Burst Error Correction
•
0 likes•376 views
This document discusses using interleaving to combat burst errors in Reed-Solomon (RS) codes. It introduces interleaving as a technique that spreads long burst errors into random errors. The project tests increasing the code length and interleaving degree, finding that burst error correction improves when both are increased together. Increasing the error correction capability also increases bandwidth usage and encoding/decoding delays, so transmission rates must be considered. In conclusion, interleaving significantly reduces burst errors, with better performance from higher interleaving degrees and code lengths.
Report
Share
Report
Share
Download to read offline
![Burst Error Correction In RS Codes
Aditi Singal, Santosh Nagaraj
Electrical and Computer Engineering , San Diego State University
Introduction
• In communication systems the noise present in the channel are
generally assumed to be Additive White Gaussian Noise, which
has a Gaussian distribution. In real, the channel noise is not
always AWGN. Instead, the distribution of error is more complex
and the error rate varies over a range of time. Error correcting
codes improve the functioning and consistency of modern
digital communication system.
• Different FEC coding methods are used in the digital
communication systems. They are mainly classified into block
and convolutional codes [1-2].
• The aim of this project is to design a code that is efficient and
suitable to implement in wireless transmission systems
• The technique of interleaving a code is used to detect and
correct the burst error.
Project approach
• The general idea behind using interleaving is to spread the long
burst of error into random error.
• The simple interleaving can be achieved by using the degree of
interleaving denoted by λ , where λ -1 should be the multiple
of n.
• Interleaving is done by entering the data row wise in an
interleaver and taking a column wise output at the
deinterleaver.
Figure 1 A block interleaving system
Results
• Increasing the length of message bit for each block was
tested.
• Interleaving is the best way to combat burst errors because
Encoder and decoder uses shift registers
Decoder of interleaved code can be derived from the
d decoder of original code
• BER becomes better for the interleaving degree of 35 when the
length is 400. The code can correct more burst errors when the
length and degree of interleaving is increased at the same time
• Coding techniques with higher error detection and correction
capability will use more redundant bits and bandwidth. This
reduces information transmission rates and will increase the
delay for encoding and decoding at source and destination.
Thus, on the design of higher error correcting codes the factor
affecting the transmission rate should be wisely considered.
Figure 2 BER performance of interleaved RS codes
Discussions
• When the MATLAB code was implemeted for the project, it was
observed that the length of the code should be proportional to
the interleaving degree of the system
• If the error correcting capability of the code is greater than the
length of the codeword input, then the burst error cannot be
corrected by the interleaver..
• Burst Error correction capability depends on the length of the
code as well as the interleaving degree of the system.
• At the deinterleaver, the original data is obtained with the burst
error converted to random errors and spread thruoghout the
codeword length.
Concluding Remarks
• From the project, it is deduced that interleaving reduces the
burst error in transmitted data by a huge percentage.
• BER becomes better when the interleaving degree and code
length are increased simultaneously.
Reference
1. https://espace.cdu.edu.au/eserv/cdu:38795/Thesis_CDU_38
795_Rupakheti_S.pdf
2. Error Control Coding: Fundamentals and Applications (2nd
Edition) Textbook by Shu Lin, Daniel J. Costello](https://image.slidesharecdn.com/42cffb8c-a843-4c43-95f0-b8c423df92dd-170109005234/85/Burst-Error-Correction-1-320.jpg)
Recommended
New error-detection
This document discusses various techniques for error detection and correction in digital communications. It describes common types of errors like single-bit and burst errors. It then explains different coding schemes for error detection and correction including block coding, linear block codes like parity codes and Hamming codes, and cyclic redundancy checks (CRCs). Key concepts covered are redundancy, minimum Hamming distance requirements for detection and correction capabilities, and encoders and decoders for different coding schemes.
Error detection and correction
This document discusses error detection and correction in data transmission. It describes single-bit errors, where one bit is corrupted, and burst errors, where multiple contiguous bits are corrupted. Error detection allows a receiver to detect if errors occurred, while error correction identifies the exact corrupted bits. Redundant bits are added to messages to enable detection and correction. Methods include forward error correction, retransmission, block coding, and convolution coding. Block coding divides messages into blocks with redundant bits added, creating codewords that allow error detection if a codeword is invalid.
Error Correction of Burst error
The document is a report submitted to a lecturer that discusses error detection and correction of burst errors. It first defines key concepts like Hamming codes and burst errors. It then describes how burst errors occur when multiple adjacent bits are flipped and explains how redundancy can be used to detect and correct burst errors. Specifically, it notes that linear codes can correct all burst errors of length t or less if the errors occur in distinct cosets, allowing them to be identified and corrected based on their syndrome. The report provides examples of burst errors and definitions of burst error parameters like location and pattern.
Error control coding
This document discusses error control coding, which introduces redundancies into transmitted data to enable error detection and correction. It describes different types of errors that can occur, as well as techniques for error detection like vertical redundancy checking (parity), checksums, longitudinal redundancy checking, and cyclic redundancy checking. Error correction techniques discussed include retransmission of corrupted data as well as forward error correction using redundant bits to detect and fix errors. Specific codes like Hamming code that can correct single bit errors are also mentioned.
Error Detection And Correction
Networks must reliably transfer data between devices with complete accuracy. Errors can occur during data transmission and must be detected and corrected for reliable communication. Error detection and correction can be implemented at the data link or transport layers, and works by adding redundant bits to detect errors without having the original message. Common types of redundancy checks used include vertical redundancy check and cyclic redundancy check.
Error correction and Detection technique while sending the message
This ppt is helpful the student of computer science and IT student which are preparing the seminor on the error correction and detection.
Coding Scheme/ Information theory/ Error coding scheme
(i) Information theory is a branch of mathematics dealing with quantifying information. It was developed by Claude Shannon and involves key concepts like entropy which measures uncertainty.
(ii) Error coding schemes allow for reliable communication over unreliable channels by detecting and correcting errors. Common schemes include repetition codes, parity bits, checksums, and cyclic redundancy checks.
(iii) Forward error correction adds redundant bits that allow the receiver to correct errors without retransmission. Applications of error coding include internet protocols, deep space communications, satellite broadcasting, data storage, and memory.
Error detection & correction presentation
This document discusses error detection and correction in data transmission. It describes two types of errors: single-bit errors, where one bit is corrupted, and burst errors, where multiple contiguous bits are corrupted. Redundancy is added through techniques like forward error correction and coding to detect or correct errors. Specifically, it explains Hamming coding, where redundant bits are added to data blocks to create codewords, allowing the receiver to detect errors when a codeword is received incorrectly.
Recommended
New error-detection
This document discusses various techniques for error detection and correction in digital communications. It describes common types of errors like single-bit and burst errors. It then explains different coding schemes for error detection and correction including block coding, linear block codes like parity codes and Hamming codes, and cyclic redundancy checks (CRCs). Key concepts covered are redundancy, minimum Hamming distance requirements for detection and correction capabilities, and encoders and decoders for different coding schemes.
Error detection and correction
This document discusses error detection and correction in data transmission. It describes single-bit errors, where one bit is corrupted, and burst errors, where multiple contiguous bits are corrupted. Error detection allows a receiver to detect if errors occurred, while error correction identifies the exact corrupted bits. Redundant bits are added to messages to enable detection and correction. Methods include forward error correction, retransmission, block coding, and convolution coding. Block coding divides messages into blocks with redundant bits added, creating codewords that allow error detection if a codeword is invalid.
Error Correction of Burst error
The document is a report submitted to a lecturer that discusses error detection and correction of burst errors. It first defines key concepts like Hamming codes and burst errors. It then describes how burst errors occur when multiple adjacent bits are flipped and explains how redundancy can be used to detect and correct burst errors. Specifically, it notes that linear codes can correct all burst errors of length t or less if the errors occur in distinct cosets, allowing them to be identified and corrected based on their syndrome. The report provides examples of burst errors and definitions of burst error parameters like location and pattern.
Error control coding
This document discusses error control coding, which introduces redundancies into transmitted data to enable error detection and correction. It describes different types of errors that can occur, as well as techniques for error detection like vertical redundancy checking (parity), checksums, longitudinal redundancy checking, and cyclic redundancy checking. Error correction techniques discussed include retransmission of corrupted data as well as forward error correction using redundant bits to detect and fix errors. Specific codes like Hamming code that can correct single bit errors are also mentioned.
Error Detection And Correction
Networks must reliably transfer data between devices with complete accuracy. Errors can occur during data transmission and must be detected and corrected for reliable communication. Error detection and correction can be implemented at the data link or transport layers, and works by adding redundant bits to detect errors without having the original message. Common types of redundancy checks used include vertical redundancy check and cyclic redundancy check.
Error correction and Detection technique while sending the message
This ppt is helpful the student of computer science and IT student which are preparing the seminor on the error correction and detection.
Coding Scheme/ Information theory/ Error coding scheme
(i) Information theory is a branch of mathematics dealing with quantifying information. It was developed by Claude Shannon and involves key concepts like entropy which measures uncertainty.
(ii) Error coding schemes allow for reliable communication over unreliable channels by detecting and correcting errors. Common schemes include repetition codes, parity bits, checksums, and cyclic redundancy checks.
(iii) Forward error correction adds redundant bits that allow the receiver to correct errors without retransmission. Applications of error coding include internet protocols, deep space communications, satellite broadcasting, data storage, and memory.
Error detection & correction presentation
This document discusses error detection and correction in data transmission. It describes two types of errors: single-bit errors, where one bit is corrupted, and burst errors, where multiple contiguous bits are corrupted. Redundancy is added through techniques like forward error correction and coding to detect or correct errors. Specifically, it explains Hamming coding, where redundant bits are added to data blocks to create codewords, allowing the receiver to detect errors when a codeword is received incorrectly.
Error detection correction (CRC)
This is the slide about assembly language.
in this slide you are gonna learn about cyclic redundancy check
Error Detection and Correction presentation
Data can be corrupted during transmission. For reliable communication, errors must be detected and correcte
Error correction error detection in digital communication
This document discusses error detection and correction techniques. It describes different types of errors like single-bit errors and burst errors. It then explains various error detection methods like vertical redundancy check (VRC), longitudinal redundancy check (LRC), cyclic redundancy check (CRC), and checksum that work by adding redundant bits. CRC is more powerful than VRC and LRC as it can detect all single and some multiple bit errors. The document also covers error correction techniques like single-bit error correction using Hamming code that allows detecting and correcting single bit errors.
Full error detection and correction
This document discusses error detection and correction techniques used at the data link layer. It describes different types of errors that can occur like single-bit and burst errors. Error detection methods like parity checks, cyclic redundancy checks (CRC), and checksums are explained. Forward error correction codes like Hamming codes that allow for error correction are also covered. The document provides examples to illustrate how various error detection and correction schemes work.
Error detection and correction, flow and error control and trasmission media
1) Errors can occur during data transmission due to interference that changes signal shapes. There are two types of errors: single-bit errors affecting one bit, and burst errors affecting multiple consecutive bits.
2) Error detection allows a receiver to detect errors without correcting them, using redundancy by adding extra bits. Error correction detects and corrects errors using even more redundancy.
3) Flow control regulates the amount of data sent before waiting for acknowledgment. Error control detects and retransmits damaged frames using automatic repeat request.
4) Transmission media are either guided (wired) using twisted pair, coaxial cable and fiber optics, or unguided (wireless) using radio waves, microwaves and infrared.
GROUP03_AMAK:ERROR DETECTION AND CORRECTION PPT
This document discusses error detection and correction techniques. It introduces concepts like redundancy, forward error correction, retransmission, linear block coding, Hamming codes, and cyclic redundancy checks (CRC). Specific error correction codes covered include Hamming codes, which use modulo-2 arithmetic to add redundant bits to detect and correct single bit errors. CRC codes are also discussed, which use cyclic codes and polynomial representations to detect errors by computing a syndrome value. The document provides information on generating and detecting errors for different codes.
Error detection and correction
This document discusses error detection and correction in digital communication. It describes how coding schemes add redundancy to messages through techniques like block coding and convolution coding to detect or correct errors. The encoder adds redundant bits to original messages to create relationships between bits that the decoder can use to check for errors. It also explains the use of modular arithmetic, specifically modulo-2 arithmetic which uses only 1s and 0s, for error detection and correction operations.
Cyclic redundancy check
Cyclic Redundancy Codes (CRCs) provide a first line of defense against data corruption in many networks. Unfortunately, many commonly used CRC polynomials provide significantly less error detection capability than they might. An exhaustive exploration reveals that most previously published CRC polynomials are either inferior to alternatives or are only good choices for particular message lengths.
Error detection and correction
This document discusses various topics related to network transmission including:
- Different types of errors that can occur such as single-bit errors and burst errors.
- How error detection and correction works using redundant bits to detect if errors have occurred and in some cases correct the errors.
- Forward error correction versus retransmission for dealing with errors.
- Modular arithmetic and how it relates to error correction by using arithmetic operations on data and redundant bits.
Error detection and correction
Error coding uses mathematical formulas to encode data bits into longer code words for transmission. This allows errors caused by environmental interference to be detected and sometimes corrected at the destination. There are two main types of error coding: error-detecting codes and error-correcting codes. Error-detecting codes add enough redundancy to allow errors to be detected but not corrected, while error-correcting codes add more redundancy to allow errors to be corrected. Common error-detecting coding techniques include parity checks, checksums, and cyclic redundancy checks (CRCs). These techniques use additional redundant bits appended to the data to facilitate error detection. CRC is particularly powerful as it can detect all single-bit errors and many burst errors.
Lecture 22
The document discusses error correction techniques for data communication and networking. It describes two main error correction methods: error correction by retransmission, which has the receiver request retransmission of data if an error is detected; and forward error correction, which uses error-correcting codes to automatically correct certain errors. The document then focuses on Hamming codes, explaining how they use redundancy bits to detect and correct errors in binary data. Specific aspects of Hamming codes like bit arrangements and calculations are provided, along with an example of how they can correct burst errors.
Error detection and correction
This document discusses error detection and correction techniques used in data communication networks. It describes common types of transmission errors like single bit errors and burst errors. It then explains different error detection methods including parity checking, longitudinal redundancy checking (LRC), and checksum checking. It also covers error correction techniques like Go-Back-N and Selective Repeat that allow retransmission of only corrupted frames. Flow control mechanisms like stop-and-wait and sliding window protocols are also summarized.
Error detection in Data Communication System
This document discusses error detection techniques including cyclic redundancy checks (CRCs) and discusses the differences between bit rate errors and frame rate errors. It can be summarized as:
1. CRCs are a commonly used error detection technique where a check value is calculated based on the data and transmitted with it to allow the receiver to check for errors.
2. Bit rate error refers to the rate of errors in transmitted bits, while frame rate error refers to the ratio of data received with errors to the total data received.
3. A method is presented for estimating both bit error rate and frame error rate for low-density parity-check codes based on enumerating the smallest weight error patterns that cannot be corrected.
DCN Error Detection & Correction
This document provides an overview of error detection and correction techniques used in digital communication systems. It defines different types of errors like single bit errors and burst errors that can occur during signal transmission. It also describes various error detection methods like parity checking, checksum detection, and cyclic redundancy check (CRC). The document explains concepts of forward error correction (FEC), automatic repeat request (ARQ), and CRC checkers. It provides block diagrams of the basic ARQ system and its operations.
Error correction, ARQ, FEC
There are two basic approaches to error correction: automatic-repeat-request (ARQ) and forward error correction (FEC). ARQ requires retransmitting frames where errors are detected, while FEC allows the receiver to detect and correct a limited number of errors without contacting the transmitter by using error correction codes. Common ARQ techniques include stop-and-wait, go-back-n, and selective-repeat. FEC works by adding redundant bits that enable the receiver to determine the most likely intended message even if some bits are received in error.
Cyclic Redundancy Check in Computers Network
1) Cyclic redundancy check (CRC) is a method for detecting errors in digital data during transmission over unreliable communication channels. It works by using a generator polynomial to generate a checksum that is appended to the transmitted data.
2) At the sender, the data bits are divided by the generator polynomial to calculate a remainder which becomes the CRC checksum. This checksum is appended to the data before transmission.
3) At the receiver, the received data and checksum are divided again by the same generator polynomial. If the remainder is zero, then no errors were detected in the received data. A non-zero remainder indicates errors were detected.
Error Detection N Correction
The document discusses error detection and correction techniques. It introduces Hamming codes, which can detect up to two bit errors and correct one bit errors. It explains how Hamming codes work by adding redundant parity bits to messages based on the values of data bits. A 4x7 generator matrix is used to encode 4-bit data words into 7-bit codewords for the Hamming(7,4) code. An example shows how a data word of 1010 encodes to the codeword 1011010. The summary then tests a C++ implementation of Hamming code encoding.
Error control, parity check, check sum, vrc
The document discusses various methods for error detection in digital communication, including:
1. Parity checking, which adds an extra parity bit to ensure an even or odd number of 1s. Two-dimensional parity divides data into a grid and adds a redundant row.
2. Checksums, which divide data into sections, add the sections using one's complement arithmetic, complement the sum, and send it along with the data for verification.
3. Vertical redundancy checking adds a parity bit to each character to detect single-bit errors and some multiple-bit errors. It is often used with ASCII encoding.
Channel Coding (Error Control Coding)
power point presentation
By : Ola Mashaqi, Suhad Malayshe, Mais Masri
Annajah national University
Telecommunications Engineers
Lecture 21
This document provides an overview of CRC (Cyclic Redundancy Check) and checksum techniques for error detection in data transmission. It describes how CRC works by appending redundant bits to the data such that the resulting data is divisible by a predetermined binary number. It also explains how checksums are generated by dividing the data into sections, adding the sections using one's complement arithmetic, and sending the complement of the sum along with the data. The document compares the performance of CRC and checksums, noting that CRC can detect all odd-length burst errors while checksums are susceptible to some even-length errors.
Paper id 312201514
This document summarizes forward error correction techniques using convolutional encoders and Viterbi decoders. It first provides background on communication channels and the need for error correction when transmitting data. It then describes convolutional coding, a technique that maps a continuous stream of input bits to a continuous stream of encoded output bits using shift registers, with the encoded bits depending on current and past input bits. The key aspects of convolutional encoders are discussed, including parameters like the number of output bits, input bits, and shift registers. Generator polynomials are also introduced as characterizing the encoder connections. Viterbi decoding is highlighted as a maximum likelihood algorithm for decoding the trellis structure of convolutional codes based on soft decisions.
Applications of information theory in communication engineering
This document provides an overview of information theory and its applications in communication engineering. It discusses key concepts such as source coding techniques like lossless and lossy data compression, algorithms like Huffman coding and arithmetic coding. It also covers channel coding techniques including error detection codes, forward error correction, block codes, convolutional codes, turbo codes and their applications in areas like digital television, DVDs, wireless communications. The document concludes that information theory provides fundamental limits for efficient digital communication and coding applications have improved reliability and efficiency of modern communication systems.
More Related Content
What's hot
Error detection correction (CRC)
This is the slide about assembly language.
in this slide you are gonna learn about cyclic redundancy check
Error Detection and Correction presentation
Data can be corrupted during transmission. For reliable communication, errors must be detected and correcte
Error correction error detection in digital communication
This document discusses error detection and correction techniques. It describes different types of errors like single-bit errors and burst errors. It then explains various error detection methods like vertical redundancy check (VRC), longitudinal redundancy check (LRC), cyclic redundancy check (CRC), and checksum that work by adding redundant bits. CRC is more powerful than VRC and LRC as it can detect all single and some multiple bit errors. The document also covers error correction techniques like single-bit error correction using Hamming code that allows detecting and correcting single bit errors.
Full error detection and correction
This document discusses error detection and correction techniques used at the data link layer. It describes different types of errors that can occur like single-bit and burst errors. Error detection methods like parity checks, cyclic redundancy checks (CRC), and checksums are explained. Forward error correction codes like Hamming codes that allow for error correction are also covered. The document provides examples to illustrate how various error detection and correction schemes work.
Error detection and correction, flow and error control and trasmission media
1) Errors can occur during data transmission due to interference that changes signal shapes. There are two types of errors: single-bit errors affecting one bit, and burst errors affecting multiple consecutive bits.
2) Error detection allows a receiver to detect errors without correcting them, using redundancy by adding extra bits. Error correction detects and corrects errors using even more redundancy.
3) Flow control regulates the amount of data sent before waiting for acknowledgment. Error control detects and retransmits damaged frames using automatic repeat request.
4) Transmission media are either guided (wired) using twisted pair, coaxial cable and fiber optics, or unguided (wireless) using radio waves, microwaves and infrared.
GROUP03_AMAK:ERROR DETECTION AND CORRECTION PPT
This document discusses error detection and correction techniques. It introduces concepts like redundancy, forward error correction, retransmission, linear block coding, Hamming codes, and cyclic redundancy checks (CRC). Specific error correction codes covered include Hamming codes, which use modulo-2 arithmetic to add redundant bits to detect and correct single bit errors. CRC codes are also discussed, which use cyclic codes and polynomial representations to detect errors by computing a syndrome value. The document provides information on generating and detecting errors for different codes.
Error detection and correction
This document discusses error detection and correction in digital communication. It describes how coding schemes add redundancy to messages through techniques like block coding and convolution coding to detect or correct errors. The encoder adds redundant bits to original messages to create relationships between bits that the decoder can use to check for errors. It also explains the use of modular arithmetic, specifically modulo-2 arithmetic which uses only 1s and 0s, for error detection and correction operations.
Cyclic redundancy check
Cyclic Redundancy Codes (CRCs) provide a first line of defense against data corruption in many networks. Unfortunately, many commonly used CRC polynomials provide significantly less error detection capability than they might. An exhaustive exploration reveals that most previously published CRC polynomials are either inferior to alternatives or are only good choices for particular message lengths.
Error detection and correction
This document discusses various topics related to network transmission including:
- Different types of errors that can occur such as single-bit errors and burst errors.
- How error detection and correction works using redundant bits to detect if errors have occurred and in some cases correct the errors.
- Forward error correction versus retransmission for dealing with errors.
- Modular arithmetic and how it relates to error correction by using arithmetic operations on data and redundant bits.
Error detection and correction
Error coding uses mathematical formulas to encode data bits into longer code words for transmission. This allows errors caused by environmental interference to be detected and sometimes corrected at the destination. There are two main types of error coding: error-detecting codes and error-correcting codes. Error-detecting codes add enough redundancy to allow errors to be detected but not corrected, while error-correcting codes add more redundancy to allow errors to be corrected. Common error-detecting coding techniques include parity checks, checksums, and cyclic redundancy checks (CRCs). These techniques use additional redundant bits appended to the data to facilitate error detection. CRC is particularly powerful as it can detect all single-bit errors and many burst errors.
Lecture 22
The document discusses error correction techniques for data communication and networking. It describes two main error correction methods: error correction by retransmission, which has the receiver request retransmission of data if an error is detected; and forward error correction, which uses error-correcting codes to automatically correct certain errors. The document then focuses on Hamming codes, explaining how they use redundancy bits to detect and correct errors in binary data. Specific aspects of Hamming codes like bit arrangements and calculations are provided, along with an example of how they can correct burst errors.
Error detection and correction
This document discusses error detection and correction techniques used in data communication networks. It describes common types of transmission errors like single bit errors and burst errors. It then explains different error detection methods including parity checking, longitudinal redundancy checking (LRC), and checksum checking. It also covers error correction techniques like Go-Back-N and Selective Repeat that allow retransmission of only corrupted frames. Flow control mechanisms like stop-and-wait and sliding window protocols are also summarized.
Error detection in Data Communication System
This document discusses error detection techniques including cyclic redundancy checks (CRCs) and discusses the differences between bit rate errors and frame rate errors. It can be summarized as:
1. CRCs are a commonly used error detection technique where a check value is calculated based on the data and transmitted with it to allow the receiver to check for errors.
2. Bit rate error refers to the rate of errors in transmitted bits, while frame rate error refers to the ratio of data received with errors to the total data received.
3. A method is presented for estimating both bit error rate and frame error rate for low-density parity-check codes based on enumerating the smallest weight error patterns that cannot be corrected.
DCN Error Detection & Correction
This document provides an overview of error detection and correction techniques used in digital communication systems. It defines different types of errors like single bit errors and burst errors that can occur during signal transmission. It also describes various error detection methods like parity checking, checksum detection, and cyclic redundancy check (CRC). The document explains concepts of forward error correction (FEC), automatic repeat request (ARQ), and CRC checkers. It provides block diagrams of the basic ARQ system and its operations.
Error correction, ARQ, FEC
There are two basic approaches to error correction: automatic-repeat-request (ARQ) and forward error correction (FEC). ARQ requires retransmitting frames where errors are detected, while FEC allows the receiver to detect and correct a limited number of errors without contacting the transmitter by using error correction codes. Common ARQ techniques include stop-and-wait, go-back-n, and selective-repeat. FEC works by adding redundant bits that enable the receiver to determine the most likely intended message even if some bits are received in error.
Cyclic Redundancy Check in Computers Network
1) Cyclic redundancy check (CRC) is a method for detecting errors in digital data during transmission over unreliable communication channels. It works by using a generator polynomial to generate a checksum that is appended to the transmitted data.
2) At the sender, the data bits are divided by the generator polynomial to calculate a remainder which becomes the CRC checksum. This checksum is appended to the data before transmission.
3) At the receiver, the received data and checksum are divided again by the same generator polynomial. If the remainder is zero, then no errors were detected in the received data. A non-zero remainder indicates errors were detected.
Error Detection N Correction
The document discusses error detection and correction techniques. It introduces Hamming codes, which can detect up to two bit errors and correct one bit errors. It explains how Hamming codes work by adding redundant parity bits to messages based on the values of data bits. A 4x7 generator matrix is used to encode 4-bit data words into 7-bit codewords for the Hamming(7,4) code. An example shows how a data word of 1010 encodes to the codeword 1011010. The summary then tests a C++ implementation of Hamming code encoding.
Error control, parity check, check sum, vrc
The document discusses various methods for error detection in digital communication, including:
1. Parity checking, which adds an extra parity bit to ensure an even or odd number of 1s. Two-dimensional parity divides data into a grid and adds a redundant row.
2. Checksums, which divide data into sections, add the sections using one's complement arithmetic, complement the sum, and send it along with the data for verification.
3. Vertical redundancy checking adds a parity bit to each character to detect single-bit errors and some multiple-bit errors. It is often used with ASCII encoding.
Channel Coding (Error Control Coding)
power point presentation
By : Ola Mashaqi, Suhad Malayshe, Mais Masri
Annajah national University
Telecommunications Engineers
Lecture 21
This document provides an overview of CRC (Cyclic Redundancy Check) and checksum techniques for error detection in data transmission. It describes how CRC works by appending redundant bits to the data such that the resulting data is divisible by a predetermined binary number. It also explains how checksums are generated by dividing the data into sections, adding the sections using one's complement arithmetic, and sending the complement of the sum along with the data. The document compares the performance of CRC and checksums, noting that CRC can detect all odd-length burst errors while checksums are susceptible to some even-length errors.
What's hot (20)
Error correction error detection in digital communication
Error correction error detection in digital communication
Error detection and correction, flow and error control and trasmission media
Error detection and correction, flow and error control and trasmission media
Similar to Burst Error Correction
Paper id 312201514
This document summarizes forward error correction techniques using convolutional encoders and Viterbi decoders. It first provides background on communication channels and the need for error correction when transmitting data. It then describes convolutional coding, a technique that maps a continuous stream of input bits to a continuous stream of encoded output bits using shift registers, with the encoded bits depending on current and past input bits. The key aspects of convolutional encoders are discussed, including parameters like the number of output bits, input bits, and shift registers. Generator polynomials are also introduced as characterizing the encoder connections. Viterbi decoding is highlighted as a maximum likelihood algorithm for decoding the trellis structure of convolutional codes based on soft decisions.
Applications of information theory in communication engineering
This document provides an overview of information theory and its applications in communication engineering. It discusses key concepts such as source coding techniques like lossless and lossy data compression, algorithms like Huffman coding and arithmetic coding. It also covers channel coding techniques including error detection codes, forward error correction, block codes, convolutional codes, turbo codes and their applications in areas like digital television, DVDs, wireless communications. The document concludes that information theory provides fundamental limits for efficient digital communication and coding applications have improved reliability and efficiency of modern communication systems.
Iisrt jona priyaa(1 5)
The document discusses a study that implemented low density parity check (LDPC) decoding using a min sum algorithm with reduced complexity compared to existing methods. It used quadrature phase-shift keying (QPSK) modulation to improve bit error rate over previous approaches that used binary phase-shift keying (BPSK) modulation. The proposed method was able to achieve a lower bit error rate than other existing techniques using fewer iterations, improving performance flexibility by varying the code size. It implemented LDPC decoding on an irregular parity check matrix using a split row technique to reduce interconnect complexity and increase parallelism in the row processing stage compared to standard decoding algorithms.
www.ijerd.com
This document summarizes a research paper that proposes using parallel concatenated turbo codes in wireless sensor networks in an adaptive way. The key points are:
1) Turbo codes can achieve near-Shannon limit performance but decoding is complex, making them difficult to implement on energy-constrained sensor nodes.
2) The proposed approach shifts the complex turbo decoding to the base station while sensor nodes implement encoding and basic error correction.
3) At sensor nodes, a parallel concatenated convolutional code (PCCC) circuit encodes data and detects/corrects errors in forwarded packets. This improves energy efficiency and reliability over the wireless sensor network.
www.ijerd.com
International Journal of Engineering Research and Development is an international premier peer reviewed open access engineering and technology journal promoting the discovery, innovation, advancement and dissemination of basic and transitional knowledge in engineering, technology and related disciplines.
72
1. The document presents a simulation of a low power analog channel decoder for error correction implemented in 65nm CMOS technology.
2. The decoder uses analog circuitry operating in the sub-threshold region to perform decoding, allowing for ultra-low power operation below 40uW for throughput up to 2.5Mbps.
3. The decoder architecture includes an analog decoding core that implements the sum-product algorithm, digital interfaces for input and output, and a digital controller to manage timing.
Turbo codes
The document discusses turbo codes, a type of forward error correction code. Turbo codes use parallel concatenated convolutional encoders with pseudorandom interleaving and iterative decoding. This structure allows turbo codes to achieve error correction performance very close to the theoretical limit defined by the Shannon capacity. Some key advantages of turbo codes are their remarkable power efficiency and ability to support delivery of multimedia services through design tradeoffs. However, turbo codes also have long latency and poor performance at very low bit error rates.
Turbo encoder and decoder chip design and FPGA device analysis for communicat...
Turbo encoder and decoder chip design and FPGA device analysis for communicat...International Journal of Reconfigurable and Embedded Systems
Turbo codes are error-correcting codes with performance that is close to the
Shannon theoretical limit (SHA). The motivation for using turbo codes is
that the codes are an appealing mix of a random appearance on the channel
and a physically realizable decoding structure. The communication systems
have the problem of latency, fast switching, and reliable data transfer. The
objective of the research paper is to design and turbo encoder and decoder
hardware chip and analyze its performance. Two convolutional codes are
concatenated concurrently and detached by an interleaver or permuter in the
turbo encoder. The expected data from the channel is interpreted iteratively
using the two related decoders. The soft (probabilistic) data about an
individual bit of the decoded structure is passed in each cycle from one
elementary decoder to the next, and this information is updated regularly.
The performance of the chip is also verified using the maximum a posteriori
(MAP) method in the decoder chip. The performance of field-programmable
gate array (FPGA) hardware is evaluated using hardware and timing
parameters extracted from Xilinx ISE 14.7. The parallel concatenation offers
a better global rate for the same component code performance, and reduced
delay, low hardware complexity, and higher frequency support.
Introduction to Channel Coding & Decoding
Introduction to Channel Coding & Decoding which is a process used in Communication Systems mainly to improve the received data accuracy.
The Reliability in Decoding of Turbo Codes for Wireless Communications
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
Paper id 2720144
The document compares the performance of single stage and double stage interleavers in communication systems using turbo codes. A single stage interleaver uses one random interleaver between two convolutional encoders, while a double stage interleaver uses two interleavers in series. The document suggests that a double stage interleaver can improve the bit error rate (BER) of the system compared to a single stage interleaver by further scrambling the input bits. It also provides details on the components of a turbo code system such as convolutional encoders, interleavers, puncturing, and iterative decoding.
Error control coding techniques
This document provides an overview of error control coding techniques, specifically cyclic codes and low-density parity-check (LDPC) codes. It begins with an introduction to the need for error correcting codes and definitions of error detection and correction. It then discusses cyclic codes in more detail, covering encoding and decoding techniques like polynomial and shift register methods. LDPC codes are also explained, including their representation via Tanner graphs and decoding algorithms. The document presents examples and applications of both code types. It concludes by discussing areas for future research and summarizing that error codes can effectively protect against random and burst errors in real-time systems.
MC_CDMA
This document discusses a project that simulates and analyzes multi-carrier CDMA signals in an additive white Gaussian noise (AWGN) channel. The project generates Walsh codes from a Hadamard matrix to spread and code signals for code division multiple access. These coded signals are then modulated using an orthogonal frequency-division multiplexing (OFDM) system and transmitted through an AWGN channel. At the receiver, the bit error rate (BER) of the signals is calculated for varying numbers of users in the system. The results show that BER increases with the number of users and higher signal-to-noise ratio (SNR) values are needed to maintain a minimum BER as more users are added.
Sandberg v deetzen_trcomm_2010
This document discusses the design of low-density parity-check (LDPC) codes that provide unequal error protection (UEP) when used with higher order constellations (HOCs) like 8-PSK and 64-QAM. The proposed method divides the variable node degree distribution into sub-distributions corresponding to protection classes from the source coding and modulation classes of the HOC. An iterative linear programming approach is used to optimize the sub-distributions to enhance the UEP capability of the code for different signal-to-noise ratios, while reducing the overall bit error rate by accounting for the different bit error probabilities of the HOC. Simulation results show significant bit error rate reductions compared to codes optimized for binary phase-shift keying
Jb2415831591
The document summarizes a research paper that proposes a low density parity check (LDPC) algorithm for insertion/deletion channels. It begins by providing background on LDPC codes and how they are finding increasing use for reliable information transfer over bandwidth-constrained links with noise. It then describes the specific system model of a concatenated coding scheme using an outer error correcting code and inner marker code. The document analyzes the achievable transmission rates using this scheme through both bit-level and symbol-level maximum a posteriori probability (MAP) detection algorithms. It finds that the symbol-level approach confirms an advantage over codes optimized for additive white Gaussian noise channels.
A New Bit Split and Interleaved Channel Coding for MIMO Decoder
Authors:-C. Amar Singh Feroz1, S. Karthikeyan2, K. Mala3
Abstract– In wireless communications, the use of multiple antennas at both the
transmitter and receiver is a key technology to enable high data transmission without
additional bandwidth or transmit power. MIMO schemes are widely used in many
wireless standards, allowing higher throughput using spatial multiplexing techniques.
Bit split mapping based on JDD is designed. Here ETI coding is used for encoding and
Viterbi is used for decoding. Experimental results for 16-QAM and 64 QAM with the
code rate of ½ and 1/3 codes are shown to verify the proposed approach and to elucidate
the design tradeoffs in terms the BER performance. This bit split mapping based JDD
algorithm can greatly improve BER performance with different system settings.
Y25124127
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
FPGA Implementation of LDPC Encoder for Terrestrial Television
The increasing data rates in digital television networks increase the demands on data capacity of the current transmission channels. Through new standards, the capacity of existing channels is increased with new methods of error correction coding and modulation. In this work, Low Density Parity Check (LDPC) codes are implemented for their error correcting capability. LDPC is a linear error correcting code. These linear error correcting codes are used for transmitting a message over a noisy transmission channel. LDPC codes are finding increasing use in applications requiring reliable and highly efficient information transfer over noisy channels. These codes are capable of performing near to Shannon limit performance and have low decoding complexity. LDPC uses parity check matrix for its encoding and decoding purpose. The main advantage of the parity check matrix is that it helps in detecting and correcting errors which is a very important advantage against noisy channels. This work presents the design and implementation of a LDPC encoder for transmission of digital terrestrial television according to the Chinese DTMB standard. The system is written in Verilog and is implemented on FPGA. The whole work is then verified with the help of Matlab modelling.
Chaos Encryption and Coding for Image Transmission over Noisy Channels
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
H017653645
This document proposes a combined ciphering and coding scheme for image transmission over noisy wireless channels. The ciphering scheme is based on a modified chaotic Logistic map to provide security. Low Density Parity Check (LDPC) coding is used as the error correction technique to improve reliability over noisy channels. Simulation results show that LDPC coding outperforms turbo coding for this application in terms of bit error rate. The combined ciphering and coding scheme is analyzed and shown to enhance performance metrics like peak signal-to-noise ratio and bit error rate, achieving both security and reliability for image transmission over wireless channels.
Similar to Burst Error Correction (20)
Applications of information theory in communication engineering
Applications of information theory in communication engineering
Turbo encoder and decoder chip design and FPGA device analysis for communicat...
Turbo encoder and decoder chip design and FPGA device analysis for communicat...
The Reliability in Decoding of Turbo Codes for Wireless Communications
The Reliability in Decoding of Turbo Codes for Wireless Communications
A New Bit Split and Interleaved Channel Coding for MIMO Decoder
A New Bit Split and Interleaved Channel Coding for MIMO Decoder
FPGA Implementation of LDPC Encoder for Terrestrial Television
FPGA Implementation of LDPC Encoder for Terrestrial Television
Chaos Encryption and Coding for Image Transmission over Noisy Channels
Chaos Encryption and Coding for Image Transmission over Noisy Channels
Burst Error Correction
- 1. Burst Error Correction In RS Codes Aditi Singal, Santosh Nagaraj Electrical and Computer Engineering , San Diego State University Introduction • In communication systems the noise present in the channel are generally assumed to be Additive White Gaussian Noise, which has a Gaussian distribution. In real, the channel noise is not always AWGN. Instead, the distribution of error is more complex and the error rate varies over a range of time. Error correcting codes improve the functioning and consistency of modern digital communication system. • Different FEC coding methods are used in the digital communication systems. They are mainly classified into block and convolutional codes [1-2]. • The aim of this project is to design a code that is efficient and suitable to implement in wireless transmission systems • The technique of interleaving a code is used to detect and correct the burst error. Project approach • The general idea behind using interleaving is to spread the long burst of error into random error. • The simple interleaving can be achieved by using the degree of interleaving denoted by λ , where λ -1 should be the multiple of n. • Interleaving is done by entering the data row wise in an interleaver and taking a column wise output at the deinterleaver. Figure 1 A block interleaving system Results • Increasing the length of message bit for each block was tested. • Interleaving is the best way to combat burst errors because Encoder and decoder uses shift registers Decoder of interleaved code can be derived from the d decoder of original code • BER becomes better for the interleaving degree of 35 when the length is 400. The code can correct more burst errors when the length and degree of interleaving is increased at the same time • Coding techniques with higher error detection and correction capability will use more redundant bits and bandwidth. This reduces information transmission rates and will increase the delay for encoding and decoding at source and destination. Thus, on the design of higher error correcting codes the factor affecting the transmission rate should be wisely considered. Figure 2 BER performance of interleaved RS codes Discussions • When the MATLAB code was implemeted for the project, it was observed that the length of the code should be proportional to the interleaving degree of the system • If the error correcting capability of the code is greater than the length of the codeword input, then the burst error cannot be corrected by the interleaver.. • Burst Error correction capability depends on the length of the code as well as the interleaving degree of the system. • At the deinterleaver, the original data is obtained with the burst error converted to random errors and spread thruoghout the codeword length. Concluding Remarks • From the project, it is deduced that interleaving reduces the burst error in transmitted data by a huge percentage. • BER becomes better when the interleaving degree and code length are increased simultaneously. Reference 1. https://espace.cdu.edu.au/eserv/cdu:38795/Thesis_CDU_38 795_Rupakheti_S.pdf 2. Error Control Coding: Fundamentals and Applications (2nd Edition) Textbook by Shu Lin, Daniel J. Costello