Intelligent Optical Communication Based on Wasserstein Generative Adversarial Network

Mu Di; Meng Wen; Zhao Shanghong; Wang Xiang; Liu Wenya

doi:10.3788/CJL202047.1106005

[1] Zeng Y, Zhang R. Energy-efficient UAV communication with trajectory optimization[J]. IEEE Transactions on Wireless Communications, 16, 3747-3760(2017). http://arxiv.org/abs/1608.01828v1

[2] Hunt B R, Iler A L, Bailey C A et al. Synthesis of atmospheric turbulence point spread functions by sparse and redundant representations[J]. Optical Engineering, 57, 024101(2018).

[3] Liu J M, Wang P P, Zhang X K et al. Deep learning based atmospheric turbulence compensation for orbital angular momentum beam distortion and communication[J]. Optics Express, 27, 16671-16688(2019).

[4] Xu M M, Bu X Z, He Z L et al. Atmospheric turbulence interference compensation for missile-borne infrared attitude measurement[J]. Infrared Physics & Technology, 97, 69-73(2019).

[5] Pappu C S, Carroll T L, Flores B C. Simultaneous radar-communication systems using controlled chaos-based frequency modulated waveforms[J]. IEEE Access, 8, 48361-48375(2020).

[6] O'Shea T. Hoydis J. An introduction to deep learning for the physical layer[J]. IEEE Transactions on Cognitive Communications and Networking, 3, 563-575(2017).

[7] Dörner S, Cammerer S, Hoydis J et al. Deep learning based communication over the air[J]. IEEE Journal of Selected Topics in Signal Processing, 12, 132-143(2018).

[8] Felix A, Cammerer S, Dörner S et al. OFDM-autoencoder for end-to-end learning of communications systems. [C]∥2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), June 25-28, 2018, Kalamata, Greece. New York: IEEE(2018).

[9] Ye H, Li G Y. Juang B H F, et al. Channel agnostic end-to-end learning based communication systems with conditional GAN. [C]∥2018 IEEE Globecom Workshops (GC Wkshps), December 9-13, 2018, Abu Dhabi, United Arab Emirates. New York: IEEE(2018).

[10] Arjovsky M. -01-17)[2020-06-04]. https:∥arxiv., org/abs/1701, 04862(2017).

[11] Zou P, Zhao Y H, Hu F C et al. Research status of machine learning based signal processing in visible light communication[J]. Laser & Optoelectronics Progress, 57, 010001(2020).

[12] Xiang Y, Bao C C. A pa rallel-data-free speech enhancement method using multi-objective learning cycle-consistent generative adversarial network[J]. ACM Transactions on Audio, Speech, and Language Processing, 28, 1826-1838(2020).

[13] Fournier N, Guillin A. On the rate of convergence in Wasserstein distance of the empirical measure[J]. Probability Theory and Related Fields, 162, 707-738(2015).

[14] Wang M H, Yuan X H, Li J et al. Propagation of radial partially coherent beams in anisotropic non-Kolmogorov turbulence[J]. Acta Optica Sinica, 38, 0306003(2018).

[15] Baum D S, Hansen J, Salo J et al. An interim channel model for beyond-3G systems: extending the 3GPP spatial channel model (SCM). [C]∥2005 IEEE 61st Vehicular Technology Conference, May 30-June 1, 2005, Stockholm, Sweden. New York: IEEE, 3132-3136(2005).

[16] Goodfellow I J, Pouget-Abadie J, Mirza M et al. Generative adversarial nets. [C]∥Proceedings of the 27th International Conference on Neural Information Processing Systems, December 8-13, 2014, Montreal, Quebec, Canada. New York: Curran Associates, 2, 2672-2680(2014).

[17] Yang Z, Chen W, Wang F et al[2020-06-04]. Improving neural machine translation with conditional sequence generative adversarial nets [2020-06-04].https:∥arxiv.org/pdf/1703.04887.pdf..

[18] Wang L, Liu J Z, Duan D P. Simulation system of QPSK and performance analysis of BER[J]. Computer Knowledge and Technology, 7, 1995-1996(2011).

[19] Duchi J C, Hazan E, Singer Y. Adaptive subgradient methods for online learning and stochastic optimization[J]. Journal of Machine Learning Research, 12, 2121-2159(2011).

[20] Jin Y C, Chen X B, Mao X R et al. Influence of modulation degree on performances of visible light communication system[J]. Chinese Journal of Lasers, 46, 0506001(2019).

[21] Wang Z H, Wu S, Liu C et al. The regression of MNIST dataset based on convolutional neural network[M]. ∥Hassanien A E, Azar A T, Gaber T, et al. The international conference on advanced machine learning technologies and applications (AMLTA2019). Advances in intelligent systems and computing. Cham: Spri, 921, 59-68(2019).