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DEEP LEARNING FOR FRAME ERROR PROBABILITY PREDICTION IN BICM-OFDM SYSTEMS

Abstract: 

In the context of wireless communications, we propose a deep learning approach to learn the mapping from the instantaneous state of a frequency selective fading channel to the corresponding frame error probability (FEP) for an arbitrary set of transmission parameters. We propose an abstract model of a bit interleaved coded modulation (BICM) orthogonal frequency division multiplexing (OFDM) link chain and show that the maximum likelihood (ML) estimator of the model parameters estimates the true FEP distribution. Further, we exploit deep neural networks as a general purpose tool to implement our model and propose a training scheme for which, even while training with the binary frame error events (i.e., ACKs / NACKs), the network outputs converge to the FEP conditioned on the input channel state. We provide simulation results that demonstrate gains in the FEP prediction accuracy with our approach as compared to the traditional effective exponential SIR metric (EESM) approach for a range of channel code rates, and show that these gains can be exploited to increase the link throughput.

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1 user has voted: Vidit Saxena

Paper Details

Authors:
Vidit Saxena, Joakim Jaldén, Hugo Tullberg, Mats Bengtsson
Submitted On:
19 April 2018 - 5:17pm
Short Link:
Type:
Presentation Slides
Event:
Presenter's Name:
Vidit Saxena
Paper Code:
4286
Document Year:
2018
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Document Files

Deep Learning for FEP Prediction.pdf

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[1] Vidit Saxena, Joakim Jaldén, Hugo Tullberg, Mats Bengtsson, "DEEP LEARNING FOR FRAME ERROR PROBABILITY PREDICTION IN BICM-OFDM SYSTEMS", IEEE SigPort, 2018. [Online]. Available: http://sigport.org/3030. Accessed: Oct. 19, 2018.
@article{3030-18,
url = {http://sigport.org/3030},
author = {Vidit Saxena; Joakim Jaldén; Hugo Tullberg; Mats Bengtsson },
publisher = {IEEE SigPort},
title = {DEEP LEARNING FOR FRAME ERROR PROBABILITY PREDICTION IN BICM-OFDM SYSTEMS},
year = {2018} }
TY - EJOUR
T1 - DEEP LEARNING FOR FRAME ERROR PROBABILITY PREDICTION IN BICM-OFDM SYSTEMS
AU - Vidit Saxena; Joakim Jaldén; Hugo Tullberg; Mats Bengtsson
PY - 2018
PB - IEEE SigPort
UR - http://sigport.org/3030
ER -
Vidit Saxena, Joakim Jaldén, Hugo Tullberg, Mats Bengtsson. (2018). DEEP LEARNING FOR FRAME ERROR PROBABILITY PREDICTION IN BICM-OFDM SYSTEMS. IEEE SigPort. http://sigport.org/3030
Vidit Saxena, Joakim Jaldén, Hugo Tullberg, Mats Bengtsson, 2018. DEEP LEARNING FOR FRAME ERROR PROBABILITY PREDICTION IN BICM-OFDM SYSTEMS. Available at: http://sigport.org/3030.
Vidit Saxena, Joakim Jaldén, Hugo Tullberg, Mats Bengtsson. (2018). "DEEP LEARNING FOR FRAME ERROR PROBABILITY PREDICTION IN BICM-OFDM SYSTEMS." Web.
1. Vidit Saxena, Joakim Jaldén, Hugo Tullberg, Mats Bengtsson. DEEP LEARNING FOR FRAME ERROR PROBABILITY PREDICTION IN BICM-OFDM SYSTEMS [Internet]. IEEE SigPort; 2018. Available from : http://sigport.org/3030