Optical intelligent reflecting surface (OIRS) is a promising technology in visible light communications (VLCs), which can help VLC overcome the shortcoming of being susceptible to occlusion. It is shown that OIRS has many advantages for nonorthogonal multiple access (NOMA)-based VLC due to its ability to reconfigure optical wireless channels. In this article, we propose an effective OIRS-aided physical layer security (PLS) scheme for NOMA-based VLC networks against multiple eavesdroppers (Eves). By exploiting artificial noise (AN) to jam Eves, the maximization problem of the minimum achievable secrecy data rate is investigated, subject to successive interference cancellation (SIC) decoding conditions and OIRS constraints. Specifically, the original problem is decomposed into the power allocation and OIRS configuration subproblems by a block coordinate descent (BCD) algorithm. Moreover, the semi-definite relaxation and successive convex approximation are employed to solve the subproblems, after which a stochastic probability assignment method is adopted for the integer OIRS constraint. Finally, simulation results demonstrate that AN can enhance the system performance in most scenarios, and the minimum achievable secrecy data rate can be significantly improved by the proposed algorithm, demonstrating the potential of OIRS for enhancing PLS in optical wireless communications.

Non-orthogonal multiple access (NOMA)-based visible light communication (VLC) is considered a promising technique for next generation high-speed wireless communications. The emerging optical intelligent reflecting surface (OIRS) offers significant benefits to the NOMA-based VLC, since it can mitigate signal blockage issues of VLC and improve its performance by manipulating channel qualities of users. This paper investigates the enhancement of OIRS to the NOMA-based multi-cell VLC system and explores the resource allocation problem for the energy efficiency (EE) maximization. To this end, the channel gains of the system are discussed, considering both the line-of-sight and OIRS-reflected paths. Then, the system model of NOMA-based VLC is established and the optimization problem is formulated to maximize the overall EE of the system. Next, the original optimization problem is decomposed into three sub-problems, which are solved by the proposed algorithms iteratively. Moreover, the simulation results demonstrate the convergence of the proposed algorithm and the enhancement in EE achieved by OIRS, as well as the influence of key parameters on the system performance, which can offer insights on resource allocation for NOMA-based VLC systems with OIRS.

Optical intelligent reflecting surface (OIRS) has attracted increasing attention due to its capability of overcoming signal blockages in visible light communication (VLC), an emerging technology for the next-generation advanced transceivers. However, current works on OIRS predominantly assume known channel state information (CSI), while its estimation problem has not been studied yet. To bridge such a gap, this paper proposes a new and customized OIRS channel estimation protocol with joint space-time sampling under the alignment-based OIRS channel model. First, we unveil the spatial and temporal coherence characteristics and derive OIRS coherence distance and coherence time in closed form. Next, to achieve dynamic beam alignment for pilot transmission within the coherence time, we propose to tune the rotation angles of the OIRS reflecting elements following a geometric optics-based non-uniform codebook. Then, given the beam alignment within the considered coherence time, a sequential OIRS channel estimation method is proposed, where the OIRS is divided into multiple subarrays based on the coherence distance. The CSI for each subarray is estimated sequentially, followed by a space-time interpolation to retrieve full CSI for other non-aligned transceiver antennas. Numerical results validate our theoretical analyses and demonstrate the efficacy of the proposed OIRS channel estimation protocol as compared to benchmark schemes.

Optical intelligent reflecting surface (OIRS) has been considered a promising technology for visible light communication (VLC) by constructing visual line-of-sight propagation paths to address the signal blockage issue. However, the existing works on OIRSs are mostly based on perfect channel state information (CSI), whose acquisition appears to be challenging due to the passive nature of the OIRS. To tackle this challenge, this paper proposes a customized channel estimation algorithm for OIRSs. Specifically, we first unveil the OIRS spatial coherence characteristics and derive the coherence distance in closed form. Based on this property, a spatial sampling-based algorithm is proposed to estimate the OIRS-reflected channel, by dividing the OIRS into multiple subarrays based on the coherence distance and sequentially estimating their associated CSI, followed by an interpolation to retrieve the full CSI. Simulation results validate the derived OIRS spatial coherence and demonstrate the efficacy of the proposed OIRS channel estimation algorithm.

Considering that optical intelligent reflecting surface (OIRS) can change the optical channel, the enhancement performance of OIRS on the energy efficiency (EE) of the non-orthogonal multiple access (NOMA)-based visible light communication (VLC) system is investigated. Specifically, a multi-cell VLC system is modelled with both line-of-sight (LoS) and OIRS-reflected paths, and then the problem is formulated to optimize the OIRS configuration and power allocation for the maximization of the overall EE while adhering to various constraints. Moreover, the original task is decomposed into two sub-problems, and is solved iteratively by the proposed algorithm. In addition, the convergence of the proposed algorithm and enhancement in EE achieved by OIRS are illustrated by simulation results, which offer beneficial insights on resource allocation for the NOMAbased VLC systems with OIRS.

The promising visible light communication (VLC) technology, which performs superior for Internet of Things (IoT) networks, can alleviate the spectrum congestion of current radio frequency communications. To overcome the drawbacks of VLC such as blockages and high path loss, we propose a multiple-input single-output (MISO) VLC system equipped with optical intelligent reflecting surface (OIRS), to maximize the asymptotic capacity in the high signal-to-noise-ratio regime. Specifically, the characteristics of the OIRS-reflected channel are discussed for the developed OIRS-assisted MISO VLC system, based on which the OIRS optimization can be transformed into an association problem between the OIRS reflecting elements and the transmitter antennas. Next, considering different emission power on antennas, the capacity lower and upper bounds are derived for three different cases and the asymptotic capacities are obtained accordingly, thus giving rise to the objective function of the capacity maximization problem. To solve this problem, we propose a priori-assisted alternating optimization algorithm to jointly optimize the OIRS element alignment and transmitter emission power, which not only can achieve the globally optimal result but also has a low complexity since the solution to each subproblem is given in closed form. Finally, extensive numerical results are provided to show the performance of the proposed algorithm and offer beneficial insights for the design of the proposed OIRS-assisted MISO VLC.

Although the multi-antenna or so-called multiple-input multiple-output (MIMO) transmission is an enabling technology for past generations of wireless communication systems, its application to visible light communication (VLC) still faces a critical challenge due to the strong spatial correlation of VLC channels, which makes it difficult to achieve sufficient spatial multiplexing gain. This paper proposes to use optical intelligent reflecting surfaces (OIRS) to tackle this challenge. Firstly, we characterize the extremely near-field channel condition in the optical frequency range and reveal a peculiar “inter-element interference (IEI) free” property of the OIRS-reflected channel, where the OIRS reflecting elements can be individually configured to align with one pair of transmitter and receiver antennas without causing interference to each other. Next, we characterize the OIRS-assisted MIMO VLC capacities under different power constraints at the transmitter antennas, and then proceed to maximize them by jointly optimizing the OIRS element alignment and transmitter emission power. In particular, we propose two algorithms for the OIRS optimization, namely, location-aided interior-point algorithm and log-det-based alternating optimization algorithm, to balance the performance versus complexity trade-off; while the optimal transmitter emission power is derived in closed form. Numerical results are provided to validate the capacity improvement of OIRS-assisted MIMO VLC against the VLC without OIRS and demonstrate the superior performance of the proposed algorithms compared to baseline schemes.

Due to the wide and license-free bandwidth, visible light communication (VLC) functions as a potential technology to meet the exponentially expanding traffic demands in wireless communications. However, the sensitivity to obstacles and high-path loss are the key issues that practical VLC systems must carefully deal with. In this article, the utilization of optical intelligent reflecting surface (OIRS) array in VLC is considered to create additional light propagation paths, thereby achieving a remarkable performance gain. In the OIRS-assisted VLC system, though the power of the signal at receiver can be increased, the resource allocation is relatively complex. Besides, the OIRS also causes time delays among signals received via various propagation paths, which is usually overlooked in existing works. To overcome these issues, the OIRS-assisted VLC system is interpreted as an autoencoder (AE), named OIRS-AE, whose architecture is enhanced according to both the model-driven and data-driven perspectives. By this way, the processing modules at the transmitter, OIRS, and receiver, including the corresponding encoding, resource management, and decoding schemes, can be simultaneously optimized, which is expected to achieve more reliable communication. Moreover, the impact of the OIRS-induced time delay spread on system performance is explored under various situations. The simulation results show that the proposed OIRS-AE can outperform the traditional OIRS-assisted VLC systems in terms of bit error rate performance.

With the capability of reconfiguring the wireless electromagnetic environment, intelligent reflecting surface (IRS) becomes a new paradigm for designing future wireless communication systems. In this paper, we consider optical IRS for improving the performance of visible light communication (VLC) under a multiple-input and multiple-output (MIMO) setting, where the mean square error (MSE) of the IRS-aided MIMO VLC is minimized by jointly designing the IRS and transceiver signal processing. To this end, the MIMO channel gains of the IRS-aided VLC are first derived under the point source assumption, based on which the MSE minimization problem is formulated subject to the emission power constraints and the IRS configuration constraints. Next, we propose an alternating optimization algorithm, which decomposes the original problem into three subproblems, to iteratively optimize the IRS configuration, the precoding and detection matrices for minimizing the MSE. Moreover, theoretical analysis on the performance of the proposed algorithm in high and low signal-to-noise ratio (SNR) regimes is investigated, revealing that the joint optimization process can be simplified in such special cases, and the algorithm’s convergence property and computational complexity are also discussed. Finally, numerical results show that IRS-aided schemes significantly reduce the MSE as compared to their counterparts without IRS, and the proposed algorithm outperforms other baseline schemes.

Though visible light communication (VLC) is a significant supplement to current communication technologies, disadvantages such as the sensitivity to obstacles limit its development and commercialization. As a revolutionizing technology, intelligent reflecting surface (IRS) offers an ability to reconfigure the wireless environment dynamically and passively, which is considered beneficial to improve the performance of VLC. This paper devotes to investigating the effect of VLC IRS and putting forward a joint resource management method for an instantaneous IRS-aided VLC system. To this end, the line-of-sight (LoS) and non-LoS channel gains are first discussed under the point source assumption, after which the system model is established and the optimization problem is formulated. Then, the frozen variable algorithm and minorization-maximization algorithm are proposed to iteratively maximize the overall spectral efficiency (SE), and detailed discussions on the weak/severe interference cases and computational complexity analysis are carried out. Moreover, numerical results are provided to show the improvement of SE and the effects of the proposed algorithms, which offers beneficial insights on joint resource management of IRS-aided VLC.