes, which were the first practical realization of rateless codes, with differential modulators to exploit the inherent coding gain of differential modulations. It may include eg previous versions that are now no longer available. Another application is that of hybrid ARQ in reliable multicast scenarios:

The invention of turbo codes and the re-discovery of sparse graph codes constitute a milestone in error-correction codes designed for communication and storage systems. The first part considers the analysis and design of rateless codes for point-to-point communication. The idea is then extended to a multi-way relay network where a linear-programming design framework is outlined for optimizing degree distributions in terms of transmission efficiency. An encoding scheme is proposed, which is subsequently used to reduce the error floor. The number of downloads is the sum of all downloads of full texts.

# Fountain code – Wikipedia

Erasure codes are used in data storage applications due to massive savings on the number of storage units for a given level of redundancy and reliability. In practice, the broadcast is typically scheduled for a fixed period of time by an operator based on characteristics of the network and receivers and desired delivery reliability, and thus the fountain code ratelese used at a code rate that is determined dynamically at the time when the file is scheduled to be broadcast.

This idea is then extended to LT codes for transmission over erasure channels and a design framework is developed to jointly improve the transmission efficiency and erasure floor performance.

To observe the consequences of the modified encoding scheme, the convergence behavior of the proposed LT code is analyzed using EXIT charts, and shown to be similar to the convergence performance of conventional LT codes.

We optimize the proposed DLT codes in terms of transmission efficiency; thus exhibiting better performance as compared to their conventional counterparts at the expense of increased computational complexity. This code is able to recover a source block from any set of encoded symbols equal to the number of source symbols in the source block with high probability, and in rare cases from slightly more than the number of source symbols in the source block.

## Fountain code

The requirements of erasure code design for data storage, particularly for distributed storage applications, might be quite different relative to communication or data streaming scenarios. Fountain codes are flexibly applicable at a fixed code rateor where a fixed code rate cannot be determined a priori, and where efficient encoding and decoding of large amounts of data is required. A fountain code is optimal if the original k source symbols can be recovered from any k encoding symbols.

It may include eg previous versions that are now no longer available. The thesis is divided into two parts. Thus due to the rateless property, these codes are suitable for transmission over time varying channels. To observe the consequences of the modified encoding scheme, the convergence behavior of the proposed LT code is analyzed using EXIT charts, and shown to be similar to the convergence performance of conventional LT codes.

The invention of turbo codes and the re-discovery of sparse graph codes constitute a milestone in error-correction codes designed for communication and storage systems. An encoding scheme is proposed, which is subsequently used to reduce the error floor. A detailed survey about fountain codes and their applications can be found at.

Thesis kB downloads. We optimize the cores DLT codes in terms of transmission efficiency; thus exhibiting better performance as compared to their conventional counterparts at the expense of increased computational complexity.

This code has an average relative reception overhead of 0. A fountain code is inherently rateless, and as a consequence, such codes may potentially generate an unlimited number of encoded symbols on the fly. To this end, we commence by considering the concatenation of Luby transform LT codes, which were the first practical realization of rateless codes, with differential modulators to exploit the inherent coding gain of differential modulations.

The second part of the thesis deals with the analysis and design of rateless codes for multi-point communication. From Wikipedia, the free encyclopedia.

By using this site, you agree to the Terms of Use and Privacy Policy. In that respect, fountain codes are expected to allow efficient repair process in tehsis of a failure: Retrieved from ” https: This page was last edited on 1 Marchat Then, we delve deeper into the characteristics of LT codes with the objective of improving the error floor performance over noisy channels.

Finally, a design framework is provided for DLT coding schemes, to jointly improve the transmission efficiency and erasure floor performance. Then, we delve deeper into the characteristics of LT codes with the objective of improving the error floor performance over noisy channels.

One example is that of a data carouselwhere some large file is continuously broadcast to a set of receivers. This problem becomes ratepess more apparent when using a traditional short-length erasure code, as the file must be split rateles several blocks, each being separately encoded: Raptor codes are the most efficient fountain codes at this time, [2] having very efficient linear time encoding and decoding algorithms, and requiring only a small constant number of XOR operations per generated symbol for both encoding and decoding.

The invention of turbo codes and the re-discovery of sparse graph codes constitute a milestone in error-correction codes designed for communication and storage systems. In addition, since the bandwidth and communication load between storage nodes can be a bottleneck, codes that allow minimum communication are very beneficial particularly when a node fails and a system reconstruction is needed to achieve the initial level of redundancy.