Capacity Characterization Analysis of Optical Intelligent Reflecting Surface Assisted MISO VLC

Abstract

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.