Photonic Network Communications最新文献

Efficient network management in optical backbone networks is essential to manage continuous traffic growth. To accommodate this growth, network operators need to upgrade their infrastructure at appropriate times. Given the cost constraint of upgrading the entire network at once, upgrading the network periodically in multiple batches is a more pragmatic approach to meet the growing demands. While multi-period, batch-upgrade strategies to increase network capacity from the conventional C band to C+L bands have been proposed, they did not consider so far the possibility to re-provision existing traffic. In this work, we investigate how to selectively re-provision connections from C band to L band during a batch upgrade. This is to ensure greater availability of C-band resources which can help to delay network upgrade and hence reduce upgrade cost, while limiting the number of disrupted connections in the network. This study proposes two re-provisioning strategies, namely, Budget-Based (BB) and Margin-Aware (MA) re-provisioning, which rely on the Quality of Transmission (QoT) of lightpaths. These strategies leverage the knowledge of Generalized Signal-to-Noise Ratio (GSNR) to choose which lightpaths to re-provision. We compare these strategies with a baseline distance-based strategy that uses path length to select and re-provision lightpaths. We also incorporate Machine Learning techniques for QoT estimation of lightpaths to reduce the computational time required for optical-path feasibility check. Numerical results show that, compared to distance-based strategy, BB and MA strategies reduce disruption by about 22% and 27%, respectively, in representative network topologies.

Given their widespread use, optical access networks are suitable as a practical infrastructure for mobile networks and services. The diverse range of services supported by mobile networks requires the implementation of slicing mechanisms that can manage resources across all associated network segments, from the mobile user to the core network. In this study, we present a fully operational and integrated 5G network deployment that caters to end-to-end slicing in next-generation access networks. We assess the impact of resource allocation mechanisms within the optical access network on the performance of a slice, particularly in terms of latency and jitter experienced by mobile users.

Multi-core fiber (MCF) based space-division multiplexed elastic optical networks (SDM-EON) is a promising technology to scale the capacity of optical transport networks. MCF-based SDM-EONs can potentially increase the network’s capacity with reduced cost and/or energy per bit. Crosstalk among the cores of MCF limits the efficient utilization of the available spectrum. Keeping the inter-core crosstalk below a threshold before establishing a new lightpath in the network is crucial. In this work, we have studied the impact of crosstalk while setting up flexible lightpaths in the MCF-based SDM-EON. Depending on the severity of inter-core crosstalk, we emphasize the importance of designing suitable resource allocation techniques, such as core selection, spectrum slot finding and crosstalk computation. In this work, we test the performance of various resource allocation algorithms in the presence of crosstalk. To circumvent the impact of crosstalk on the performance of MCF-based SDM-EONs, we propose two dynamic resource allocation algorithms, D-XT-Aware RMCSA and CR-FA-XT-Aware RMCSA. Extensive simulations are performed on three realistic network topologies to study the performance of benchmark and proposed algorithms under dynamic traffic conditions. Based on simulation results, we suggest RMCSA techniques suitable against the severity of inter-core crosstalk for MCF-based SDM-EONs.

Quantum computing has emerged as a useful resource for winning random games. Monty Hall problem is one such game, where the powers of quantum mechanics can be utilized for winning the prize. Our paper depicts this problem as a two-player game, where the two players, i.e., the host and the participant share an entangled quantum state. The entangled state is closely knit with the position of the prize containing door, and the decision of the player i.e., either switch or stay from his initial choice of door. The two players are part of one team as they share a quantum communication channel among them by sharing the entangled state as a quantum resource. This enables them to share secret information about the position of the price as well as the strategy to opt for winning the game. The article shows a unique way of utilizing three different type of entangled states, three-qubit symmetric W state, three-qubit (chi ) state, and five-qubit highly entangled Brown state. Further, the effectiveness of each quantum state as a source of communication in disguise is also compared. All the entangled states under study assure winning the price by the participant. However, each quantum state has different entanglement degree and offer varied merits as per the game setting.

In this paper, we investigate the performance of the novel one-bit control intelligent reflecting surface (IRS)-assisted mixed free-space optical (FSO)-radio frequency (RF) communication system, where an IRS is utilized over the RF hop to empower the end-to-end system performance. The FSO link is assumed to be affected by path loss, nonzero boresight pointing error, and atmospheric turbulence, which is modeled by generalized Malaga ((mathcal {M}))-distribution, whereas the multipath fading in RF link is modeled by Nakagami-m distribution. In particular, unified closed-form expressions for the outage probability (OP), bit-error-rate (BER), and ergodic capacity (EC) are derived for optical heterodyne detection (OHD) and intensity modulation with direct detection (IMDD) techniques. We also derive the achievable diversity order of the considered IRS-assisted system by obtaining the asymptotic OP and asymptotic BER expressions. In addition, we derive the asymptotic EC of the considered system. The numerical results show that the proposed IRS-assisted system significantly outperforms the conventional mixed FSO-RF system without IRS. Moreover, the impact of the number of reflecting elements, practical reflection amplitude, and controlling mechanism at the IRS is studied on the system performances.

In this paper, an all optical 4–2 encoder based on triangular lattice Photonic Crystal structure is proposed. The proposed structure consists of three micro-cavity resonators placed next to each other, resonates at the operating wavelength of 1550 nm to perform the encoder logical operation. The normalized output power for ON state is above 28%, and OFF state is below 0.9%. The minimum time delay and the bit rate of the proposed encoder are about 800 fs and 1.25 Tb/s, respectively. The total footprint of the proposed encoder is around 125 µm².

With the increasing bandwidth requirements in smart cities, high-capacity optical networks featuring ultrahigh bandwidths have become a necessity. The currently existing static and dynamic optical networks cannot efficiently optimize network resources and do not support intelligent decision making for smart cities, rendering them energy inefficient. The software-defined networking (SDN) controller in these networks also requires intelligent algorithms that can optimize network resources based on bandwidth requirements. We have designed a novel SDN-controlled dynamically reconfigurable time division multiplexing and dense wavelength-division multiplexing-based optical network for smart cities, which maximizes the utilization of network resources, making it energy efficient. To further empower the decision-making capabilities of the SDN controller, three novel algorithms are proposed: inter-application wavelength redirection with ROADM, dynamic load balancing, and bandwidth selection with resource allocation based on the different bandwidth requirements of primary and secondary applications. These algorithms sense the free bandwidth in primary applications and then assign this free bandwidth to secondary applications accordingly. The proposed SDN controller determines the best algorithm that optimally utilizes the network resources and routes the traffic through it. The performance of the designed optical network for a smart city is analyzed in terms of different performance parameters such as the bandwidth satisfaction rate, timing diagrams, eye diagrams, bit error rate, and quality factor. The proposed algorithms prove instrumental in the more efficient utilization of network resources, ensuring the maintenance of the required quality of service. This holistic proposed system addresses the unique challenges posed by smart cities, emphasizing energy efficiency and intelligent decision-making within the dynamic landscape of high-capacity optical networks.