RS-A-SISO algorithms for serially concatenated CPM over fading channels and density evolution analysis

2003 ◽  
Vol 39 (22) ◽  
pp. 1597 ◽  
Author(s):  
Kyuhyuk Chung ◽  
Jun Heo
Keyword(s):  
Fading Channels ◽  
Density Evolution ◽  
Evolution Analysis ◽  
Serially Concatenated

The Study of Coded CPM Schemes

2012 ◽  
Vol 198-199 ◽  
pp. 1408-1412
Author(s):  
Lin Bo Su ◽  
Jian Hua Chen ◽  
Ying Peng Hu
Keyword(s):  
Fading Channels ◽  
Convolutional Codes ◽  
Continuous Phase ◽  
Coded Modulation ◽  
Superior Performance ◽  
Continuous Phase Modulation ◽  
Codes Over Rings ◽  
Constant Envelope ◽  
Modulation Schemes ◽  
Serially Concatenated

Continuous Phase Modulation (CPM) schemes belong to a class of constant-envelope digital modulation schemes, the constant-envelope nature of the CPM signals makes them robust for the nonlinear and fading channels, and very useful for the satellite and/or the mobile radio channels. Comparing to PSK modulation, CPM modulation can not only provide spectral economy, but also exhibit a “coding gain”. CPM can be decomposed into a Continuous Phase Encoder (CPE) followed by a Memoryless Modulator (MM), this allows many new coded modulation schemes of combination of convolutional encoder and CPM modulator to be possible, such as serially-concatenated CPM (SC-CPM), SC-CPM with Convolutional Codes over Rings, pragmatic CPM (P-CPM), Concatenation of convolutional endocder and extended CE（CCEC）, etc. Some simulations show that these new CPM schemes can offer superior performance.

scholarly journals Analysis of TDMP Algorithm of LDPC Codes Based on Density Evolution and Gaussian Approximation

Entropy ◽  
2019 ◽  
Vol 21 (5) ◽  
pp. 457 ◽  
Author(s):  
Xiumin Wang ◽  
Hong Chang ◽  
Jun Li ◽  
Weilin Cao ◽  
Liang Shan
Keyword(s):  
Message Passing ◽  
Belief Propagation ◽  
Gaussian Approximation ◽  
Bp Algorithm ◽  
Turbo Decoding ◽  
Density Evolution ◽  
Analysis Process ◽  
Evolution Analysis ◽  
Simplified Algorithm ◽  
Previous Iteration

Based on density evolution analysis of the existing belief propagation (BP) algorithm, the Turbo Decoding Message Passing (TDMP) algorithm was analyzed from the perspective of density evolution and Gaussian approximation, and the theoretical analysis process of TDMP algorithm was given. When calculating the prior message of each layer of the TDMP algorithm, the check message of the previous iteration should be subtracted. Therefore, the result will not be convergent, if the TDMP algorithm is directly analyzed based on density evolution and Gaussian approximation. We researched the TDMP algorithm based on the symmetry conditions to obtain the convergent result. When using density evolution (DE) and Gaussian approximation to analyze the decoding convergence of the TDMP algorithm, we can provide a theoretical basis for proving the superiority of the algorithm. Then, based on the DE theory, we calculated the probability density function (PDF) of the check-to-variable information of TDMP and its simplified algorithm, and then gave it a calculation based on the process of the normalization factor. Simulation results show that the decoding convergence speed of the TDMP algorithm was faster and the iterations were smaller compared to the BP algorithm under the same conditions.

An accurate density evolution analysis for a finite-state Markov channel

2010 ◽  
Vol 13 (1) ◽  
pp. 85-97 ◽  
Author(s):  
Naoto Kobayashi ◽  
Toshiyasu Matsushima ◽  
Shigeichi Hirasawa
Keyword(s):  
Density Evolution ◽  
Evolution Analysis ◽  
Finite State ◽  
Markov Channel
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