arXiv subjects

Sarah Masaad

Publications and source records attributed to Sarah Masaad.

3 recordsLinked to original sources

arXiv2026

Baudrate- and Reach-Flexible All-Optical Equalization with a Co-Packaged Photonic Reservoir and Receiver

Intensity-modulation direct-detection links must support increasing baudrates and transmission distances while operating under stringent power and cost constraints. However, as data rates and reaches increase, chromatic dispersion induces stronger inter-symbol interference and, after direct detection, frequency-selective fading, thus requiring increasingly powerful equalization. In conventional receivers, this translates into digital equalization whose complexity scales unfavorably with data rate. Photonic-domain equalization offers a hardware-based alternative that operates naturally at line rate and mitigates frequency fading. However, prior demonstrations were not readily adaptable for different rate and/or reach operation. In this paper, we experimentally demonstrate all-optical equalization across 10-46 Gbaud and 10-250 km SSMF in the C-band enabled solely through retraining of the readout layer, achieving up to four orders of magnitude BER improvement over standard DSP equalization. The demonstrator comprises a 16-node spatially multiplexed reservoir, programmable on-chip readout, and co-packaged receiver front-end. To our knowledge, this is the first co-packaged photonic reservoir receiver and the first demonstration of simultaneous baudrate- and reach-flexible equalization using a fixed-topology integrated photonic circuit.

physics.optics↗

arXiv2026

Node-reduction through Joint Optimization of Input and Readout Layers in Photonic Reservoir Equalization

Photonic reservoir computing is a machine learning paradigm in which a recurrent neural network remains fixed while only the output weights are trained. This makes it a well-suited approach for high-speed signal equalisation in optical communication systems, offering a trainable, low-power, and low-complexity solution. However, achieving strong performance typically requires relatively large network sizes, as learning is confined to the output layer. To address this, we investigate the role of trainable input mappings alongside conventional output weight optimisation. Across a range of short- and mid-reach IM/DD transmission scenarios, reaching up to 200 km for a 28 GBd NRZ signal, improvements of over two orders of magnitude in BER are achieved. This enables halving the network size while maintaining comparable performance. Furthermore, we show that this approach effectively extends the memory of the reservoir, resulting in over three orders of magnitude improvement in memory-intensive tasks. These results also show that starting at 16 nodes a performance of at least one to two magnitudes better than both a complexity matched FFE and a Volterra filter of second order are reached.

physics.optics↗

arXiv2025

Real-time all-optical signal equalisation with silicon photonic recurrent neural networks

Communication through optical fibres experiences limitations due to chromatic dispersion and nonlinear Kerr effects that degrade the signal. Mitigating these impairments is typically done using complex digital signal processing algorithms. However, these equalisation methods require significant power consumption and introduce high latencies. Photonic reservoir computing (a subfield of neural networks) offers an alternative solution, processing signals in the analog optical Domain. In this work, we present to our knowledge the very first experimental demonstration of real-time online equalisation of fibre distortions using a silicon photonics chip that combines the recurrent reservoir and the programmable readout layer. We successfully equalize a 28 Gbps on-off keying signal across varying power levels and fibre lengths, even in the highly nonlinear regime. We obtain bit error rates orders of magnitude below previously reported optical equalisation methods, reaching as low as 4e-7 , far below the generic forward error correction limit of 5.8e-5 used in commercial Ethernet interfaces. Also, simulations show that simply by removing delay lines, the system becomes compatible with line rates of 896 Gpbs. Using wavelength multiplexing, this can result in a throughput in excess of 89.6 Tbps. Finally, incorporating non-volatile phase shifters, the power consumption can be less than 6 fJ/bit.

physics.optics↗