A Reinforcement-Learning-Based Beam Adaptation for Underwater Optical Wireless Communications

Romdhane, Imene; Kaddoum, Georges

doi:10.1109/jiot.2022.3173211

Cited by 24 publications

(7 citation statements)

References 25 publications

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“…Their results demonstrated a significant reduction in power distribution variance with the PSO layout, indicating consistent emission uniformity across the water classifications [ 7 ]. In addition to this, to maintain consistent alignment, Romdhane and Kaddoum proposed a novel beam adaptation algorithm for UOWC receivers based on artificial intelligence reinforcement learning to optimize beamwidth and orientation in different water types for point-to-point line-of-sight (P2P-LOS) communication [ 8 ]. They compared the performance of Q-learning and State-Action-Reward-State-Action (SARSA) algorithms, with SARSA converging more quickly.…”

Section: Literature Reviewmentioning

confidence: 99%

Geometric Implications of Photodiode Arrays on Received Power Distribution in Mobile Underwater Optical Wireless Communication

Govinda Waduge,

Seet,

Vopel

2024

Sensors

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Underwater optical wireless communication (UOWC) has gained interest in recent years with the introduction of autonomous and remotely operated mobile systems in blue economic ventures such as offshore food production and energy generation. Here, we devised a model for estimating the received power distribution of diffused line-of-sight mobile optical links, accommodating irregular intensity distributions beyond the beam-spread angle of the emitter. We then used this model to conduct a spatial analysis investigating the parametric influence of the placement, orientation, and angular spread of photodiodes in array-based receivers on the mobile UOWC links in different Jerlov seawater types. It revealed that flat arrays were best for links where strict alignment could be maintained, whereas curved arrays performed better spatially but were not always optimal. Furthermore, utilizing two or more spectrally distinct wavelengths and more bandwidth-efficient modulation may be preferred for received-signal intensity-based localization and improving link range in clearer oceans, respectively. Considering the geometric implications of the array of receiver photodiodes for mobile UOWCs, we recommend the use of dynamically shape-shifting array geometries.

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Section: Literature Reviewmentioning

confidence: 99%

Geometric Implications of Photodiode Arrays on Received Power Distribution in Mobile Underwater Optical Wireless Communication

Govinda Waduge,

Seet,

Vopel

2024

Sensors

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“…Considering this challenge, a reinforcement learning-based solution for a P2P UOWC system has been recently proposed in [338] to solve PAT problems by defining a beam adaptation method that includes both beamwidth and beam orientation adaptation to improve the link quality while maintaining a high success rate. Extended FoV photonic receivers can also ease the PAT requirements for UOWC links, such as those based on scintillating fibers [339].…”

Section: B Technical Challenges Of Owc-iowt Networkingmentioning

confidence: 99%

A Top-Down Survey on Optical Wireless Communications for the Internet of Things

Çelik

Romdhane²,

Kaddoum³

2023

IEEE Commun. Surv. Tutorials

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The Internet of Things (IoT) is a transformative technology marking the beginning of a new era where physical, biological, and digital worlds are integrated by connecting a plethora of uniquely identifiable smart objects. Although the Internet of terrestrial things (IoTT) has been at the center of our IoT perception, it has been recently extended to different environments, such as the Internet of underWater things (IoWT), the Internet of Biomedical things (IoBT), and Internet of un-derGround things (IoGT). Even though radio frequency (RF) based wireless networks are regarded as the default means of connectivity, they are not always the best option due to the limited spectrum, interference limitations caused by the everincreasing number of devices, and severe propagation loss in transmission mediums other than air. As a remedy, optical wireless communication (OWC) technologies can complement, replace, or co-exist with audio and radio wave-based wireless systems to improve overall network performance. To this aim, this paper reveals the full potential of OWC-based IoT networks by providing a top-down survey of four main IoT domains: IoTT, IoWT, IoBT, and IoGT. Each domain is covered by a dedicated and self-contained section that starts with a comparative analysis, explains how OWC can be hybridized with existing wireless technologies, points out potential OWC applications fitting best the related IoT domain, and discusses open communication and networking research problems. More importantly, instead of presenting a visionary OWC-IoT framework, the survey discloses that OWC-IoT has become a reality by emphasizing ongoing proof-of-concept prototyping efforts and available commercial off-the-shelf (COTS) OWC-IoT products.

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“…Particularly for the fiber-optics based fronthaul assisted by machine learning, one important challenge is related to the need for representative data-set for training neural networks. Researches have pointed out reinforcement learning techniques, which do not demand a previously generated data set, since the reinforcement learning model is trained on the fly [146]. In parallel, recent mobile communication systems have embraced a plurality of new services and applications, which increase the demand for computing processing and storage capabilities.…”

Section: B Fiber-optics-based Fronthaul Assisted By Machine Learningmentioning

confidence: 99%

Wireless and Optical Convergent Access Technologies Toward 6G

Filgueiras¹,

Lima

Cunha

et al. 2023

IEEE Access

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The sixth generation of mobile communication (6G) systems is recently rising a lot of interest, introducing new futuristic and challenging use cases that will demand much more than just communications to become a reality. Higher throughput, lower latencies, higher number of connections will push the requirement of the future mobile networks to a new level, but also sensing, positioning and imaging will play an important role in the new foreseen use cases. The integration of techniques developed for wireless communications with those conceived for optical links will be essential to provide the infrastructure for the 6G networks. In this context, this paper presents a review on wireless and optical convergent access solutions towards the 6G systems. The manuscript brings the use cases, requirements and enablers for 6G networks including a discussion about the state-of-the-art on THz and sub-THz communications, wireless and optical convergence, visible light communication, integrated and free-space optics, new antenna designs, powerover-fiber deployments and the use of machine learning in the physical layer of future networks. By reviewing the most relevant contributions available in the literature for wireless and optical communications and presenting their main contributions, this paper clearly shows that, more than a technological trend, the convergence of wireless and optical technologies is a fundamental step towards the development of the 6G network infrastructure.

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A Reinforcement-Learning-Based Beam Adaptation for Underwater Optical Wireless Communications

Cited by 24 publications

References 25 publications

Geometric Implications of Photodiode Arrays on Received Power Distribution in Mobile Underwater Optical Wireless Communication

Geometric Implications of Photodiode Arrays on Received Power Distribution in Mobile Underwater Optical Wireless Communication

A Top-Down Survey on Optical Wireless Communications for the Internet of Things

Wireless and Optical Convergent Access Technologies Toward 6G

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