Binary Neural Network Aided CSI Feedback in Massive MIMO System

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2012

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L. Liu, C. Oestges, J. Poutanen, K. Haneda, P. Vainikainen, F. Quitin, F. Tufvesson, and P. De Doncker, “The cost 2100 mimo channel model,” IEEE Wireless Communications , vol. 19, no. 6, pp. 92–99, 2012

2012

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E. G. Larsson, O. Edfors, F. Tufvesson, and T. L. Marzetta, “Massive mimo for next generation wireless systems,” IEEE communications magazine , vol. 52, no. 2, pp. 186–195, 2014

2014

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F. Boccardi, R. W. Heath, A. Lozano, T. L. Marzetta, and P. Popovski, “Five disruptive technology directions for 5g,” IEEE communications magazine , vol. 52, no. 2, pp. 74–80, 2014

2014

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C.-K. Wen, S. Jin, K.-K. Wong, J.-C. Chen, and P. Ting, “Channel estimation for massive mimo using gaussian-mixture bayesian learning,” IEEE Transactions on Wireless Communications , vol. 14, no. 3, pp. 1356–1368, 2014

2014

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M. Courbariaux, Y. Bengio, and J.-P. David, “Binaryconnect: Training deep neural networks with binary weights during propagations,” in Advances in neural information processing systems , 2015, pp. 3123–3131

2015

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M. Rastegari, V. Ordonez, J. Redmon, and A. Farhadi, “Xnor-net: Imagenet classification using binary convolutional neural networks,” in European conference on computer vision . Springer, 2016, pp. 525–542

2016

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C.-K. Wen, W.-T. Shih, and S. Jin, “Deep learning for massive mimo csi feedback,” IEEE Wireless Communications Letters , vol. 7, no. 5, pp. 748–751, 2018

2018

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T. Wang, C.-K. Wen, S. Jin, and G. Y. Li, “Deep learning-based csi feedback approach for time-varying massive mimo channels,” IEEE Wireless Communications Letters , vol. 8, no. 2, pp. 416–419, 2018

2018

Cited alongside, same era.

Z. Liu, L. Zhang, and Z. Ding, “Exploiting bi-directional channel reciprocity in deep learning for low rate massive mimo csi feedback,” IEEE Wireless Communications Letters , vol. 8, no. 3, pp. 889–892, 2019

2019

Cited alongside, same era.

Y. Yang, F. Gao, G. Y. Li, and M. Jian, “Deep learning-based downlink channel prediction for fdd massive mimo system,” IEEE Communications Letters , vol. 23, no. 11, pp. 1994–1998, 2019

2019

Cited alongside, same era.

Q. Yang, M. B. Mashhadi, and D. Gündüz, “Deep convolutional compression for massive mimo csi feedback,” in 2019 IEEE 29th international workshop on machine learning for signal processing (MLSP) . IEEE, 2019, pp. 1–6

2019

Cited alongside, same era.

Z. Lu, J. Wang, and J. Song, “Multi-resolution csi feedback with deep learning in massive mimo system,” in ICC 2020-2020 IEEE International Conference on Communications (ICC) . IEEE, 2020, pp. 1–6

2020

Closest in time.

J. Guo, C.-K. Wen, S. Jin, and G. Y. Li, “Convolutional neural network-based multiple-rate compressive sensing for massive mimo csi feedback: Design, simulation, and analysis,” IEEE Transactions on Wireless Communications , vol. 19, no. 4, pp. 2827–2840, 2020

2020

Closest in time.

X. Li and H. Wu, “Spatio-temporal representation with deep neural recurrent network in mimo csi feedback,” IEEE Wireless Communications Letters , vol. 9, no. 5, pp. 653–657, 2020

2020

Closest in time.

Z. Cao, W.-T. Shih, J. Guo, C.-K. Wen, and S. Jin, “Lightweight convolutional neural networks for csi feedback in massive mimo,” arXiv preprint arXiv:2005.00438 , 2020

Original

2020

Closest in time.