Tunable optical matrix convolution of 20-Gbit/s QPSK 2-D data with a kernel using optical wave mixing

被引:0
|
作者
Minoofar, Amir [1 ]
Alhaddad, Abdulrahman [1 ]
Ko, Wing [1 ]
Karapetyan, Narek [1 ]
Almaiman, Ahmed [2 ]
Zhou, Huibin [1 ]
Ramakrishnan, Muralekrishnan [1 ]
Annavaram, Murali [1 ]
Tur, Moshe [3 ]
Habif, Jonathan L. [1 ,4 ]
Willner, Alan E. [1 ,5 ]
机构
[1] Univ Southern Calif, Dept Elect Engn, Los Angeles, CA 90089 USA
[2] King Saud Univ, Riyadh, Saudi Arabia
[3] Tel Aviv Univ, Sch Elect Engn, IL-69978 Ramat Aviv, Israel
[4] Univ Southern Calif, Inst Informat Sci, 890 Winter St, Waltham, MA 02451 USA
[5] Univ Southern Calif, Dornsife Dept Phys & Astron, Los Angeles, CA 90089 USA
关键词
25;
D O I
10.1364/OL.530189
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Compared to its electronic counterpart, optically performed matrix convolution can accommodate phase-encoded data at high rates while avoiding optical-to-electronic-to-optical (OEO) conversions. We experimentally demonstrate a reconfigurable matrix convolution of quadrature phase-shift keying (QPSK)-encoded input data. The two-dimensional (2-D) input data is serialized, and its time-shifted replicas are generated. This 2-D data is convolved with a 1-D kernel with coefficients, which are applied by adjusting the relative phase and amplitude of the kernel pumps. Time-shifted data replicas (TSDRs) and kernel pumps are coherently mixed using nonlinear wave mixing in a periodically poled lithium niobate (PPLN) waveguide. To show the tunability and reconfigurability of this approach, we vary the kernel coefficients, kernel sizes (e.g., 2x1 or 3x1), and input data rates (e.g., 6-20 Gbit/s). The convolution results are verified to be error-free under an applied: (a) 2x1 kernel, resulting in a 16-quadrature amplitude modulation (QAM) output with an error vector magnitude (EVM) of similar to 5.1-8.5%; and (b) 3x1 kernel, resulting in a 64-QAM output with an EVM of similar to 4.9-5.5%. (c) 2024 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.
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收藏
页码:4899 / 4902
页数:4
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