Reduced-Complexity Artificial Neural Network Equalization for Ultra-High-Spectral-Efficient Optical Fast-OFDM Signals

Digital-based artificial neural network (ANN) machine learning is harnessed to reduce fiber nonlinearities, for the first time in ultra-spectrally-efficient optical fast orthogonal frequency division multiplexed (Fast-OFDM) signals. The proposed ANN design is of low computational load and is compared to the benchmark inverse Volterra-series transfer function (IVSTF)-based nonlinearity compensator. The two aforementioned schemes are compared for long-haul single-mode-fiber-based links at 9.69 Gb/s direct-detected optical Fast-OFDM signals. It is shown that an 80 km extension in transmission-reach is feasible when using ANN compared to IVSTF. This occurs because ANN can tackle stochastic nonlinear impairments, such as parametric noise amplification. Using ANN, the dynamic parameters requirements of the sub-ranging quantizers can also be relaxed compared to linear equalization, such as the reduction of the optimum clipping ratio and quantization bits by 2 dB and 2-bits, respectively, and by 2 dB and 2 bits when compared to the IVTSF equalizer

High-Performance and Power-Saving Mechanism for Page Activations Based on Full Independent DRAM Sub-Arrays in Multi-Core Systems

Modern DRAM devices’ performance and energy efficiency are significantly improved when the row-buffer locality is exploited properly. In multi-core architectures, however, the DRAM-based main memory banks used by the processing units, called cores, are shared. Memory interference, also known as memory contention, occurs when many cores contend for simultaneous access to the shared banks. The performance benefits provided by utilizing the available row-buffer locality are diminished by the increased memory contention brought on by the integration of more cores. Large DRAM page sizes are therefore activated in order to access only a tiny amount of data. Poor energy efficiency or wasted opportunity to loosen DRAM power timing restrictions are both downsides to this page over-fetching issue. This study introduces a Fine-Grained Activation (FGA) technique to reduce the number of involved bitlines when accessing DRAM memory. This technique significantly improves the parallelism at the DRAM subarray level to support multiple memory accesses routed to distinct subarrays inside the same memory bank. The FGA technique presented in this research intends to provide large energy savings while simultaneously delivering significant performance gains. Our evaluation findings with 4-core multi-program benchmarks demonstrate that the FGA technique proposed in this paper can significantly improve both DRAM performance and DRAM energy efficiency with a negligible area overhead. In comparison to the baseline, the Half-DRAM page activation mechanism, and the recently suggested FGA mechanism, the proposed technique in this study reduces the average DRAM memory access latency for the evaluated four-core applications by 25.6%, 27.1%, and 14.8%, respectively. Our introduced technique also decreases the DRAM activation power by an average of 46.7%, 27.1%, and 14.7%, respectively, when compared with the baseline, Half-DRAM technique, and the recently proposed FGA mechanism

Effective handling of nonlinear distortions in CO-OFDM using affinity propagation clustering

© 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.We experimentally demonstrate a system-agnostic and training-data-free nonlinearity compensator, using affinity propagation (AP) clustering in single- and multi-channel coherent optical OFDM (CO-OFDM) for up to 3200 km transmission. We show that AP outperforms benchmark deterministic and clustering algorithms by effectively tackling stochastic nonlinear distortions and inter-channel nonlinearities. AP offers up to almost 4 dB power margin extension over linear equalization in single-channel 16-quadrature amplitude-modulated CO-OFDM and a 1.4 dB increase in Q-factor over digital back-propagation in multi-channel quaternary phase-shift keying CO-OFDM. Simulated results indicate transparency to higher modulation format orders and better efficiency when a multi-carrier structure is considered.Peer reviewe

Volterra-Based Reconfigurable Nonlinear Equalizer for Coherent OFDM

Elias Giacoumidis, et al, 'Volterra-Based Reconfigurable Nonlinear Equalizer for Coherent OFDM', IEEE Photonics Technology Letters, Vol 26 (14): 1383-1386, June 2014, doi: https://doi.org/10.1109/LPT.2014.2321434. Published by IEEE.A reconfigurable nonlinear equalizer (RNLE) based on inverse Volterra series transfer function is proposed for dual-polarization (DP) and multiband coherent optical orthogonal frequency-division multiplexing (OFDM) signals. It is shown that the RNLE outperforms by 2 dB the linear equalization in a 260-Gb/s DP-OFDM system at 1500 km. The RNLE improves the tolerance to inter/intraband nonlinearities, being independent on polarization tributaries, modulation format, signal bit rate, subcarrier number, and distance.Peer reviewe