scholarly journals Performance of Unequal Error Protection Using Maximum A- posteriori Probability Algorithm and Modified MAP in Additive White Gaussian Noise and Fading Channel

2008 ◽  
Vol 4 (7) ◽  
pp. 585-590
Author(s):  
Gnanasekaran T. ◽  
K. Duraiswamy
Keyword(s):  
Gaussian Noise ◽  
Fading Channel ◽  
Additive White Gaussian Noise ◽  
Unequal Error Protection ◽  
White Gaussian Noise ◽  
Posteriori Probability ◽  
Maximum A Posteriori ◽  
A Posteriori ◽  
Error Protection ◽  
A Posteriori Probability

scholarly journals Threshold Computation for Spatially Coupled Turbo-Like Codes on the AWGN Channel

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 240
Author(s):  
Muhammad Umar Farooq ◽  
Alexandre Graell i Amat ◽  
Michael Lentmaier
Keyword(s):  
Gaussian Noise ◽  
Belief Propagation ◽  
Additive White Gaussian Noise ◽  
Maximum A Posteriori ◽  
Prediction Methods ◽  
Threshold Analysis ◽  
A Posteriori ◽  
Awgn Channel ◽  
Efficient Prediction ◽  
Binary Erasure Channel

In this paper, we perform a belief propagation (BP) decoding threshold analysis of spatially coupled (SC) turbo-like codes (TCs) (SC-TCs) on the additive white Gaussian noise (AWGN) channel. We review Monte-Carlo density evolution (MC-DE) and efficient prediction methods, which determine the BP thresholds of SC-TCs over the AWGN channel. We demonstrate that instead of performing time-consuming MC-DE computations, the BP threshold of SC-TCs over the AWGN channel can be predicted very efficiently from their binary erasure channel (BEC) thresholds. From threshold results, we conjecture that the similarity of MC-DE and predicted thresholds is related to the threshold saturation capability as well as capacity-approaching maximum a posteriori (MAP) performance of an SC-TC ensemble.

Maximum a posteriori probability background estimation

1999 ◽  
Vol 105 (2) ◽  
pp. 1365-1366
Author(s):  
Thomas J. Green ◽  
William H. Payne ◽  
Vivian E. Titus ◽  
Eric J. Van Allen
Keyword(s):  
Posteriori Probability ◽  
Maximum A Posteriori ◽  
A Posteriori ◽  
A Posteriori Probability ◽  
Background Estimation
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