arXiv subjects
Publications and source records attributed to Stylianos Sygletos.
We experimentally evaluated the sensing-communication trade-off from the fixed-point precision MIMO equalizer using FPGA. At 7-bit, noise floor drops 100x and angular error 63%, but the communication performance saturates while the hardware complexity rises.
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.
We develop a complex-valued kernel-adaptive-filtering based method for phase and amplitude distortion compensation in cascaded fibre-optical parametric amplifier (FOPA) links. Our algorithm predicts and cancels both distortions induced by pump-phase modulation across all amplification stages, achieving more than an order of magnitude improvement in BER.
We propose a novel MIMO-WDM Volterra-based nonlinear-equalisation scheme with adaptive time-domain nonlinear stages enhanced by filtering in both the power and optical signal waveforms. This approach efficiently captures the interplay between dispersion and non-linearity in each step, leading to $46\%$ complexity reduction for $9\times 9$-MIMO operation.
We introduce low complexity machine learning based approach for mitigating nonlinear impairments in optical fiber communications systems. The immense intricacy of the problem calls for the development of "smart" methodology, simplifying the analysis without losing the key features that are important for recovery of transmitted data. The proposed sparse identification method for optical systems (SINO) allows to determine the minimal (optimal) number of degrees of freedom required for adaptive mitigation of detrimental nonlinear effects. We demonstrate successful application of the SINO method both for standard fiber communication links and for few-mode spatial-division-multiplexing systems.
Since Shannon proved that Gaussian distribution is the optimum for a linear channel with additive white Gaussian noise and he calculated the corresponding channel capacity, it remains the most applied distribution in optical communications while the capacity result is celebrated as the seminal linear Shannon limit. Yet, when it is applied in nonlinear channels (e.g. fiber-optics) it has been shown to be non-optimum, yielding the same result as for uncoded transmission in the high nonlinear regime. This has led to the notion of nonlinear Shannon limit, which predicts vanishing capacity at high nonlinearity. However, recent findings indicate that non-Gaussian distribution may lead to improved capacity estimations, urging for an exciting search for novel methods in nonlinear optical communications. Here for the first time, we show that it is possible to transmit information above the existing limits by using a novel probabilistic shaping of the input signal, which we call ripple distribution