Hamzeh Beyranvand

Matin Rafiei Forooshani, Farhad Arpanaei, Hamzeh Beyranvand et al.

This paper introduces SixGman, an open-source optical network planning tool for evaluating access-metro-core aggregation network architectures. The framework integrates traffic generation, dual-homed routing, Quality of Transmission (QoT) estimation, spectrum and fiber assignment, techno-economic analysis, energy consumption evaluation, and visualization capabilities. Its modular design, based on standardized interfaces and clearly defined functions, enables flexible, transparent, and reproducible network simulations. SixGman is applied to the Telefónica MAN157 metro-urban topology, composed of 157 optical nodes, 220 links, and four hierarchical layers (HL1-HL4), to compare a conventional full hierarchical architecture with an HL3-bypassed architecture where electrical aggregation at HL3 nodes is removed. The analysis includes traffic distribution, IP router utilization, link congestion, latency, Total Cost of Ownership (TCO), and energy consumption. Results show that HL3 bypassing improves traffic distribution, reduces optical and electrical resource usage, lowers end-to-end latency, and decreases both capital and operational expenditures. Compared to the full hierarchical architecture, the HL3-bypassed scenario achieves reductions of up to 17.5% in TCO and 29.1% in cumulative energy consumption. These results demonstrate the potential of SixGman as a flexible planning platform for cost- and energy-efficient optical network design.

Matin Rafiei Forooshani, Farhad Arpanaei, Hamzeh Beyranvand et al.

This study compares transponder-based, Point-to-Point, and DSCM-based Point-to-Multipoint (PtMP) access-metro architectures. Findings demonstrate that PtMP IPoWDM significantly optimizes efficiency across diverse geotypes, slashing CAPEX by 92.0% and power by 99.2% compared to the traditional benchmark over a ten-year horizon.

Aboozar Heydaribeni, Hamzeh Beyranvand, Sahar Eslami

This paper presents a dual-hop hybrid framework that integrates a free-space optical (FSO)/RIS-aided radio frequency (RF) link operating under a hard-switching protocol as the first hop, and an optical reconfigurable intelligent surface (O-RIS)-assisted underwater wireless optical communication (UWOC) link as the second hop. To capture realistic underwater dynamics, the Oceanic Turbulence Optical Power Spectrum (OTOPS) is employed for accurate turbulence modeling. For efficient O-RIS phase control, deep reinforcement learning (DRL) algorithms, specifically the Deep Deterministic Policy Gradient (DDPG) and Twin Delayed DDPG (TD3), have been developed to optimize the phase shifts of O-RIS elements. Simulation results demonstrate that the proposed system substantially improves outage probability and channel capacity, with TD3 achieving superior robustness and adaptability. These findings highlight the DRL-enabled O-RIS as a promising approach for achieving reliable and high-capacity 6G cross-domain UWOC networks.