In this paper, we apply the non-orthogonal multiple access (NOMA) technique to improve the achievable sum rate of multiple-input multiple-output (MIMO) based multi-user visible light communication (VLC) systems. To ensure efficient and low- complexity power allocation in indoor MIMO-NOMA based VLC systems, a normalized gain difference power allocation (NGDPA) method is firstly proposed by exploiting users’ channel conditions. We investigate the performance of an indoor 2×2 MIMO-NOMA based multi-user VLC system through numerical simulations. The obtained results show that the achievable sum rate of the 2×2 MIMO-VLC system can be significantly improved by employing NOMA with the proposed NGDPA method. It is demonstrated that NOMA with NGDPA achieves a sum rate improvement of up to 29.1% compared to NOMA with the gain ratio power allocation (GRPA) method in the 2×2 MIMO-VLC system with three users.

In this paper, a low-complexity time-difference-of-arrival (TDOA)-based indoor visible light positioning (VLP) system using an enhanced practical localization scheme based on cross-correlation is proposed and experimentally demonstrated. The proposed TDOA scheme offers two advantages: 1) the use of virtual local oscillator (VLO) to replace the real local oscillator (RLO) for cross-correlation at the receiver side so as to reduce the hardware complexity; 2) the application of cubic spline interpolation on the correlation function to reduce the rigorous requirement on the sampling rate and to enhance the time-resolution of cross-correlation. In order to achieve high positioning accuracy with minimum implementation complexity, parameter optimization is first performed in terms of sampling rate, interpolation factor and data length for correlation. Using the obtained optimal parameters, we demonstrate a low-complexity indoor two-dimensional (2D) VLP system using the correlation-based TDOA scheme in a coverage area of 1.2$\times$1.2 m$^{2}$ with a height of 2 m. The experimental results validate the feasibility of the proposed TDOA scheme, and an average positioning accuracy of 9.2 cm is achieved with a sampling rate of 500 MSa/s, an interpolation factor of 100 and a data length of 250k samples.

With the rapid development of Internet of Things (IoT) in the smart city, smart grid, and smart industry, indoor communication and positioning are important for IoT. However, Radio Frequency (RF) based wireless networks may fail to guarantee different Quality of Service (QoS) requirements of devices, due to the limited bandwidth, severe interference and multipath reflections. Hence, this paper presents a new integrated Visible Light Communication (VLC) and Positioning (VLCP) network for IoT to provide both high-speed communication and high-accuracy positioning services. As the network consists of multiple VLC Access Points (APs), we propose jointly optimizing the AP selection, bandwidth allocation, adaptive modulation and power allocation approach to satisfy different QoS requirements of indoor devices while maximizing the network data rate. A low-complexity iterative algorithm is presented to solve the resource management (RM) optimization problem by decomposing it into two subproblems. Finally, we consider the Line Of Sight (LOS) blockage, a robust handover mechanism and a pedestrian dead reckoning-assisted VLCP scheme are presented to maintain the good performances. The simulation results verify that the proposed solutions outperform other existing solutions in terms of effectively enhancing the data rate, improving the positioning accuracy and guaranteeing devices’ QoS requirements. In details, the mean position error is reduced from 20 cm to 4.3 cm by using our presented integrated VLCP model. The proposed RM approach achieves a satisfied QoS level improvement of up to 20.3% compared with non-QoS-driven RM approach, and it achieves the high data rate up to 1.31 Gbps.

Due to severe inter-cell interference, the signal-to- interference-and-noise ratio (SINR) suffers from very significant fluctuation in indoor multi-cell visible light communication (VLC) systems, which greatly limits the overall system performance. In this paper, we propose and evaluate a generalized angle diversity receiver (ADR) structure to reduce SINR fluctuation in indoor multi-cell VLC systems. The generalized ADR consists of one top detector and multiple inclined side detectors. In an indoor multi- cell VLC system using the generalized ADR, the inclination angle of the side detectors is optimized in order to minimize the SINR fluctuation over the receiving plane, where the impact of receiver random rotation is considered. An optimized ADR with different numbers of detectors is analyzed with different LED layouts and diversity combining techniques in a typical indoor environment. Analytical results show that the SINR fluctuation is gradually reduced when more detectors are equipped in the optimized ADR. In an indoor two-cell VLC system, much more significant SINR fluctuation reduction is achieved by using select-best combining (SBC). However, nearly the same SINR fluctuations are obtained in an indoor four-cell VLC system when using SBC and maximal- ratio combining (MRC). By applying the optimized ADR, up to 15.9 and 32.4-dB SINR fluctuation reductions can be achieved in comparison to a conventional single-element receiver in indoor two-cell and four-cell VLC systems, respectively.

With the rapid development of Internet of Things (IoT) in the smart city, smart grid and smart industry, indoor communication and positioning are important fields of applications for indoor IoT. This paper presents an integrated visible light communication and positioning (VLCP) system for indoor IoT, in order to provide the high-speed data rate and high-accuracy positioning for IoT devices. where the filter bank multicarrier-based subcarrier multiplexing (FBMCSCM) technique is exploited to effectively reduce the out-ofband interference (OOBI) on both adjacent communication and positioning subcarriers. After that, we propose a coordinated resource allocation approach for the system with the purpose of maximizing the sum rate while guaranteeing the minimum data rates and positioning accuracy requirements of devices. To this end, we solve the optimization problem by decomposing it into two subproblems, where a low-complexity suboptimal subcarrier allocation approach is proposed and the sequential quadratic programming (SQP) method is adopted to solve the non-linearly constrained power allocation optimization problem. Numerical results verify the superiority in performance of the presented integrated VLCP system for indoor IoT, and the results also reveal that the proposed coordinated resource allocation approach can effectively improve the sum rate and the positioning accuracy compared with other resource allocation approaches.