In this paper, we propose a lightwave power transfer-enabled underwater optical integrated sensing and communication (O-ISAC) system, where an access point (AP) mounted on a seasurface ship transmits lightwave signals to two nodes, namely ($i$) a seabed sensor that harvests energy and transmits uplink information to the AP, and ($ii$) a sensing target whose position is estimated by the AP using an array of pinhole cameras. To capture practical deployment conditions, the ship attitude variation is modeled through its roll, pitch, and yaw angles, each following a Gaussian distribution under low-to-moderate sea states. Closed-form approximations are derived for the mean squared error (MSE) of target localization and the achievable uplink data rate. Analytical and simulation results demonstrate excellent agreement, validating the proposed models and derived expressions, while revealing the fundamental communication-sensing tradeoff in the O-ISAC system. The results further provide valuable design insights, including the optimal camera placement on the ship to minimize localization error, achieving a minimum MSE of $10^{-2}$ $\text{m}^2$ with multiple cameras under roll, pitch, and yaw angle variation of $10^{\circ}$, and the optimal harvest-use ratio of $0.55$ for the considered setup.

This paper presents a comprehensive analysis of the information-energy capacity region for simultaneous lightwave information and power transfer (SLIPT) systems over lognormal fading channels. Unlike conventional studies that primarily focus on additive white Gaussian noise channels, we study the complex impact of lognormal fading, which is prevalent in optical wireless communication systems such as underwater and atmospheric channels. By applying the Smith’s framework to these channels, we demonstrate that the optimal input distribution is discrete, characterized by a finite number of mass points. We further investigate the properties of these mass points, especially at the transition points, to reveal critical insights into the rate-power trade-off inherent in SLIPT systems. Additionally, we introduce a novel cooperative information-energy capacity learning framework, leveraging generative adversarial networks, to effectively estimate and optimize the information-energy capacity region under practical constraints. Numerical results validate our theoretical findings, illustrating the significant influence of channel fading on system performance. The insights and methodologies presented in this work provide a solid foundation for the design and optimization of future SLIPT systems operating in challenging environments.

In this paper, we consider a tunable liquid convex lens-assisted imaging receiver for indoor multiple-input multiple-output (MIMO) visible light communication (VLC) systems. In contrast to existing MIMO VLC receivers that rely on fixed optical lenses, the proposed receiver leverages the additional degrees of freedom offered by liquid lenses via adjusting both focal length and orientation angles of the lens. This capability facilitates the mitigation of spatial correlation between the channel gains, thereby enhancing the overall signal quality and leading to improved bit-error rate (BER) performance. We present an accurate channel model for the liquid lens-assisted VLC system by using three-dimensional geometry and geometric optics. To achieve optimal performance under practical conditions such as random receiver orientation and user mobility, optimization of both focal length and orientation angles of the lens are required. To this end, driven by the fact that channel models are mathematically complex, we present two optimization schemes including a blockwise machine learning (ML) architecture that includes convolution layers to extract spatial features from the received signal, long-short term memory layers to predict the user position and orientation, and fully connected layers to estimate the optimal lens parameters. Numerical results are presented to compare the performance of each scheme with conventional receivers. Results show that a significant BER improvement is achieved when liquid lenses and presented ML-based optimization approaches are used. Specifically, the BER can be improved from 6 × 10−2to 1.4 × 10−3at an average signal-to-noise ratio of 30 dB.

In this paper, we consider an indoor visible light communication (VLC) system with multiple "white" light emitting diodes serving to form overlapping wireless communication cells. In order to maintain seamless connectivity to mobile users, a handover procedure should be implemented. In particular, practical conditions such as blockages due to obstacles inside the room environment and the mobility of users can affect direct VLC connectivity. The use of reconfigurable intelligent surfaces (RISs) in optical wireless systems allows to exploit non-direct connectivity links, thus providing efficient communication links. In this paper, we present a proactive handover mechanism that exploits the presence of a RIS, in order to redirect the communication links in case of blockages. The proposed approach has been implemented both in hard and soft modes and assessed in terms of achievable data rate and handover latency for a user walking in a given reference room at different user speeds and blockage conditions. Our presented results and comparisons with conventional handover methods (i.e., without RIS) are helpful in showing the superiority of the presented algorithm.

In this paper, we study the fundamental limits of simultaneous lightwave information and power transfer (SLIPT) systems over channels with path loss and lognormal fading conditions. We consider a system with a single transmitter transferring information to a photodiode-based receiver as well as transferring energy to a photovoltaic cell receiver. In particular, we study the information-energy capacity region and the optimal input distribution under (a) peak-power and average-power constraints at the transmitter, and (b) the minimum harvest energy at the energy harvesting receiver. To this end, an expression for the transition probability distribution function of the lognormal channel is derived. By extending Smith's framework and using Hermite polynomial bases, we prove that the optimal input distribution is discrete with a finite number of mass points. Information-energy capacity region for SLIPT over lognormal channel conditions is illustrated and compared with the case of additive white Gaussian noise channel.

In this article, we consider a simultaneous lightwave information and power transfer-enabled indoor visible light/radio frequency (RF) hybrid communication system. In this system, several luminaries are mounted on the ceiling of a room and sensors receive lightwave power and information from luminaries. Each sensor harvests energy from lightwave signals and uses them for uplink communication using RF signals. In general, blockages due to the movement of humans are common in indoor systems which results in severe performance degradation. We consider blockages due to such human movements in our system. An optimization problem is formulated to maximize the uplink weighted sum rate considering uplink orthogonal multiple access (OMA) and non-OMA cases. To find the optimal beamforming matrix and time allocation parameters, a lightweight artificial neural network architecture is proposed. Our solution is capable of predicting the human blockages and accordingly optimizing the beamforming matrices and time allocation parameters leading to a near-optimal uplink sum rate. Specifically, up to 30% rate improvement is observed compared to zero-forcing beamforming when the number of blockages is more than five. Further, the use of NOMA for uplink results in up to 25% sum rate improvement.

In this paper, we consider a non-orthogonal multiple access (NOMA) underwater optical wireless communication system in which a full-duplex decode-and-forward relay is used to assist the far user with weak channel conditions. Full-duplex operation introduces interference to the near user with strong channel conditions and our model covers several practical assumptions such as imperfect interference cancellation and random receiver orientation at the near/far user. In particular, we derive the exact outage probability at the near user and far user valid for log-normal weak turbulence conditions. An accurate outage approximation for the near user is also derived in closed-form. The correctness of the analysis has been verified through simulation results where they both match closely. Moreover, the derived expressions are useful to investigate the impact of various system and channel parameters such as the access point/relay transmit power, node locations, strength of the residual interference and random receiver orientation at the near and far user. Our results reveal that the outage probability of the near user is more sensitive to receiver orientation errors as compared to the far user.