The present work describes the development of an organic photodiode (OPD) receiver for high-speed optical wireless communication. To determine the optimal communication design, two different types of photoelectric conversion layers, bulk heterojunction (BHJ) and planar heterojunction (PHJ), are compared. The BHJ-OPD device has a −3 dB bandwidth of 0.65 MHz (at zero bias) and a maximum of 1.4 MHz (at −4 V bias). A 150 Mbps single-channel visible light communication (VLC) data rate using this device by combining preequalization and machine learning (ML)-based digital signal processing (DSP) is demonstrated. To the best of the authors' knowledge, this is the highest data rate ever achieved on an OPD-based VLC system by a factor of 40 over the previous fastest reported. Additionally, the proposed OPD receiver achieves orders of magnitude higher spectral efficiency than the previously reported organic photovoltaic (OPV)-based receivers.

Vehicle-to-vehicle communication based on visible light communication has gained much attention. This work proposes a smart license plate receiver incorporated with a fluorescent concentrator, enabling a fast vehicle-to-vehicle communication with a large field of view and high optical gain. Communication performance is experimentally analyzed using off-the-shelf light-emitting diode-based headlamps for low-latency direct line of sight channel. Additionally, a blue laser diode-based beam-steering and tracking system, through image processing of taillights with a steerable mirror, is investigated. Data rates of 54 Mbps from the headlamps and 532 Mbps from the beam-steering channel with ±25° are demonstrated. In addition, real-time video streaming through the beam-steering channel is presented.

With the remarkable advances in vertical-cavity surface-emitting lasers (VCSELs) in recent decades, VCSELs have been considered promising light sources in the field of optical wireless communications. However, off-the-shelf VCSELs still have a limited modulation bandwidth to meet the multi-Gb/s data rate requirements imposed on the next-generation wireless communication system. Recently, employing machine learning (ML) techniques as a method to tackle such issues has been intriguing for researchers in wireless communication. In this work, through a systematic analysis, it is shown that the ML technique is also very effective in VCSEL-based visible light communication. Using a commercial VCSEL and bidirectional long short-term memory (Bi-LSTM)-based ML scheme, a high-speed visible light communication (VLC) link with a data rate of 13.5 Gbps is demonstrated, which is the fastest single channel result from a cost-effective, off-the-shelf VCSEL device, to the best of the authors’ knowledge.