# Optimization of Bit Allocation for Spatial Multiplexing in MIMO VLC System with Smartphones
###### Abstract  
This paper focuses on the hardware components of smartphones, namely, the use of displays and cameras in mobile devices as transmitters and receivers to establish a near-field multiple-input-multiple-output (MIMO) visible light communication (VLC) system. Based on the relationship between the grayscale values of transmitted and received signals, the physical channel responses are detected and approximated with a high-order regression to obtain the channel gain. With the constraint of bit numbers in the MIMO VLC system, an integer-type water-filling scheme was designed for bit allocation to improve transmission efficiency. The physical examinations show that bit error rate (BER) reduction can be 26.4% with Gaussian noise of 30 dB and detected channel gain compared with the equal bit allocation. The optimization of the simulation was confirmed with the bit assignments in real cases. optical channel; modulation; water filling algorithm;  
A basic VLC system is developed with the integration of a controller and optical components based on light-emitting diodes (LEDs) that deliver both lighting and data transmission. At the receiver part, a photodiode (PD) can detect the optical signals. Accordingly, the overall system design is inexpensive compared to radio frequency (RF) systems. In [6], some advantages of VLC include unregulated and license-free bandwidth, frequency reuse in adjacent rooms, security as light signals are undetectable behind walls, fewer health issues, and functionality in such environments where traditional RF systems are limited or forbidden. In recent years, related developments vary not only in long-distance transmission via conductors or cables but also in near-field wireless communication. An increasing number of communication applications are especially used in mobile platforms, such as in smartphones and wearable devices. Due to advances in software and hardware designs, the optical components of mobile platforms have also been improved for high-value displays and cameras. Therefore, optical wireless transmission with mobile devices has emerged from radio frequency communication. This novel communication method can transmit information through visible light channels by converting electrical signals into intensity signals [7]. Therefore, optical components, such as a liquid-crystal display (LCD) and light-emitting diodes (LEDs), commonly designed for monitoring and illumination, are used as transmitters for VLC technologies. Moreover, the imaging capture components, including the complementary metal-oxide-semiconductor (CMOS) and charge-coupled device (CCD), are potential solutions for optical receivers. Generally, the advantages of VLCs [8; 9; 10] are safety, illumination, low cost, no electromagnetic interference, and a license-free spectrum. Since frequency band competition is increasingly fierce, VLC has become increasingly important. To realize VLC techniques, precoding and equalization are critical for adapting the transmitter to the channels. Moreover, the joint design of the precoder and equalizer for a MIMO VLC system [11] usually suffers from a degraded performance in the low signal-to-noise ratio (SNR) regime. In preliminary research, the power allocation of a single-user MIMO VLC was studied with a design of modulation, multiplexing, and detection, as in [12]. Moreover, zero-forcing multi-user precoding techniques are also realized to improve VLC systems [13]. However, this incorporation of precoding and equalization developed in simulation cannot be directly applied to mobile devices because display-camera VLC systems utilize a low operating frequency (generally 30 Hz for display and capture). Moreover, the configurations of cameras, mainly adjusted by a mobile system (BIOS, firmware, or operating system), may yield significantly different signals and models. In the physical channel, transmission quality as bit error rate (BER) varies due to the issues of the mediums in channels, such as fogging or blurry conditions.