Optical packet switching (OPS) ring networks are emerging as promising solutions for future metropolitan area networks. Architectures utilizing tunable transmitters (TTs) and tunable receivers (TRs) deliver high performance but incur significant cost. Conversely, fixed transmitter–fixed receiver (FT–FR) systems provide cost benefits; however, conventional designs typically require W wavelength-specific FT–FR pairs, limiting scalability. This paper proposes a novel WDM-based dual-ring architecture that achieves low cost, high throughput, and scalability. A distributed MAC protocol enables efficient operation with a minimal number of FT–FR pairs. Through strategic wavelength assignment, nodes can either transmit directly to nearby destinations or relay packets through intermediate nodes to enable long-distance communication. Simulation results demonstrate that with only two FT–FR pairs, the proposed system achieves a throughput of 2.5, outperforming previous TT–TR-based designs with a throughput of 2.0. These findings highlight the proposed system’s superior efficiency, fairness, and cost-effectiveness.
This study introduces a comprehensive mathematical benchmarking framework and comparative performance evaluation of seven distinct orthogonal and quasi-orthogonal coding families designed for advanced multi-user optical wireless and quantum networks. To resolve the critical trade-off between maximizing subscriber capacity and minimizing multi-user co-channel interference, we systematically evaluate Optical Orthogonal Codes (OOCs), Self-Orthogonal Linear Codes, Geometric Orthogonal Codes (GOCs), Biorthogonal Wavelet Codes, Pseudo-Orthogonal Codes (POCs), Super-Orthogonal Convolutional Codes (SOCCs), and Quasi-Orthogonal Codes (QOCs). Utilizing a unified Python-based simulation ecosystem, we evaluate each scheme under standardized channel models using algebraic graph theory, finite field ring structures, and multi-objective meta-heuristic optimization pipelines. Empirical evaluations demonstrate that the localized neighbour difference mapping approach for ( n,ω ,1 )-OOCs reduces computational matrix generation complexity to an O( ω^2) boundary while compressing optoelectronic receiver decoding latency to a linear O(ω ) limit. Concurrently, self-orthogonal linear block codes derived from the adjacency matrices of distance-regular graphs Γ_280 and Γ_216 establish secure, zero-collision data links over fields of characteristic 2. Furthermore, firefly-tuned polyphase pseudo-orthogonal sequences successfully suppress worst-case cross-correlation peak sidelobe levels to − 21.169 dB, while adaptive SOCC trellis configurations consistently satisfy strict frame error rate limits under dense traffic loads. Ultimately, this comparative structural mapping provides network engineers with an authoritative, data-driven selection matrix to optimize physical-layer communication parameters based on real-time link budgets and subscriber requirements.
This paper investigates the performance of secure image transmission over free-space optical (FSO) communication systems employing image encryption and decryption techniques. The analysis considers different atmospheric turbulence conditions, including weak turbulence and moderate-to-strong turbulence, which are modeled using Log-normal and Gamma-Gamma statistical distributions, respectively. The effects of atmospheric attenuation, transmission distance, and turbulence-induced fading on the quality and reliability of image transmission are systematically evaluated. Prior to transmission, the input image is encrypted using an encryption algorithm designed to provide high randomness and security, achieving an entropy close to the ideal value of 8, while the corresponding encrypted image exhibits a PSNR of approximately 30 dB. At the receiver, the encrypted image is recovered through the corresponding decryption process and compared with the original image to assess the reconstruction quality. The overall performance of the proposed secure FSO communication system is evaluated using bit error rate (BER), peak signal-to-noise ratio (PSNR), entropy, and mean square error (MSE). The results provide insights into the combined effects of atmospheric turbulence and attenuation on the security and image reconstruction performance of FSO-based optical wireless communication systems.
Currently, analyses of the propagation performance of vector vortex beams (VVBs) underwater primarily focus on the impact of oceanic turbulence phase screens, lacking consideration of the optical intensity attenuation caused by absorption and scattering effects. Therefore, this study proposes a semi-classical hybrid simulation framework. By integrating statistical sampling techniques with wave optics evolution theory, this framework utilizes Monte Carlo path tracing to simulate the power loss induced by absorption and scattering. Simultaneously, it characterizes the wavefront distortion caused by oceanic turbulence through cumulative phase screens, thereby facilitating a comprehensive propagation analysis of VVBs. The results demonstrate that, when taking optical intensity attenuation into account, the complex oceanic environment–including water quality and turbulence strength–significantly affects the propagation characteristics of VVBs. These findings offer valuable insights for optimizing high-bit-rate communication links between autonomous underwater vehicles and enhancing the stability of data transmission in deep-sea sensor networks operating under complex and dynamic water conditions.
The advancement of contemporary optical communication networks relies on the creation of efficient and flexible photonic technologies. This paper presents novel physics-informed neural network (PINN) approaches for the development and enhancement of 3D circular-shaped photonic crystal add/drop filters (PCADFs), which are essential for frequency control. While existing 3D designs are often technically costly and imprecise, existing 2D photonic crystal designs typically suffer from limited wavelength selection, higher power losses, and reduced adaptability to dynamic networking needs. To address these challenges, the proposed PCADF system integrates PINNs to optimize structural parameters by incorporating Maxwell's equations and other physical principles influencing light transmission into an intelligence system. By leveraging PINN, which can model complex wave interactions within 3D circular photonic crystals (PCs), this research reduces computational costs and enhances the precision of wavelength-specific responses. The approach employs adaptive materials, waveguide design optimization, and simulated thermal methods to minimize crosstalk and improve the add/drop filter's efficiency. The primary objectives are to enable robust and precise wavelength selection, reduce signal distortion, and increase energy efficiency in optical networks. Modeling results reveal significant improvements, including enhanced wavelength isolation, lower insertion losses, and greater adaptability to varying operating conditions. This study underscores the potential of PINNs to merge computational science and artificial intelligence, setting a new standard in photonic device design. It offers an innovative pathway for next-generation optical communication technologies for novel applications in optical computing, high-speed data transmission, and advanced networked communications.
