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Error detection and correction

About: Error detection and correction is a research topic. Over the lifetime, 29440 publications have been published within this topic receiving 409341 citations. The topic is also known as: error detection & error correction.


Papers
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Journal ArticleDOI
TL;DR: A statistical model for the optical intensity fluctuation at the receiver due to the combined effects of atmospheric turbulence and pointing errors is derived and the effect of beam width, detector size, and jitter variance explicitly is considered.
Abstract: We investigate the performance and design of free-space optical (FSO) communication links over slow fading channels from an information theory perspective. A statistical model for the optical intensity fluctuation at the receiver due to the combined effects of atmospheric turbulence and pointing errors is derived. Unlike earlier work, our model considers the effect of beam width, detector size, and jitter variance explicitly. Expressions for the outage probability are derived for a variety of atmospheric conditions. For given weather and misalignment conditions, the beam width is optimized to maximize the channel capacity subject to outage. Large gains in achievable rate are realized versus using a nominal beam width. In light fog, by optimizing the beam width, the achievable rate is increased by 80% over the nominal beam width at an outage probability of 10-5. Well-known error control codes are then applied to the channel and shown to realize much of the achievable gains.

1,205 citations

Journal ArticleDOI
TL;DR: The results suggest that on a Rayleigh channel, the standard trellis codes may not be the correct approach for improving the reliability of the communication channel.
Abstract: A suboptimal trellis coding approach based on the concept of combining a good convolutional code and bit interleavers is presented. The aim is to improve the reliability of digital radio communication over a fading channel. It is shown that over a Rayleigh channel and for a fixed code complexity the proposed system is superior to the baseline system. Its performance is analyzed using the generalized R/sub o/ and the upper bound on the bit error rate. The results suggest that on a Rayleigh channel, the standard trellis codes may not be the correct approach for improving the reliability of the communication channel. The discussion is restricted to a rate 2/3 coded system with 8-PSK modulation. >

1,074 citations

Journal ArticleDOI
Luigi Rizzo1
01 Apr 1997
TL;DR: A very basic description of erasure codes is provided, an implementation of a simple but very flexible erasure code to be used in network protocols is described, and its performance and possible applications are discussed.
Abstract: Reliable communication protocols require that all the intended recipients of a message receive the message intact. Automatic Repeat reQuest (ARQ) techniques are used in unicast protocols, but they do not scale well to multicast protocols with large groups of receivers, since segment losses tend to become uncorrelated thus greatly reducing the effectiveness of retransmissions. In such cases, Forward Error Correction (FEC) techniques can be used, consisting in the transmission of redundant packets (based on error correcting codes) to allow the receivers to recover from independent packet losses.Despite the widespread use of error correcting codes in many fields of information processing, and a general consensus on the usefulness of FEC techniques within some of the Internet protocols, very few actual implementations exist of the latter. This probably derives from the different types of applications, and from concerns related to the complexity of implementing such codes in software. To fill this gap, in this paper we provide a very basic description of erasure codes, describe an implementation of a simple but very flexible erasure code to be used in network protocols, and discuss its performance and possible applications. Our code is based on Vandermonde matrices computed over GF(pr), can be implemented very efficiently on common microprocessors, and is suited to a number of different applications, which are briefly discussed in the paper. An implementation of the erasure code shown in this paper is available from the author, and is able to encode/decode data at speeds up to several MB/s running on a Pentium 133.

1,067 citations

Journal ArticleDOI
Carl James1
TL;DR: This book discusses human error Successive paradigms Interlanguage and the veto on comparison Learners and native speakers The heyday of Error Analysis Mounting criticism of Error analysis Data collection for Error Analysis.
Abstract: General editor's preface Author's preface Abbreviations 1. Definition and Delimitation Human error Successive paradigms Interlanguage and the veto on comparison Learners and native speakers The heyday of Error Analysis Mounting criticism of Error Analysis Data collection for Error Analysis 2. The Scope of Error Analysis Good English for the English Good English for the L2 learner The native speaker and the power dimension The Incompleteness hypothesis 3. Defining 'Error' Ignorance Measures of deviance Other Dimensions of Error: Error and Mistake Error: Mistake and Acquisition: Learning - An Equation? Lapsology 4. The Description of Errors Error detection Describing errors Error Classification Error Taxonomies Counting errors Profiling and Error Analysis Computerized Corpora of Errors: ICLE - COALA 5. Levels of Error Medium errors Text errors Lexical errors Classifying Lexical errors Grammar errors Discourse errors 6. Diagnosong Error Description and diagnosis Ignorance and avoidance Mother tongue influence: Interlingual errors Target language causes: Intralingual errors Learning-strategy based errors Communication strategy based errors Induced errors Compound and ambiguous errors 7. Error Gravity and Error Evaluation Evaluation Criteria for error gravity 8. Error Correction What is correction? Whether to correct: pros and cons How to do error correction: some options and principles Noticing error 9. A Case Study Elicitation and registration Error identification Categorizing the errors Status: error or mistake? Diagnosis Bibliography Index

1,058 citations

Journal ArticleDOI
TL;DR: This tutorial paper begins with an elementary presentation of the fundamental properties and structure of convolutional codes and proceeds with the development of the maximum likelihood decoder, which yields for arbitrary codes both the distance properties and upper bounds on the bit error probability.
Abstract: This tutorial paper begins with an elementary presentation of the fundamental properties and structure of convolutional codes and proceeds with the development of the maximum likelihood decoder. The powerful tool of generating function analysis is demonstrated to yield for arbitrary codes both the distance properties and upper bounds on the bit error probability for communication over any memoryless channel. Previous results on code ensemble average error probabilities are also derived and extended by these techniques. Finally, practical considerations concerning finite decoding memory, metric representation, and synchronization are discussed.

1,040 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023189
2022417
2021617
2020949
20191,040
2018997