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Updated: Jul 29, 2025

Design and Characterization Methodology for Efficient Wide Range Tunable MEMS Filters
Published on: February 4, 2018
Low-complexity Volterra-inspired neural network equalizer in 100-G band-limited IMDD PON system
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 1310 nm band-limited IMDD PON systems. A 30.5-dB power budget is achieved with the 10-G-class transmitter.
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