A hybrid VLP and VLC system using m-CAP modulation and fingerprinting algorithm

Mahdi Nassiri, Gholamreza Baghersalimi*, Zabih Ghassemlooy

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


A global positioning system (GPS) with high positioning accuracy (PA) is not feasible for challenging environments such as tunnels, underground, complex buildings, etc. For such environments, the alternative technology of visible light positioning (VLP) system has emerged as a viable solution. In this paper, we propose for the first time, a hybrid multi-band carrier-less amplitude and phase (m-CAP) based VLP and visible light communications (VLC) system using the fingerprinting algorithm for determining the position of the receiver, i.e., VLP, and employing the unused sub-bands of m-CAP for VLC. We compare the results for different transmitter configurations and a range of step sizes in terms of the position error (PE) and the bit error rate (BER) performances. Results show that, PE increases with the step size, which is the most critical parameter in fingerprinting-based positioning systems, for a fixed bit energy to noise ratio (Eb∕N0). For a fixed Eb∕N0 of 10 dB the PE values are 4.5 and 10.7 cm for the step sizes of 1 and 20 cm, respectively. For a fixed step size, in contrast, PE decreases with increasing Eb∕N0. Numerical results for a fixed step size of 5 cm show that the PE is reduced from 13.8 to 3.3 cm by 10 dB increase in Eb∕N0. In addition, by increasing the step size, the quantization error overcomes the noise-induced error. We also show that, configurations I and II outperform configuration III in terms of the PE by about 8 to 6 cm at Eb∕N0 of 5 dB and BER (i.e., 1.56×10−4, 2.52×10−4 and 2.54×10−3 for configurations I, II and III, respectively at Eb∕N0 of 20 dB), since configuration III is approximately linear with a symmetrical fingerprint map and a lower illumination level.

Original languageEnglish
Article number125699
JournalOptics Communications
Early online date7 Mar 2020
Publication statusPublished - 15 Oct 2020


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