scholarly journals Analisis Kinerja FBMC OQAM menggunakan Kode Konvolusi

2021 ◽  
Vol 9 (4) ◽  
pp. 775
Author(s):  
MIFTAKHUDIN YUSUF ◽  
ANGGUN FITRIAN ISNAWATI ◽  
SOLICHAH LARASATI
Keyword(s):  
Channel Capacity ◽  
Channel Coding ◽  
Viterbi Algorithm ◽  
Convolutional Code ◽  
Bit Rate ◽  
Digital Modulation ◽  
Data Rates ◽  
Better Than

ABSTRAKSistem FBMC merupakan teknologi MCM yang dapat menyediakan laju data bit yang tinggi. Modulasi digital OQAM digunakan untuk meningkatkan bit rate. Pengkodean kanal digunakan untuk mengoreksi kesalahan yang diakibatkan noise. Penilitian ini menggunakan pengkodean kanal kode konvolusi yang digunakan pada bagian pengirim dan algortima viterbi pada bagian penerima. Simulasi dilakukan pada FBMC OQAM dengan kode konvolusi dan tanpa kode konvolusi dengan perbandingan parameter BER dan kapasitas kanal terhadap SNR. Hasil penelitian menunjukan FBMC OQAM dengan kode konvolusi lebih baik daripada FBMC OQAM tanpa kode konvolusi pada SNR tinggi. Pada FBMC OQAM untuk mencapai BER 10-3 membutuhkan SNR 17 dB sedangkan pada FBMC OQAM dengan kode konvolusi membutuhkan SNR 16 dB. Peningkatan SNR dapat meningkatkan kapasitas kanal yang dihasilkan, pada SNR 0 dB menghasilkan 0,4535 bps/Hz dan SNR 20 dB menghasilkan 5,858 bps/Hz.Kata kunci: kode konvolusi, algoritma viterbi, FBMC, OQAM, BER ABSTRACTThe FBMC system is an MCM technology that can provide high bit data rates. OQAM digital modulation is used to increase the bit rate. Channel coding is used to correct errors caused by noise. This research uses convolutional code channel coding used on the sender and viterbi algorithms on the receiver. Simulations are carried out on FBMC OQAM with convolutional code and without convolutional code with a comparison of BER parameters and channel capacity to SNR. The results showed that FBMC OQAM with convolutional code was better than FBMC OQAM without convolutional code at high SNR. In FBMC OQAM to reach BER 10-3 requires SNR of 17 dB while in FBMC OQAM with convolutional code requires SNR of 16 dB. Increasing SNR can increase the resulting channel capacity, at 0 dB SNR it produces 0.4535 bps / Hz and SNR 20 dB produces 5.858 bps / Hz.Keywords: convolutional code, viterbi algorithm, FBMC, OQAM, BER

scholarly journals Fast but Not Furious. When Sped Up Bit Rate of Information Drives Rule Induction

2021 ◽  
Vol 12 ◽  
Author(s):  
Silvia Radulescu ◽  
Areti Kotsolakou ◽  
Frank Wijnen ◽  
Sergey Avrutin ◽  
Ileana Grama
Keyword(s):  
Information Transmission ◽  
Channel Capacity ◽  
Channel Coding ◽  
Coding Theory ◽  
Accuracy Assessment ◽  
Assessment Method ◽  
Rule Induction ◽  
Theoretic Model ◽  
Bit Rate ◽  
Cognitive Limitations

The language abilities of young and adult learners range from memorizing specific items to finding statistical regularities between them (item-bound generalization) and generalizing rules to novel instances (category-based generalization). Both external factors, such as input variability, and internal factors, such as cognitive limitations, have been shown to drive these abilities. However, the exact dynamics between these factors and circumstances under which rule induction emerges remain largely underspecified. Here, we extend our information-theoretic model (Radulescu et al., 2019), based on Shannon’s noisy-channel coding theory, which adds into the “formula” for rule induction the crucial dimension of time: the rate of encoding information by a time-sensitive mechanism. The goal of this study is to test the channel capacity-based hypothesis of our model: if the input entropy per second is higher than the maximum rate of information transmission (bits/second), which is determined by the channel capacity, the encoding method moves gradually from item-bound generalization to a more efficient category-based generalization, so as to avoid exceeding the channel capacity. We ran two artificial grammar experiments with adults, in which we sped up the bit rate of information transmission, crucially not by an arbitrary amount but by a factor calculated using the channel capacity formula on previous data. We found that increased bit rate of information transmission in a repetition-based XXY grammar drove the tendency of learners toward category-based generalization, as predicted by our model. Conversely, we found that increased bit rate of information transmission in complex non-adjacent dependency aXb grammar impeded the item-bound generalization of the specific a_b frames, and led to poorer learning, at least judging by our accuracy assessment method. This finding could show that, since increasing the bit rate of information precipitates a change from item-bound to category-based generalization, it impedes the item-bound generalization of the specific a_b frames, and that it facilitates category-based generalization both for the intervening Xs and possibly for a/b categories. Thus, sped up bit rate does not mean that an unrestrainedly increasing bit rate drives rule induction in any context, or grammar. Rather, it is the specific dynamics between the input entropy and the maximum rate of information transmission.

scholarly journals An Implementation of Error Minimization Data Transmission in OFDM using Modified Convolutional Code

2016 ◽  
Vol 3 (2) ◽  
Author(s):  
Hendy Briantoro ◽  
I Gede Puja Astawa ◽  
Amang Sudarsono
Keyword(s):  
Data Transmission ◽  
Channel Coding ◽  
Convolutional Code ◽  
Software Radio ◽  
Code Rate ◽  
Bch Code ◽  
Error Minimization ◽  
Ofdm System ◽  
Software Define Radio ◽  
Better Than

This paper presents about error minimization in OFDM system. In conventional system, usually using channel coding such as BCH Code or Convolutional Code. But, performance BCH Code or Convolutional Code is not good in implementation of OFDM System. Error bits of OFDM system without channel coding is 5.77%. Then, we used convolutional code with code rate 1/2, it can reduce error bitsonly up to 3.85%. So, we proposed OFDM system with Modified Convolutional Code. In this implementation, we used Software Define Radio (SDR), namely Universal Software Radio Peripheral (USRP) NI 2920 as the transmitter and receiver. The result of OFDM system using Modified Convolutional Code with code rate is able recover all character received so can decrease until 0% error bit. Increasing performance of Modified Convolutional Code is about 1 dB in BER of 10-4 from BCH Code and Convolutional Code. So, performance of Modified Convolutional better than BCH Code or Convolutional Code.Keywords: OFDM, BCH Code, Convolutional Code, Modified Convolutional Code, SDR, USRP

scholarly journals The Application of Baum-Welch Algorithm in Multistep Attack

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Yanxue Zhang ◽  
Dongmei Zhao ◽  
Jinxing Liu
Keyword(s):  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov Models ◽  
Viterbi Algorithm ◽  
Markov Models ◽  
Hidden Markov ◽  
Simulation Experiments ◽  
Forward Algorithm ◽  
Better Than

The biggest difficulty of hidden Markov model applied to multistep attack is the determination of observations. Now the research of the determination of observations is still lacking, and it shows a certain degree of subjectivity. In this regard, we integrate the attack intentions and hidden Markov model (HMM) and support a method to forecasting multistep attack based on hidden Markov model. Firstly, we train the existing hidden Markov model(s) by the Baum-Welch algorithm of HMM. Then we recognize the alert belonging to attack scenarios with the Forward algorithm of HMM. Finally, we forecast the next possible attack sequence with the Viterbi algorithm of HMM. The results of simulation experiments show that the hidden Markov models which have been trained are better than the untrained in recognition and prediction.

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 Channel coding: The road to channel capacity

2007 ◽  
Vol 95 (6) ◽  
pp. 1150-1177 ◽  
Author(s):  
Daniel J. Costello ◽  
G. David Forney
Keyword(s):  
Channel Capacity ◽  
Channel Coding ◽  
The Road
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