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Digital receivers are required to recover the transmitted symbols from their observed channel output.
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J. G. Andrews · 2005
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Y. Bengio · 2009
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K. Gregor and Y. LeCun · 2010
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3G Evolution: HSPA and LTE for Mobile Broadband
E. Dahlman, S. Parkvall, J. Skold, and P. Beming · 2010
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Network Information Theory
A. El Gamal and Y. H. Kim · 2011
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“Plug-and-play priors for model based reconstruction”
S. V. Venkatakrishnan, C. A. Bouman, and B. Wohlberg · 2013
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“Deep unfolding: Model-based inspiration of novel deep architectures”
J. R. Hershey, J. Le Roux, and F. Weninger · 2014
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“MIMO-OFDM with nonlinear power amplifiers”
I. Iofedov and D. Wulich · 2015
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“Deep learning”
Y. LeCun, Y. Bengio, and G. Hinton · 2015
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“Quantized massive MU-MIMO-OFDM uplink”
C. Struder and G. Durisi · 2016
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“Convergence analysis and assurance for Gaussian message passing iterative detector in massive MU-MIMO systems”
L. Liu, C. Yuen, Y. L. Guan, Y. Li, and Y. Su · 2016
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“Communication system design and analysis for asynchronous molecular timing channels”
N. Farsad, Y. Murin, W. Guo, C-B. Chae, A. W. Eckford, and A. J. Goldsmith · 2017
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“An introduction to deep learning for the physical layer”
T. O’Shea and J. Hoydis · 2017
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“The secrecy capacity of Gaussian MIMO channels with finite memory”
N. Shlezinger, D. Zahavi, R. Murin, and R. Dabora · 2017
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“On the capacity of MIMO broadband power line communications channels”
N. Shlezinger, R. Shaked, and R. Dabora · 2018
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“A very brief introduction to machine learning with applications to communication systems”
“Radar and communication coexistence: An overview: A review of recent methods”
L. Zheng, M. Lops, Y. C. Eldar and X. Wang · 2019
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D. Gunduz, P. de Kerret, N. D. Sidiropoulos, D. Gesbert, C. Murthy, and M. van der Schaar · 2019
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“Deep unfolding for communications systems: A survey and some new directions”
A. Balatsoukas-Stimming and C. Struder · 2019
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“Deep symbol detection for millimeter wave communications”
Y. Liao, N. Farsad, N. Shlezinger, Y. C. Eldar, and A. J. Goldsmith · 2019
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“An algorithm unrolling approach to deep blind image deblurring”
Y. Li, M. Tofighi, J. Geng, V. Monga and Y. C. Eldar · 2019
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O. Simeone · 2018
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“Deep learning for intelligent wireless networks: A comprehensive survey”
Q. Mao, F. Hu and Q. Hao · 2018
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“Model-driven deep learning for physical layer communications”
H. He, S. Jin, C.-K. Wen, F. Gao, G. Y. Li, and Z. Xu · 2018
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“Communication Algorithms via deep learning”
H. Kim, Y. Jiang, R. Rana, S. Kannan, S. Oh, and P. Viswanath · 2018
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“Neural network detection of data sequences in communication systems”
N. Farsad and A. Goldsmith · 2018
Cited alongside, same era.
“Brain-inspired wireless communications: Where reservoir computing meets MIMO-OFDM”
S. Mosleh, L. Liu, C. Sahin, Y. R. Zheng, and Y. Yi · 2018
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“Blind channel equalization using variational autoencoders”
A. Caciularu and D. Burshtein · 2018
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“Learning to detect”
N. Samuel, T. Diskin and A. Wiesel · 2019
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“Deep signal recovery with one-bit quantization”
S. Khobahi, N. Naimipour, M. Soltanalian, and Y. C. Eldar · 2019
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“Capacity-achieving MIMO-NOMA: Iterative LMMSE detection”
L. Liu, Y. Chi, C. Yuen, Y. L. Guan, and Y. Li · 2019
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“ Model-driven deep learning for joint MIMO channel estimation and signal detection”
H. He, C.-K. Wen, S. Jin, and G. Y. Li, · 2019
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“Deep neural network-aided Gaussian message passing detection for ultra-reliable low-latency communications”
J. Guo, B. Song, Y. Chi, L. Jayasinghe, C. Yuen, Y. L. Guan, X. Du, and M. Guizani · 2019
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“DNN-aided block sparse Bayesian learning for user activity detection and channel estimation in grant-free non-orthogonal random access”
Z. Zhang, Y. Li, C. Huang, Q. Guo, C. Yuen, and Y. L. Guan · 2019
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“One-bit OFDM receivers via deep learning”
E. Balevi and J. G. Andrews · 2019
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“Deep task-based quantization”
N. Shlezinger and Y. C. Eldar · 2019
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“Deep soft interference cancellation for MIMO detection”
N. Shlezinger, R. Fu, and Y. C. Eldar · 2020
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“ViterbiNet: A deep learning based Viterbi algorithm for symbol detection”
N. Shlezinger, N. Farsad, Y. C. Eldar, and A. J. Goldsmith · 2020
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“Data-driven factor graphs for deep symbol detection”
N. Shlezinger, N. Farsad, Y. C. Eldar, and A. J. Goldsmith · 2020
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“Inference from stationary time sequences via learned factor graphs”
N. Shlezinger, N. Farsad, Y. C. Eldar, and A. J. Goldsmith · 2020
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“From learning to meta-learning: Reduced training overhead and complexity for communication systems”
O. Simeone, S. Park, and J. Kang · 2020
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