Modeling the Performance of Optical Modems in the DESERT Underwater Network Simulator

Signori, Alberto; Campagnaro, Filippo; Zorzi, Michele

doi:10.1109/ucomms.2018.8493196

Cited by 6 publications

(5 citation statements)

References 9 publications

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“…The need for high-speed communications in an underwater environment has pushed the realization of optical devices that can transmit data within short distances at a bit rate on the order of one or more Mbps (up to few Gbps at very short ranges, depending on the model and the water conditions). Indeed, unlike acoustic communications, optical communications are more suitable for ranges up to 100 m, especially in deep dark waters, and are not affected by multipath, shipping, and wind noise, as their performance mainly depends on water turbidity and sunlight noise [70]. In fact, high turbidity scatters and attenuates the optical field, whereas ambient light may become a significant source of noise, making transmissions close to the sea surface more difficult.…”

Section: Optical Communicationsmentioning

confidence: 99%

“…The performance of the BlueComm 200 optical modem was mapped in the form of lookup tables (LUTs), as presented in [70], by considering a raw bit rate of 5 Mbps and the use of a forward error correction (FEC) mechanism with 80% efficiency (as declared from the manufacturer); hence, the actual data rate was 4 Mbps. Although the modem performs best in a deep, dark water environment, where oil and gas pipelines are typically deployed, in our simulations, we considered the performance of the modem when used in the presence of external lighting sources, such as the light needed for recording video streams, that introduced an important source of noise to the receiver, however, without saturating the photomultiplier.…”

Section: Optical Modem Simulatormentioning

confidence: 99%

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Wireless Remote Control for Underwater Vehicles

Campagnaro

Signori

Zorzi

2020

JMSE

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Nowadays, the increasing availability of commercial off-the-shelf underwater acoustic and non-acoustic (e.g., optical and electromagnetic) modems that can be employed for both short-range broadband and long-range low-rate communication, the increasing level of autonomy of underwater vehicles, and the refinement of their underwater navigation systems pave the way for several new applications, such as data muling from underwater sensor networks and the transmission of real-time video streams underwater. In addition, these new developments inspired many companies to start designing hybrid wireless-driven underwater vehicles specifically tailored for off-shore operations and that are able to behave either as remotely operated vehicles (ROVs) or as autonomous underwater vehicles (AUVs), depending on both the type of mission they are required to perform and the limitations imposed by underwater communication channels. In this paper, we evaluate the actual quality of service (QoS) achievable with an underwater wireless-piloted vehicle, addressing the realistic aspects found in the underwater domain, first reviewing the current state-of-the-art of communication technologies and then proposing the list of application streams needed for control of the underwater vehicle, grouping them in different working modes according to the level of autonomy required by the off-shore mission. The proposed system is finally evaluated by employing the DESERT Underwater simulation framework by specifically analyzing the QoS that can be provided to each application stream when using a multimodal underwater communication system specifically designed to support different traffic-based QoSs. Both the analysis and the results show that changes in the underwater environment have a strong impact on the range and on the stability of the communication link.

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Section: Optical Communicationsmentioning

confidence: 99%

Section: Optical Modem Simulatormentioning

confidence: 99%

Wireless Remote Control for Underwater Vehicles

Campagnaro

Signori

Zorzi

2020

JMSE

Self Cite

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“…Further physical verification of channel models should be conducted using data collected from realistic environment for channel estimation. The data can then be used for developing robust UWOC system through simulation [10], and for As the physical layer technologies are improved, development among the Open Systems Interconnection layers will soon be required, including data link layer (multiple access schemes and link configurations), network layer (routing protocols), transport layer (connectivity and reliability), and application layer. It is noteworthy that fully understanding the constraints of application layer is necessary to the design of lower layers [11].…”

Section: Underwater Wireless Optical Communications: Opportunity Chal...mentioning

confidence: 99%

Underwater wireless optical communications: Opportunity, challenges and future prospects commentary on “Recent progress in and perspectives of underwater wireless optical communication”

Ooi

Kong

2020

Progress in Quantum Electronics

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“…The port of Hamburg, indeed, is located on the Elbe river, where the water is typically very turbid and the river depth rarely exceeds 20 m (this statement is supported by the bathymetry used for our simulations, depicted in Figure 17b, and by the water turbidity measurements provided by the hydrography department of the port of Hamburg). Such environment is very challenging for optical communications [4,28,29]: for this reason the multimodal network used in this paper involves only acoustic technology. Specifically, a low power short range acoustic link is employed to transmit data from the nodes to the AUV, and a high rate acoustic modem is used to upload all the collected data from the AUV to the sink.…”

Section: State Of the Artmentioning

confidence: 99%

“…Similarly, also underwater optical communications are used only for very short range links, as they are affected by turbidity and solar noise. Usually, they are employed only in deep water scenarios, where the turbidity is typically very low and the surrounding light noise is negligible [4]. Acoustic communication systems, instead, can be used for long range communications; they have been developed for considerable time now, and have reached a remarkable level of maturity [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Data Gathering from a Multimodal Dense Underwater Acoustic Sensor Network Deployed in Shallow Fresh Water Scenarios

Signori

Campagnaro

Steinmetz

et al. 2019

JSAN

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The Robotic Vessels as-a-Service (RoboVaaS) project intends to exploit the most advanced communication and marine vehicle technologies to revolutionize shipping and near-shore operations, offering on-demand and cost-effective robotic-aided services. In particular, the RoboVaaS vision includes a ship hull inspection service, a quay walls inspection service, an antigrounding service, and an environmental and bathymetry data collection service. In this paper, we present a study of the underwater environmental data collection service, performed by a low-cost autonomous vehicle equipped with both a commercial modem and a very low-cost acoustic modem prototype, the smartPORT Acoustic Underwater Modem (AHOI). The vehicle mules the data from a network of low cost submerged acoustic sensor nodes to a surface sink. To this end, an underwater acoustic network composed by both static and moving nodes has been implemented and simulated with the DESERT Underwater Framework, where the performance of the AHOI modem has been mapped in the form of lookup tables. The performance of the AHOI modem has been measured near the Port of Hamburg, where the RoboVaaS concept will be demonstrated with a real field evaluation. The transmission with the commercial modem, instead, has been simulated with the Bellhop ray tracer thanks to the World Ocean Simulation System (WOSS), by considering both the bathymetry and the sound speed profile of the Port of Hamburg. The set up of the polling-based MAC protocol parameters, such as the maximum backoff time of the sensor nodes, appears to be crucial for the network performance, in particular for the low-cost low-rate modems. In this work, to tune the maximum backoff time during the data collection mission, an adaptive mechanism has been implemented. Specifically, the maximum backoff time is updated based on the network density. This adaptive mechanism results in an 8% improvement of the network throughput.

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Modeling the Performance of Optical Modems in the DESERT Underwater Network Simulator

Cited by 6 publications

References 9 publications

Wireless Remote Control for Underwater Vehicles

Wireless Remote Control for Underwater Vehicles

Underwater wireless optical communications: Opportunity, challenges and future prospects commentary on “Recent progress in and perspectives of underwater wireless optical communication”

Data Gathering from a Multimodal Dense Underwater Acoustic Sensor Network Deployed in Shallow Fresh Water Scenarios

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