الفهرس | Only 14 pages are availabe for public view |
Abstract In exible and adaptive optical communication systems, e.g., elastic optical networks, the modulation format is adapted according to each user demand based on the channel state information. Therefore, at the receiver side, it is required to blindly identify the modulation format of the received signals with high accuracy, which enables the DSP algorithm embedded at the receiver to be recon- gured, accordingly. This, in turn, removes the need for sending end-to-end handshaking information between the transmitter and the receiver. In this thesis, two schemes for blind optical modulation format identication (MFI), based on the singular value decomposition (SVD) and Radon transform (RT) of the constellation diagrams, are proposed and applied in two dierent domains. In the rst domain, Jones space domain, constellation diagrams are obtained at optical signal-to-noise ratios (OSNRs) ranging from 2 to 30 dB for eight dierent modulation formats as images. The rst scheme depends on the utilization of feature vectors composed of the singular values (SVs) of the obtained images, while the second scheme is based on applying the RT and then getting the SVs. Dierent classiers are used and compared for the MFI task. The eect of varying the number of samples on the accuracy of the classi ers is studied for each modulation format. Simulation and experimental setups are provided to study the eciency of the two schemes at high bit rates for three dual-polarized modulation formats. A decimation approach for the constellation diagrams is suggested to reduce the SVD complexity, while maintaining high classication accuracy. The obtained results reveal that the proposed schemes can be accurately used to identify the optical modulation format blindly with classication rates up to 100%, even at low OSNR values of 10 dBs. Moreover, a new application of the proposed schemes in the Stoke Space (SS), which deals with the dual-polarized modulation formats, is presented. The SS gives a representation of the received signal in 3 dimensions. In our case, we take the projection of that representation on three dierent planes and deal with them as representative images. Then, we implement SVD of these obtained images and use their SVs as features. In another implementation, the RTs are obtained from the three dierent projections, and the SVD is implemented to get the features. Here, the features are prepared to train the classiers. The test scenario is performed on features extracted in the same manner from projections. The two schemes proposed are tested for random data transmission. In addition, the applicability of transmitting images on the optical channel model is studied and veried in dierent cases. Different types of compression schemes such as SVD, PCA and JPEG are studied and compared. Moreover, two schemes for image encryption: The double random phase encoding (DRPE) and optical scanning holography (OSH) are suggested to secure the image communication process. DRPE is a full encryption scheme and the OSH is a partial encryption scheme. Moreover, error correction coding is considered as a feasible approach for reliable image communication |