Sequence estimation scheme using Viterbi algorithm for improving bit error rate of binary continuous phase FSK with limiter discriminator and integrate and dump filter detection

2003 ◽  
Author(s):  
Y. Iwanami ◽  
T. Ikeda
Keyword(s):  
Bit Error Rate ◽  
Error Rate ◽  
Viterbi Algorithm ◽  
Continuous Phase ◽  
Sequence Estimation ◽  
Estimation Scheme

Rate-Compatible Punctured Ring Convolutional Coded Continuous Phase Modulation

2012 ◽  
Vol 195-196 ◽  
pp. 217-220
Author(s):  
Lei Zhang ◽  
Man Ping Tong ◽  
Hong Bo Wang
Keyword(s):  
Bit Error Rate ◽  
Error Rate ◽  
Phase Modulation ◽  
Euclidean Distance ◽  
Convolutional Codes ◽  
Continuous Phase ◽  
Transmission Efficiency ◽  
Continuous Phase Modulation ◽  
Simulation Results ◽  
Squared Euclidean Distance

In this paper, continuous phase modulation (CPM) with rate-compatible punctured ring convolutional codes is investigated. Some typical schemes with maximum normalized minimum squared euclidean distance (NMSED) are searched and given. The performance of bit error rate for rate-compatible punctured ring convolutional coded CPM on AWGN channel is simulated, and simulation results show that this system can provide good performance of bit error rate and variable-rate capabilities. Furthermore, simulation results also prove that the transmission efficiency increases when code rate is decreasing.

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.

Bit-Error-Rate Degradation Due to Inter-Channel Crosstalk of Different Signal Format

2019 ◽  
Vol E102.B (5) ◽  
pp. 1000-1004
Author(s):  
Naruki SHINOHARA ◽  
Koji IGARASHI ◽  
Kyo INOUE
Keyword(s):  
Bit Error Rate ◽  
Error Rate

ANALISIS SENSITIVITAS VIDEO MPEG-4 BERDASARKAN STRUKTUR FRAME PADA TRANSMISI DVB-T

2020 ◽  
Vol 25 (2) ◽  
pp. 86-97
Author(s):  
Sandy Suryo Prayogo ◽  
Tubagus Maulana Kusuma
Keyword(s):  
Deep Learning ◽  
Bit Error Rate ◽  
Error Rate ◽  
Signal To Noise Ratio ◽  
Similarity Index ◽  
Structural Similarity ◽  
Signal To Noise ◽  
Structural Similarity Index ◽  
Noise Ratio

DVB merupakan standar transmisi televisi digital yang paling banyak digunakan saat ini. Unsur terpenting dari suatu proses transmisi adalah kualitas gambar dari video yang diterima setelah melalui proses transimisi tersebut. Banyak faktor yang dapat mempengaruhi kualitas dari suatu gambar, salah satunya adalah struktur frame dari video. Pada tulisan ini dilakukan pengujian sensitifitas video MPEG-4 berdasarkan struktur frame pada transmisi DVB-T. Pengujian dilakukan menggunakan simulasi matlab dan simulink. Digunakan juga ffmpeg untuk menyediakan format dan pengaturan video akan disimulasikan. Variabel yang diubah dari video adalah bitrate dan juga group-of-pictures (GOP), sedangkan variabel yang diubah dari transmisi DVB-T adalah signal-to-noise-ratio (SNR) pada kanal AWGN di antara pengirim (Tx) dan penerima (Rx). Hasil yang diperoleh dari percobaan berupa kualitas rata-rata gambar pada video yang diukur menggunakan metode pengukuran structural-similarity-index (SSIM). Dilakukan juga pengukuran terhadap jumlah bit-error-rate BER pada bitstream DVB-T. Percobaan yang dilakukan dapat menunjukkan seberapa besar sensitifitas bitrate dan GOP dari video pada transmisi DVB-T dengan kesimpulan semakin besar bitrate maka akan semakin buruk nilai kualitas gambarnya, dan semakin kecil nilai GOP maka akan semakin baik nilai kualitasnya. Penilitian diharapkan dapat dikembangkan menggunakan deep learning untuk memperoleh frame struktur yang tepat di kondisi-kondisi tertentu dalam proses transmisi televisi digital.

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