Machine Learning Techniques to Mitigate Nonlinear Phase Noise in Moderate Baud Rate Optical Communication Systems

Nonlinear phase noise (NLPN) is the most common impairment that degrades the performance of radio-over-fiber networks. The effect of NLPN in the constellation diagram consists of a shape distortion of symbols that increases the symbol error rate due to symbol overlapping when using a conventional demodulation grid. Symbol shape characterization was obtained experimentally at a moderate baud rate (250 MBd) for constellations impaired by phase noise due to a mismatch between the optical carrier and the transmitted radio frequency signal. Machine learning algorithms have become a powerful tool to perform monitoring and to identify and mitigate distortions introduced in both the electrical and optical domains. Clustering-based demodulation assisted with Voronoi contours enables the definition of non-Gaussian boundaries to provide flexible demodulation of 16-QAM and 4+12 PSK modulation formats. Phase-offset and in-phase and quadrature imbalance may be detected on the received constellation and compensated by applying thresholding boundaries obtained from impairment characterization through statistical analysis. Experimental results show increased tolerance to the optical signal-to-noise ratio (OSNR) obtained from clustering methods based on k-means and fuzzy c-means Gustafson-Kessel algorithms. Improvements of 3.2 dB for 16-QAM, and 1.4 dB for 4+12 PSK in the OSNR scale as a function of the bit error rate are obtained without requiring additional compensation algorithms

Block copolypeptide nanoparticles for the delivery of ocular therapeutics

Self-assembling block copolypeptides were prepared by sequential ring-opening polymerization of N-carboxyanhydride (NCA) derivatives of γ-benzyl-L-glutamic acid and ε-carbobenzyloxy-L-lysine, followed by selective deprotection of the benzyl glutamate block. The synthesized polymers had number average molecular weights close to theoretical values, and had low dispersities (ĐM = 1.15–1.28). Self-assembly of the amphiphilic block copolymers into nanoparticles was achieved using the “solvent-switch” method, whereby the polymer was dissolved in THF and water and the organic solvent removed by rotary evaporation. The type of nanostructures formed varied from spherical micelles to a mixture of spherical and worm-like micelles, depending on copolymer composition. The spherical micelles had an average diameter of 43 nm by dynamic light scattering, while the apparent diameter of the mixed phase system was around 200nm. Reproducibility of nanoparticle preparation was demonstrated to be excellent; almost identical DLS traces were obtained over three repeats. Following qualitative dye-solubilization experiments, the nanoparticles were loaded with the ocular anti-inflammatory drug dexamethasone. Loading efficiency of the nanoparticles was 90% and the cumulative drug release was 94% over 16 d, with a 20% burst release in the first 24 h.mabi201400471-gra-000