# Bi-LSTM-Augmented Deep Neural Network for Multi-Gbps VCSEL-Based Visible Light Communication Link
## 1 Introduction  
With the advent of big-data technology and extremely fast computing speeds, machine learning for data-intensive science has developed. Machine learning (ML) is a field of artificial intelligent (AI) that automates the generation of models for data analysis, allowing software to learn and find patterns based on data. This helps minimize human intervention and accelerate decision making. In recent years, machine learning has served as a useful technology in various fields such as gender recognition from facial images for security systems or mobile devices [1], the analysis of financial fraud detection [2] and the prediction of biological data [3]. Additionally, it is shown that machine learning is useful in many areas of the agriculture industry, including crop management, livestock management, water management and soil management [4]. Machine learning can contribute to both the physical layer and the network layer in the field of optical communication as well [5, 6, 7]. It can also improve the performances in diverse fields such as physics [8], chemistry [9], society [10], economy [11] and communication [7]. More introductory information about the basic ideas of machine learning methods can be found in [12]. With the emergence of the next generation communication networks, there has been a significant interest in machine learning as a technology that can realize next-generation communication systems. Adversarial machine learning (AML) in radio frequency (RF) wireless communications has been studied for defending against cyberattacks, eventually developing a secure system for the foundation of next-generation wireless communications [13, 14]. To meet the requirements imposed on the next-generation wireless communication, data rates that are an order of magnitude higher and have substantially lower latency, compared to the existing network, should be provided. Optical wireless communication(OWC) and visible light communication (VLC) have been attractive solutions mainly due to their license-free and high spectral efficiency [15]. There are two types of light sources used in most OWC and VLC systems: light-emitting diodes (LED) and laser diodes (LD). LEDs have a broad spectral width, and they have been widely deployed as lighting sources due to their cost-effectiveness and high efficacy. LDs have a narrow spectral and can be utilized to achieve higher data rates and longer transmission distances in VLC systems thanks to their coherent characteristics. However, LDs are relatively expensive sources and often require sophisticated temperature control. The modulation bandwidth of LEDs, in general, ranges from a few MHz to tens of MHz, and that of LDs is orders of magnitude higher. Additionally, it is useful to apply wideband auxiliary components to avoid the additional bandwidth limitation on the light sources [16]. Using a single LED, a VLC communication link with a data rate of 8 Gbps was reported [17], where a resonant cavity LED with direct current-biased orthogonal frequency division multiplexing (DCO-OFDM) was used. Employing a single GaN-based blue laser diode, the authors in [18] achieved a data rate of 15 Gbps at a distance of 15 cm. With the advancement of vertical-cavity surface-emitting laser (VCSEL) diodes in recent decades, researchers have been exploring the potential of VCSEL as a light source for OWC and VLC systems. VCSELs are cost-effective compared to other LDs and have a faster modulation bandwidth than LEDs. They require a low driving current and provide an excellent beam quality with a circular emission pattern, suitable for OWC and VLC [19]. Further, VCSELs' short cavity results in a single longitudinal mode only. Therefore, VCSELs do not suffer from kink phenomena in the optical L-I curve, whereas other semiconductor lasers suffer from power instability and control problems [20]. A single channel data rate of 12.5 Gbps using a VCSEL with 5.2 GHz of bandwidth was demonstrated with 16-level quadrature amplitude modulation (QAM) OFDM modulation [21].