This paper proposes a joint design of probabilistic constellation shaping (PCS) and precoding to enhance the sum-rate performance of multi-user visible light communications (VLC) broadcast channels subject to signal amplitude constraint. In the proposed design, the transmission probabilities of bipolarM-pulse amplitude modulation (M-PAM) symbols for each user and the transmit precoding matrix are jointly optimized to improve the sum-rate performance. The joint design problem is shown to be a complex multivariate non-convex problem due to the non-convexity of the objective function. To tackle the original non-convex optimization problem, the firefly algorithm (FA), a nature-inspired heuristic optimization approach, is employed to solve a local optima. The FA-based approach, however, suffers from high computational complexity. Thus, using zero-forcing (ZF) precoding, we propose a low-complexity design, which is solved using an alternating optimization approach. Additionally, considering the channel uncertainty, a robust design based on the concept of end-to-end learning with autoencoder (AE) is also presented. Simulation results reveal that the proposed joint design with PCS significantly improves the sum-rate performance compared to the conventional design with uniform signaling. For instance, the joint design achieves$\mathbf {17.5\%}$and$\mathbf {19.2\%}$higher sum-rate for 8-PAM and 16-PAM, respectively, at 60 dB peak amplitude-to-noise ratio. Some insights into the optimal symbol distributions of the two joint design approaches are also provided. Furthermore, our results show the advantage of the proposed robust design over the non-robust one under uncertain channel conditions.

This paper proposes a joint design of probabilistic constellation shaping (PCS) and precoding to enhance the sum-rate performance of multi-user visible light communications (VLC) broadcast channels subject to signal amplitude constraint. In the proposed design, the transmission probabilities of bipolar M-pulse amplitude modulation (M-PAM) symbols for each user and the transmit precoding matrix are jointly optimized to improve the sum-rate performance. The joint design problem is shown to be a complex non-convex problem due to the non-convexity of the objective function. To tackle the problem, the firefly algorithm (FA), a nature-inspired heuristic optimization approach, is employed to solve a local optima to the original non-convex optimization problem. The FA-based approach, however, suffers from high computational complexity. Therefore, we propose a low-complexity design based on zero-forcing (ZF) precoding, which is solved using an alternating optimization (AO) approach. Simulation results reveal that the proposed joint design with PCS significantly improves the sum-rate performance compared to the conventional design with uniform signaling. Some insights into the optimal symbol distributions of the two joint design approaches are also provided.

This paper investigates the energy efficiency (EE) of rate-splitting multiple access (RSMA)-based visible light communications (VLC) with confidential private messages. We first formulate an EE maximization problem that takes into account the achievable rate of the common message and the sum secrecy rate of private messages. Due to the fractional non-convex nature of the design problem, an algorithm that leverages the Dinkelbach algorithm and convex-concave procedure (CCP) is proposed to solve local optima. In this study, the channel similarity$S_{C}$and the rate-splitting power allocation ratio$\rho$are jointly considered to evaluate EE performance and trade-offs between the achievable common rate and the sum secrecy rate. Numerical results reveal that when$S_{C}$is below 0.7, the EE saturates at its optimum as$\rho$increases, while when$S_{C}$exceeds 0.7, an optimal$\rho$exists beyond which the EE starts declining. Moreover, it is observed that while the relationship between the sum secrecy rate and$S_{C}$is inversely proportional, it is directly proportional in the case of the common rate.