scholarly journals Reduced Complexity Iterative Decoding of 3D-Product Block Codes Based on Genetic Algorithms

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Abdeslam Ahmadi ◽  
Faissal El Bouanani ◽  
Hussain Ben-Azza ◽  
Youssef Benghabrit
Keyword(s):  
Genetic Algorithms ◽  
Iterative Decoding ◽  
Block Codes ◽  
Shannon Capacity ◽  
Large Parameter ◽  
Decoding Algorithms ◽  
Capacity Limit ◽  
Large Correction ◽  
Reduced Complexity ◽  
Simulation Results

Two iterative decoding algorithms of 3D-product block codes (3D-PBC) based on genetic algorithms (GAs) are presented. The first algorithm uses the Chase-PyndiahSISO, and the second one uses the list-basedSISOdecoding algorithm (LBDA) based on order- reprocessing. We applied these algorithms overAWGNchannel to symmetric3D-PBCconstructed fromBCHcodes. The simulation results show that the first algorithm outperforms the Chase-Pyndiah one and is only 1.38 dB away from the Shannon capacity limit at BER of forBCH(31, 21, 5)3and 1.4 dB forBCH(16, 11, 4)3. The simulations of the LBDA-basedGAon theBCH(16, 11, 4)3show that its performances outperform the first algorithm and is about 1.33 dB from the Shannon limit. Furthermore, these algorithms can be applied to any arbitrary 3D binary product block codes, without the need of a hard-in hard-out decoder. We show also that the two proposed decoders are less complex than both Chase-Pyndiah algorithm for codes with large correction capacity and LBDA for large parameter. Those features make the decoders based on genetic algorithms efficient and attractive.

New iterative decoding algorithms of 2D product block codes

2014 ◽  
Author(s):  
Abdeslam Ahmadi ◽  
Hussain Ben-Azza ◽  
Faissal El Bouanani
Keyword(s):  
Iterative Decoding ◽  
Block Codes ◽  
Decoding Algorithms

Lossy Source Compression Using Belief Propagation with Decimation over Multi-Edge Type Factor Graphs of LDGM Codes

2014 ◽  
Vol 610 ◽  
pp. 437-442
Author(s):  
Wu Guan ◽  
Li Ping Liang
Keyword(s):  
Belief Propagation ◽  
Low Complexity ◽  
Shannon Capacity ◽  
Generator Matrix ◽  
Edge Type ◽  
Belief Propagation Algorithm ◽  
Reduced Complexity ◽  
Simulation Results ◽  
Type Factor ◽  
Capacity Performance

A low complexity approach for binary quantization is proposed. This approach uses a multi-edge type bipartite graph of the low density generator matrix (LDGM) code with the belief propagation algorithm to encode the informations. A damping decimation is developed for the algorithm convergence. Simulation results show that our algorithm achieves near Shannon capacity performance with reduced complexity.

scholarly journals Performances of BICM-ID system using CRSC code in optical transmissions

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Hocine Fekih ◽  
Boubakar Seddik Bouazza ◽  
Keltoum Nouri
Keyword(s):  
Bit Error Rate ◽  
Error Rate ◽  
Iterative Decoding ◽  
Optical Transmission ◽  
Coded Modulation ◽  
Modulation Scheme ◽  
Coding Gain ◽  
Decoding Algorithms ◽  
Qam Modulation ◽  
Short Code

AbstractRecently, using iterative decoding algorithms to achieve an interesting bit error rate for spectrally efficient modulation become a necessity for optical transmission, in this paper, we propose a coded modulation scheme based on bit interleaving circular recursive systematic convolutional (CRSC) code and 16-QAM modulation. The proposal system considered as a serial concatenation of a channel encoder, a bit interleaver and M-ary modulator can be flexible easy to implement using a short code length. For a spectral efficiency $\eta =3\text{bit}/s/Hz$, the coding gain at a bit error rate of 10−6 is about 8 dB.

Some Analog Filters of Reduced Complexity with Shelving and Multifunctional Characteristics

2018 ◽  
Vol 27 (10) ◽  
pp. 1850150 ◽  
Author(s):  
Sudhanshu Maheshwari
Keyword(s):  
Power Supply ◽  
Active Element ◽  
Current Conveyor ◽  
Analog Filters ◽  
First Order ◽  
Voltage Mode ◽  
Experimental Support ◽  
Reduced Complexity ◽  
Simulation Results ◽  
The One

This paper presents first-order voltage-mode filters using a single current conveyor with an additional X-stage, and passive elements. The new circuits have multifunction capability, and also realize low-shelf, high-shelf and band-shelf functions. The study is carried out on the effects of non-idealities, parasitic elements, and loading on the performance of proposed circuits. Active and passive sensitivities are also analyzed. The active element, extra-X current conveyor used for designing new circuits is simpler than most of the one active element and two passive elements’ based circuits. Detailed comparisons are carried out with relevant available works, and the new circuits are found to be more compact and exhibit higher frequency performances. The simulation results using 0.25[Formula: see text][Formula: see text]m CMOS parameters with [Formula: see text]1.25[Formula: see text]V power-supply are shown to verify the proposed circuits. The proposed circuits are also verified through simulations. Experimental support is given using AD-844 ICs to strengthen the validity of the proposed circuits.

scholarly journals Detection of Attacks on Wireless Sensor Network Using Genetic Algorithms Based on Fuzzy

2019 ◽  
Vol 8 (1) ◽  
pp. 57 ◽  
Author(s):  
Shaymaa Al Hayali ◽  
Osman Ucan ◽  
Javad Rahebi ◽  
Oguz Bayat
Keyword(s):  
Genetic Algorithms ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Development ◽  
Wireless Sensor ◽  
Optimal Routing ◽  
Fuzzy Function ◽  
Renewable Energy Development ◽  
Multi Agent ◽  
Simulation Results

In this paper an individual - suitable function calculating design for WSNs is conferred. A multi-agent- located construction for WSNs is planned and an analytical type of the active combination is built for the function appropriation difficulty. The purpose of this study is to identify the threats identified by clustering genetic algorithms in clustering networks, which will prolong network lifetime. In addition, optimal routing is done using the fuzzy function. Simulation results show that the simulated genetic algorithm improves diagnostic speed and improves energy consumption.©2019. CBIORE-IJRED. All rights reservedArticle History: Received May 16th 2018; Received in revised form Octiber 6th 2018; Accepted Jnauary 6th 2019; Available onlineHow to Cite This Article: Al-Hayali, S., Ucan, O., Rahebi, J. and Bayat, O. (2019) Detection of Attacks on Wireless Sensor Network Using Genetic Algorithms Based on Fuzzy. International Journal of Renewable Energy Development, 8(1), 57-64.https://doi.org/10.14710/ijred.8.1.57-64

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