Low-complexity Volterra-inspired neural network equalizer in 100-G band-limited IMDD PON system.
Opt Lett
; 47(21): 5692-5695, 2022 Nov 01.
Article
in En
| MEDLINE
| ID: mdl-37219305
ABSTRACT
One of the most promising solutions for 100 Gb/s line-rate passive optical networks (PONs) is intensity modulation and direct detection (IMDD) technology together with a digital signal processing- (DSP-) based equalizer for its advantages of system simplicity, cost-effectiveness, and energy-efficiency. However, due to restricted hardware resources, the effective neural network (NN) equalizer and Volterra nonlinear equalizer (VNLE) have the drawback of high implementation complexity. In this paper, we incorporate an NN with the physical principles of a VNLE to construct a white-box low-complexity Volterra-inspired neural network (VINN) equalizer. This equalizer has better performance than a VNLE at the same complexity and attains similar performance with much lower complexity than a VNLE with optimized structural hyperparameter. The effectiveness of the proposed equalizer is verified in 1310â
nm band-limited IMDD PON systems. A 30.5-dB power budget is achieved with the 10-G-class transmitter.
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Collection:
01-internacional
Database:
MEDLINE
Language:
En
Journal:
Opt Lett
Year:
2022
Document type:
Article