scholarly journals A Form of List Viterbi Algorithm for Decoding Convolutional Codes

2018 ◽  
Vol 4 (2) ◽  
pp. 42-48
Author(s):  
Shamsuddeen Hassan Muhammad ◽  
Abdulrasheed Mustapha
Keyword(s):  
Communication Systems ◽  
Viterbi Algorithm ◽  
Convolutional Code ◽  
Convolutional Codes ◽  
Wireless Communication Systems ◽  
Voice Over Internet Protocol ◽  
Viterbi Decoding ◽  
Maximum Likelihood Decoding ◽  
Error Performance ◽  
List Viterbi Algorithm

Viterbi algorithm is a maximum likelihood decoding algorithm. It is used to decode convolutional code in several wireless communication systems, including Wi-Fi. The standard Viterbi algorithm gives just one decoded output, which may be correct or incorrect. Incorrect packets are normally discarded thereby necessitating retransmission and hence resulting in considerable energy loss and delay. Some real-time applications such as Voice over Internet Protocol (VoIP) telephony do not tolerate excessive delay. This makes the conventional Viterbi decoding strategy sub-optimal. In this regard, a modified approach, which involves a form of List Viterbi for decoding the convolutional code is investigated. The technique employed combines the bit-error correction capabilities of both the Viterbi algorithm and the Cyclic Redundancy Check (CRC) procedures. It first uses a form of ‘List Viterbi Algorithm’ (LVA), which generates a list of possible decoded output candidates after the trellis search. The CRC check is then used to determine the presence of correct outcome. Results of experiments conducted using simulation shows considerable improvement in bit-error performance when compared to classical approach.

The Viterbi Decoding Scheme for FPGA

2011 ◽  
Vol 63-64 ◽  
pp. 835-840
Author(s):  
Ke Han ◽  
Zhong Liang Deng ◽  
Lian Ming Xu
Keyword(s):  
Power Consumption ◽  
Mobile Communication ◽  
Communication System ◽  
Viterbi Algorithm ◽  
Convolutional Code ◽  
Fpga Implementation ◽  
Viterbi Decoding ◽  
Mobile Communication System ◽  
Uniform State ◽  
Branch Weight

This paper analyzes the principle of Viterbi algorithm which can be used in the norm of the mobile communication system. Then a new Viterbi decoding scheme of (2, 1, 7) convolutional code is presented for FPGA implementation. To take advantage of the FPGA, a new branch weight algorithm and uniform state weight memories is used. At last, a new decoding circuit which can work on 35MHz and can achieve 120 kbs in decoding speed was designed. To use the design of survival path exchange register module, it can decrease the power consumption and the RAM size.

scholarly journals Iterative Decoding of Turbo Codes

2018 ◽  
Vol 3 ◽  
pp. 15
Author(s):  
Dhaneshwar Sah
Keyword(s):  
Turbo Codes ◽  
Coding Theory ◽  
Iterative Decoding ◽  
Communication Systems ◽  
Error Control ◽  
Viterbi Algorithm ◽  
Convolutional Codes ◽  
Soft Information ◽  
Space Communications ◽  
College Of Engineering

<p><strong> </strong>This paper presents a Thesis which consists of a study of turbo codes as an error-control Code and the software implementation of two different decoders, namely the Maximum a Posteriori (MAP), and soft- Output Viterbi Algorithm (SOVA) decoders. Turbo codes were introduced in 1993 by berrouet at [2] and are perhaps the most exciting and potentially important development in coding theory in recent years. They achieve near- Shannon-Limit error correction performance with relatively simple component codes and large interleavers. They can be constructed by concatenating at least two component codes in a parallel fashion, separated by an interleaver. The convolutional codes can achieve very good results. In order of a concatenated scheme such as a turbo codes to work properly, the decoding algorithm must affect an exchange of soft information between component decoders. The concept behind turbo decoding is to pass soft information from the output of one decoder to the input of the succeeding one, and to iterate this process several times to produce better decisions. Turbo codes are still in the process of standardization but future applications will include mobile communication systems, deep space communications, telemetry and multimedia. Finally, we will compare these two algorithms which have less complexity and which can produce better performance.</p><p><strong>Journal of Advanced College of Engineering and Management</strong>, Vol.3, 2017, Page: 15-30</p>

scholarly journals Mathematical Approach and Implementation of Frequency Mapping Techniques in Power-Line Communications Channel

2019 ◽  
Vol 10 (1) ◽  
pp. 88-108
Author(s):  
Tedy Lukusa ◽  
Khmaies Ouahada ◽  
Hendrik C. Ferreira
Keyword(s):  
Error Correcting Code ◽  
Convolutional Codes ◽  
Power Line ◽  
Modulation Scheme ◽  
Mathematical Approach ◽  
Viterbi Decoder ◽  
Viterbi Decoding ◽  
Maximum Likelihood Decoding ◽  
Power Line Communications ◽  
Mapping Techniques

Abstract Power-line channel is considered to be a very hostile channel compared to other channels in view of the different types of noise that could exist. Therefore, the choice of the error correcting code and the modulation scheme can play a big role in combating the noise in such a channel. M -FSK modulation has shown its robustness for such a type of channel. Two frequency mappings techniques are presented in this paper. In the first technique, M orthogonal frequencies are arranged in sequences based on the value and the position of permutation symbols, while in the second technique, the frequencies are rearranged based on the sign changes of the Walsh-Hadamard transform (WHT). The obtained M-FSK modulation is combined to codes based on Viterbi decoding algorithms since Viterbi decoder is considered to be the maximum-likelihood decoding algorithm for convolutional codes and codes with state machine representation. A mathematical approach and implementation of frequency mappings is introduced to investigate the performance of the new designed communication system in the presence of permanent frequency disturbances, also known as narrow-band interference (NBI), such as those encountered in power line communications (PLC) channel.

scholarly journals List Viterbi Decoding of PAC Codes

2020 ◽  
Author(s):  
Mohammad Rowshan ◽  
Emanuele Viterbo
Keyword(s):  
Error Correction ◽  
Viterbi Algorithm ◽  
Hamming Distance ◽  
Poor Performance ◽  
Superior Performance ◽  
List Decoding ◽  
Viterbi Decoding ◽  
Vector Channel ◽  
Constraint Length ◽  
List Viterbi Algorithm

<div>Polarization-adjusted convolutional (PAC) codes are special concatenated codes in which we employ a one-to-one convolutional transform as a pre-coding step before the polar transform. In this scheme, the polar transform (as a mapper) and the successive cancellation process (as a demapper) present a synthetic vector channel to the convolutional transformation. The numerical results show that this concatenation improves the Hamming distance properties of polar codes. </div><div>In this work, we implement the parallel list Viterbi algorithm (LVA) and show how the error correction performance moves from the poor performance of the Viterbi algorithm (VA) to the superior performance of list decoding by changing the constraint length, list size, and the sorting strategy (local sorting and global sorting) in the LVA. Also, we analyze the latency of the local sorting of the paths in LVA relative to the global sorting in the list decoding and the trade-off between the sorting latency and the error correction performance.</div>

scholarly journals Turbo codes and turbo algorithms

2017 ◽  
Vol 2 (3) ◽  
pp. 179
Author(s):  
Claude Berrou ◽  
Charlotte Langlais ◽  
Yi Yu
Keyword(s):  
Turbo Codes ◽  
Iterative Decoding ◽  
Communication Systems ◽  
Evaluation Method ◽  
Multiple Input Multiple Output ◽  
Convolutional Codes ◽  
Error Performance ◽  
Iterative Processing ◽  
Input Multiple Output ◽  
Basic Ideas

In the first part of this paper, several basic ideas that prompted the coming of turbo codes are commented on. We then present some personal points of view on the main advances obtained in past years on turbo coding and decoding such as the circular trellis termination of recursive systematic convolutional codes and double-binary turbo codes associated with Max-Log-MAP decoding. A novel evaluation method, called genieinitialised iterative processing (GIIP), is introduced to assess the error performance of iterative processing. We show that using GIIP produces a result that can be viewed as a lower bound of the maximum likelihood iterative decoding and detection performance. Finally, two wireless communication systems are presented to illustrate recent applications of the turbo principle, the first one being multiple-input/multiple-output channel iterative detection and the second one multi-carrier modulation with linear precoding.

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