With the promotion of the solid-state lighting industry, visible light communication (VLC) has attracted increasing interests these years. However, the blockage problems in VLC due to the nanoscale wavelength of the visible light are severe. In this letter, a VLC system deployed with the intelligent reflecting surface (IRS) is modeled under the point source assumption, where both line-of-sight and specular non-line-of-sight paths are considered. By introducing a discrete matrix, the resource allocation process is simplified into a binary programming problem, and then we propose a low-complexity algorithm to maximize the achievable sum rate. Moreover, numerical results demonstrate that IRS can improve the rate performance and ease blockage problems of VLC.

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.

In this letter, we present a novel hybrid intensity modulation and direct detection communication system, which integrates asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) and on-off keying (OOK) modulation schemes. First, the negative ACO-OFDM is proposed based on the conventional ACO-OFDM system to accommodate the on case with direct current in the OOK modulation, while the ACO-OFDM can match the off case in the OOK modulation. Therefore, the novel hybrid system combines the ACO-OFDM and OOK modulation schemes, while the signals can be recovered at the receiver to support the different qualities of service with high spectral efficiency and can be adapted to various receivers with different complexities. Simulation results are reported for the visible light channel and show that both the ACO-OFDM and OOK signals can be well recovered.

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.

This letter investigates physical layer security in intelligent reflecting surface (IRS)-aided VL communication (VLC). Under the point source assumption, we first elaborate the system model in the scenario with multiple legitimate users and one eavesdropper, where the secrecy rate maximization problem is transformed into an assignment problem by objective function approximation. Then, an iterative Kuhn-Munkres algorithm is proposed to optimize the transformed problem, and its computational complexity is in the second-order form of the numbers of IRS units and transmitters. Moreover, numerical simulations are carried out to verify the approximation performance and the VLC secrecy rate improvement by IRS.

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.