Fig. 1. Schematic of energy self-sustaining indoor VLP system based on Kmeans-KNN fusion algorithm

Fig. 2. Clustering results of the location area obtained by the Kmeans clustering algorithm. (a) First-level clustering; (b) second-level clustering

Fig. 3. Using Kmeans-KNN fusion algorithm, the positioning error of the system changes with K. (a) RMSE comparison with traditional KNN algorithm; (b) CDF of average error

Fig. 4. RMSE of the positioning system varying with the signal-to-noise ratio

Fig. 5. System positioning error using Kmeans-KNN fusion algorithm. (a) Average error CDF; (b) positioning error distribution