Iterative decoding of GMSK modulated convolutional code with multiple differential detection

2000 ◽  
Vol 36 (3) ◽  
pp. 258 ◽  
Author(s):  
Guan-Feng Qin ◽  
Shi-Dong Zhou ◽  
Li-Min Xiao ◽  
Yan Yao
Keyword(s):  
Iterative Decoding ◽  
Convolutional Code ◽  
Differential Detection

scholarly journals A General Rate K/N Convolutional Decoder Based on Neural Networks with Stopping Criterion

2009 ◽  
Vol 2009 ◽  
pp. 1-11 ◽  
Author(s):  
Johnny W. H. Kao ◽  
Stevan M. Berber ◽  
Abbas Bigdeli
Keyword(s):  
Neural Network ◽  
Bit Error Rate ◽  
Error Rate ◽  
Iterative Decoding ◽  
Viterbi Algorithm ◽  
Convolutional Code ◽  
Rate Transmission ◽  
Neural Network Structure ◽  
Data Rate Transmission ◽  
Novel Algorithm

A novel algorithm for decoding a general rate K/N convolutional code based on recurrent neural network (RNN) is described and analysed. The algorithm is introduced by outlining the mathematical models of the encoder and decoder. A number of strategies for optimising the iterative decoding process are proposed, and a simulator was also designed in order to compare the Bit Error Rate (BER) performance of the RNN decoder with the conventional decoder that is based on Viterbi Algorithm (VA). The simulation results show that this novel algorithm can achieve the same bit error rate and has a lower decoding complexity. Most importantly this algorithm allows parallel signal processing, which increases the decoding speed and accommodates higher data rate transmission. These characteristics are inherited from a neural network structure of the decoder and the iterative nature of the algorithm, that outperform the conventional VA algorithm.

Iterative decoding of GMSK modulated convolutional code

1999 ◽  
Vol 35 (10) ◽  
pp. 810 ◽  
Author(s):  
Guan-Feng Qin ◽  
Shi-Dong Zhou ◽  
Yan Yao
Keyword(s):  
Iterative Decoding ◽  
Convolutional Code

Chase-Like Decoding of Arithmetic Codes with Applications

2013 ◽  
pp. 27-41
Author(s):  
Amin Zribi ◽  
Sonia Zaibi ◽  
Ramesh Pyndiah ◽  
Ammar Bouallègue
Keyword(s):  
Image Compression ◽  
Gaussian Noise ◽  
Iterative Decoding ◽  
Convolutional Code ◽  
Additive White Gaussian Noise ◽  
Error Rates ◽  
Sequence Estimation ◽  
Awgn Channel ◽  
Arithmetic Codes ◽  
Classical Arithmetic

Motivated by recent results in Joint Source/Channel (JSC) coding and decoding, this paper addresses the problem of soft input decoding of Arithmetic Codes (AC). A new length-constrained scheme for JSC decoding of these codes is proposed based on the Maximum a posteriori (MAP) sequence estimation criterion. The new decoder, called Chase-like arithmetic decoder is supposed to know the source symbol sequence and the compressed bit-stream lengths. First, Packet Error Rates (PER) in the case of transmission on an Additive White Gaussian Noise (AWGN) channel are investigated. Compared to classical arithmetic decoding, the Chase-like decoder shows significant improvements. Results are provided for Chase-like decoding for image compression and transmission on an AWGN channel. Both lossy and lossless image compression schemes were studied. As a final application, the serial concatenation of an AC with a convolutional code was considered. Iterative decoding, performed between the two decoders showed substantial performance improvement through iterations.

Chase-Like Decoding of Arithmetic Codes with Applications

2011 ◽  
Vol 1 (1) ◽  
pp. 27-40
Author(s):  
Amin Zribi ◽  
Sonia Zaibi ◽  
Ramesh Pyndiah ◽  
Ammar Bouallègue
Keyword(s):  
Image Compression ◽  
Iterative Decoding ◽  
Convolutional Code ◽  
Additive White Gaussian Noise ◽  
Error Rates ◽  
Symbol Sequence ◽  
Sequence Estimation ◽  
Awgn Channel ◽  
Arithmetic Codes ◽  
Classical Arithmetic

Motivated by recent results in Joint Source/ Channel (JSC) coding and decoding, this paper addresses the problem of soft input decoding of Arithmetic Codes (AC). A new length-constrained scheme for JSC decoding of these codes is proposed based on the Maximum a posteriori (MAP) sequence estimation criterion. The new decoder, called Chase-like arithmetic decoder is supposed to know the source symbol sequence and the compressed bit-stream lengths. First, Packet Error Rates (PER) in the case of transmission on an Additive White Gaussian Noise (AWGN) channel are investigated. Compared to classical arithmetic decoding, the Chase-like decoder shows significant improvements. Results are provided for Chase-like decoding for image compression and transmission on an AWGN channel. Both lossy and lossless image compression schemes were studied. As a final application, the serial concatenation of an AC with a convolutional code was considered. Iterative decoding, performed between the two decoders showed substantial performance improvement through iterations.

scholarly journals HybridConcatenated Coding Scheme for MIMO Systems

2015 ◽  
Vol 5 (3) ◽  
pp. 464
Author(s):  
Ilesanmi Banjo Oluwafemi
Keyword(s):  
Fading Channels ◽  
Iterative Decoding ◽  
Mimo Systems ◽  
Convolutional Code ◽  
Convolutional Codes ◽  
Space Time ◽  
Trellis Codes ◽  
Orthogonal Space ◽  
Serially Concatenated ◽  
Better Than

<!--?xml:namespace prefix = "o" ns = "urn:schemas-microsoft-com:office:office" /-->Abstract: Inthis paper, two hybrid concatenated super-orthogonal space-time trellis codes(SOSTTC) applying iterative decoding are proposed for flat fading channels. Theencoding operation is based on the concatenation of convolutional codes,interleaving and super-orthogonal space-time trellis codes. The firstconcatenated scheme consists of a serial concatenation of a parallelconcatenated convolutional code with a SOSTTC while the second consists ofparallel concatenation of two serially concatenated convolutional and SOSTTCcodes. The decoding of these two schemes is described, their pairwise errorprobabilities are derived and the frame error rate (FER) performances areevaluated by computer simulation in Rayleigh fading channels. The proposedtopologies are shown to perform better than existing concatenated schemes with aconstituent code of convolutional andspace-time codes in literature.

Differential Detection of Single-Chain and Two-Chain Urokinase-Type Plasminogen Activator by a New Immunoadsorbent-Amidolytic Assay (IAA)

1986 ◽  
Vol 56 (03) ◽  
pp. 407-410 ◽  
Author(s):  
Angelo Corti ◽  
Maria Luisa Nolli ◽  
Giovanni Cassani
Keyword(s):  
Plasminogen Activator ◽  
Carcinoma Cell ◽  
Differential Detection ◽  
Single Chain ◽  
Response Curves ◽  
Type Plasminogen Activator ◽  
Urokinase Type Plasminogen Activator ◽  
Before And After ◽  
Culture Supernatants ◽  
Human Epidermoid Carcinoma

SummaryA new immunoadsorbent-amidolytic assay (IAA) for the specific differential detection of two-chain urokinase-type plasminogen activator (tcu-PA) and its single-chain precursor (scu-PA) in cell culture supernatants has been developed. The assay combines the selectivity of immunoassays with the specificity of enzyme activity assays exploiting both the antigenic and enzymatic properties of the two proteins. tcu-PA and scu-PA are selectively immunoadsorbed on the wells of a microtiterplate coated with the monoclonal antibody 5B4 and tested for enzymatic activity before and after activation by plasmin treatment. Both proteins are determined with similar efficiency since overlapping dose-response curves were obtained in the range between 12.5-200 ng/ml. The assay has been used to determine tcu-PA and scu-PA in A431 human epidermoid carcinoma cell supernatants. The analytical recoveries for tcu-PA and scu-PA added to A431 cell supernatants were 95.2% and 96.9% respectively. The intra- and inter-assay variations (CV) were 5.5% and 9.0% for tcu-PA and 9.7% and 9.8% for scu-PA respectively.

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