Machine Learning Applications for Short Reach Optical Communication

With the rapid development of optical communication systems, more advanced techniques conventionally used in long-haul transmissions have gradually entered systems covering shorter distances below 100 km, where higher-speed connections are required in various applications, such as the optical access networks, inter- and intra-data center interconnects, mobile fronthaul, and in-building and indoor communications. One of the techniques that has attracted intensive interests in short-reach optical communications is machine learning (ML). Due to its robust problem-solving, decision-making, and pattern recognition capabilities, ML techniques have become an essential solution for many challenging aspects. In particular, taking advantage of their high accuracy, adaptability, and implementation efficiency, ML has been widely studied in short-reach optical communications for optical performance monitoring (OPM), modulation format identification (MFI), signal processing and in-building/indoor optical wireless communications. Compared with long-reach communications, the ML techniques used in short-reach communications have more stringent complexity and cost requirements, and also need to be more sensitive. In this paper, a comprehensive review of various ML methods and their applications in short-reach optical communications are presented and discussed, focusing on existing and potential advantages, limitations and prospective trends.

State-of-the art and perspectives of underwater optical wireless communications

In scientific, military, and industrial sectors, the development of robust and efficient submarine wireless communication links is of enormous interest. Underwater wireless communications can be carried out through acoustic, radio frequency (RF), and optical waves. Underwater optical communication is not a new idea, but it has recently been considered because seawater exhibits a window of reduced absorption both in the visible spectrum and long-wavelength UV light (UV-A). Compared to its bandwidth limited acoustic counterpart, underwater optical wireless communications (UOWCs) can support higher data rates at low latency levels. Underwater wireless communication networks are important in ocean exploration, military tactical operations, environmental and water pollution monitoring. Anyway, given the rapid development of UOWC technology, documents are still needed showing the state of the art and the progress made by the most current research. This paper aims to examine current technologies, and those potentially available soon, for Underwater Optical Wireless Communication and to propose a new perspective using UV-A radiation.

On the Outage Capacity of Transdermal Optical Wireless Links with Stochastic Spatial Jitter and Skin-Induced Attenuation

The tremendous development of both optical wireless communications (OWC) and implantable medical devices (IMDs) has recently enabled the establishment of transdermal optical wireless (TOW) links that utilize light waves to transfer information inside the living body to the outside world and conversely. Indeed, numerous emerging medical applications such as cortical recording and telemetry with cochlear implants require extremely high data rates along with low power consumption that only this new technology could accommodate. Thus, in this paper, a typical TOW link is investigated in terms of outage capacity which is a critical performance metric that has so far not been evaluated for such wireless systems in the open technical literature. More precisely, an outage capacity analysis is performed considering both skin-induced attenuation and stochastic spatial jitter, i.e., pointing error effects. Analytical expressions and results for the outage capacity are derived for a variety of skin channel conditions along with varying stochastic pointing errors which demonstrate the feasibility of this cross-field cooperation. Lastly, the corresponding simulation outcomes further validate our suggestions.

Channel Modeling for In-body Optical Wireless Communications

Next generation in-to-out-of body biomedical applications have adopted optical wireless communications (OWCs). However, by delving into the published literature, a gap is recognised in modeling the in-to-out-of channel, since most published contributions neglect the particularities of different type of tissues. Towards this direction, in this paper we present a novel pathloss and scattering models for in-to-out-of OWC links. Specifically, we derive extract analytical expressions that accurately describe the absorption of the five main tissues’ constituents, namely fat, water, melanin, oxygenated and de-oxygenated blood. Moreover, we formulate a model for the calculation of the absorption coefficient of any generic biological tissue. Next, by incorporating the impact of scattering in the aforementioned model we formulate the complete pathloss model. The developed theoretical framework is verified by means of comparisons between the estimated pathloss and experimental measurements from independent research works. Finally, we illustrate the accuracy of the theoretical framework in estimating the optical properties of any generic tissue based on its constitution. The extracted channel model is capable of boosting the design of optimized communication protocols for a plethora of biomedical applications.