Journal of Optoelectronics · Laser, Volume. 36, Issue 2, 200(2025)
Simulation on machine learning-based underwater optical communication channel estimation and signal demodulation algorithm
[2] [2] ZENG Z Q. A survey of underwater wireless optical communication[D]. Vancouver: University of British Columbia,2015.
[3] [3] YE H, LI G Y, JUANG B H. Power of deep learning for channel estimation and signal detection in OFDM systems[J]. IEEE Wireless Communications Letters, 2018, 7(1):114-117.
[4] [4] LEE H, LEE I, LEE S H. Deep learning based transceiver design for multi-colored VLC systems[J]. Optics Express, 2018, 26(5):6222-6238.
[5] [5] LU H, JIANG M, CHENG J. Deep learning aided robust joint channel classification, channel estimation, and signal detection for underwater optical communication[J]. IEEE Transactions on Communications, 2020, 69(4):2290-2303.
[6] [6] CHEN J, JIANG M. Joint blind channel estimation, channel equalization, and data detection for underwater visible light communication systems[J]. IEEE Wireless Communications Letters, 2021, 10(12):2664-2668.
[7] [7] JIANG R, SUN C, ZHANG L, et al. Deep learning aided signal detection for SPAD-based underwater optical wireless communications[J]. IEEE Access, 2020, 8:20363-20374.
[11] [11] SALAMA W M, ALY M H, AMER E S. Enhanced deep learning based channel estimation for indoor VLC systems[J]. Optical and Quantum Electronics, 2022, 54(9):535.
[12] [12] ARMSTRONG J, SCHMIDT B J C. Comparison of asymmetrically clipped optical OFDM and DC-biased optical OFDM in AWGN[J]. IEEE Communications Letters, 2008, 12(5):343-345.
[13] [13] GABRIEL C, KHALIGHI M A, BOURENNANE S, et al. Monte-Carlo-based channel characterization for underwater optical communication systems[J]. Journal of Optical Communications and Networking, 2013, 5(1):1-12.
[14] [14] JAMALI M V, MIRANI A, PARSAY A, et al. Statistical studies of fading in underwater wireless optical channels in the presence of air bubble, temperature, and salinity random variations[J]. IEEE Transactions on Communications, 2018, 66(10):4706-4723.
[15] [15] DUMOULIN V, VISIN F. A guide to convolution arithmetic for deep learning[EB/OL]. (2016-03-23)[2023-08-24]. https:arxiv.org/abs/1603.07285.
[16] [16] GAO X, JIN S, WEN C K, et al. ComNet: Combination of deep learning and expert knowledge in OFDM receivers[J]. IEEE Communications Letters, 2018, 22(12):2627-2630.
[17] [17] HARTIGAN J A, WONG M A. Algorithm AS 136: A k-means clustering algorithm[J]. Journal of the Royal Statistical Society. Series c (Applied Statistics), 1979, 28(1):100-108.
[18] [18] WANG Z P, CHEN S F. BER performance analysis of an OFDM-based visible light communication system using DHT postcoding[J]. Optoelectronics Letters, 2022, 18(5):288-292.
[19] [19] YU J, WEI Z J, GUAN X J, et al. High-speed real-time visible light communication system based on InGaN/GaN-base multi-quantum well blue micro-LED[J]. Optoelectronics Letters, 2021, 17(12):741-745.
Get Citation
Copy Citation Text
YE Pengfei, ZHANG Peng, WU Wentao, YU Hao, FAN Yunlong, ZHANG Penghao. Simulation on machine learning-based underwater optical communication channel estimation and signal demodulation algorithm[J]. Journal of Optoelectronics · Laser, 2025, 36(2): 200
Category:
Received: Aug. 24, 2023
Accepted: Jan. 23, 2025
Published Online: Jan. 23, 2025
The Author Email: ZHANG Peng (zhangpeng@cust.edu.cn)