In an indoor visible light communication (VLC) system, it is indispensable to optimize the uniformity of the system, ensuring the flatness of illumination and the fairness of communication. On the one hand, uniform received illuminance can provide a more comfortable lighting environment, which is also the primary purpose of indoor lighting sources. On the other hand, uniform received optical power can improve the communication quality and fairness of the VLC system. However, the layout and configuration parameters of the lighting source will directly affect the uniformity of the light signals. The existing schemes often optimize the lighting source layout based on the top of the room without considering the deployment height of the lighting source and tend to employ a sequential optimization scheme to improve the lighting source layout and power allocation. Besides, little research is conducted on simultaneous optimization. Therefore, it is extremely important to optimize the uniformity of illuminance and received power of the system in view of the uneven distribution of light signals in the indoor VLC system.

Given the above problems, a fast whale optimization algorithm (FWOA) based on a fusion improvement strategy is proposed to simultaneously optimize the indoor lighting source layout and power allocation in this study. Considering the lighting source layout and power distribution of the LED deployment height, we adopt a simultaneous optimization scheme to achieve the optimal LED position layout and uniformity of indoor light signals. At the same time, as there may be a wide range of search and long optimization time in simultaneous optimization, the whale optimization algorithm (WOA) is introduced from the perspective of swarm intelligence. The convergence speed and global optimization ability of the algorithm are further improved through the fusion improvement strategy. The specific improvement design is as follows. First, to solve the problem of insufficient convergence speed of the WOA, we employ reverse learning to optimize the initialization stage of the whale algorithm. Second, although the existing knowledge of LED position layout and power distribution scheme facilitates algorithm convergence, the primary stage of the algorithm has not been greatly improved. Therefore, the coefficient matrix is adjusted so that the optimization stage enters the local search more quickly to accelerate the convergence process of the WOA. Third, entering the local search too early will induce the algorithm to fall into the local extremum search condition. For the problem of the algorithm falling into local optimum, a global perturbation search mechanism is added to better balance the search ability of the algorithm.

After the simultaneous optimization of 16 LED layout models (Fig. 3), five different LED lighting source optimization schemes are selected for comparison (Table 5), and the performance indicators after optimization are listed. The results show that compared with the previous optimization schemes, the illuminance uniformity of the proposed optimization scheme has been improved by 7.39% to 109.03%, and the quality factor of received power has been improved from 5.25 to 12.23, an increase of nearly 133%. After simultaneous optimization of lighting source layout and power distribution, the factor further increases to 15.12. The simultaneous optimization scheme and the proposed FWOA have excellent optimization performance. In addition, the optimal layout (Fig. 6) and received power distribution (Fig. 7) of the system are explored when the number of LEDs is 14, 12, 9, and 6 respectively. It is found (Table 6) that in different scenarios, a better balance between system energy and performance can be achieved by selecting the appropriate number of LEDs. In addition, by introducing the FWOA, the time for simultaneous optimization is also greatly reduced, and the calculation time is shortened to less than 1 h, which verifies the superior performance of the proposed algorithm in terms of convergence speed and optimum search.

In the indoor VLC system considering one reflection, we propose a FWOA based on the fusion improvement strategy and realize the optimal distribution of LEDs by simultaneously optimizing the lighting source layout and power distribution model of the LED deployment height. The research results show that compared with the traditional optimization models, the uniformity of the received power, illuminance, and signal-to-noise ratio (SNR) of the optimized distribution model is better with excellent communication fairness. Besides, the distribution model of different numbers of LEDs in the room is also studied. The results show that as the number of LEDs increases, the system performance exhibits a positive convergence characteristic. By increasing the number of LEDs, the optimized lighting source layout and received power can improve system performance. However, this growth relationship converges when the number of LEDs increases to 12. Then, increasing the number of LEDs can no longer significantly improve system performance, and will in turn increase system energy consumption and optimization time. Therefore, the performance and energy efficiency of the system can be better balanced by selecting the appropriate number of LEDs. This study can provide a valuable reference for the application of VLC in indoor rooms of different sizes.