As 5G devices and networks continue to roll out, new broadcasting services and capabilities have been introduced to the entire ecosystem, opening up additional new applications and granular business opportunities, where indoor joint communication and sensing are critical. Under this trend, in this paper, we propose a new system using multi-band carrierless amplitude and phase $(m$ -CAP) modulation associated with received signal strength (RSS)-based trilateration to achieve visible light sensing and communication from the same signal. The architecture of this system is first detailed, with an emphasis on how the light source limitations in terms of dynamic range and modulation bandwidth may be taken into account. The proposed set-up is then shown through simulations to provide an illuminance between 300 and 500 lux over the whole room, positioning with an error lower than 7.17 cm in 90% of the cases, and a continuous data connectivity at 32 Mbps. The influence of several parameters, including that of the main $m$ -CAP settings, on this performance is studied in order to define some general rules for the design of such a system.

Whilethe contours of 6G are still being defined, integrated sensing and communication (ISAC) has been identified by the International Telecommunications Union (ITU) as a key feature of next-generation wireless communications. Given the maturity already demonstrated for data transmission on the one hand, and positioning on the other hand, optical wireless communications (OWC) could offer promising solutions for ISAC implementation, especially in indoor scenarios. In this paper, we propose and implement an OWC-based ISAC system that relies on multi-band carrierless amplitude and phase ( $m$ -CAP) modulation associated with received signal strength (RSS)-based positioning to achieve data transmission and localization from the same signal. This $m$ -CAP/RSS system is deployed in a 1.2 $\times\, 1.2\,\times$ 2.16 m $^{3}$ room using four access points installed on the ceiling, and can provide a communication link at a data rate of 12 Mbps with a bit error rate of less than $3.8\times 10^{-3}$ to any user in a reception plane 20 cm above the ground, while estimating its position with an error of less than 5.9 cm in 90% of cases.

In this paper, a novel device identification method is proposed to improve the security of Visible Light Communication (VLC) in 5G networks. This method extracts the fingerprints of Light-Emitting Diodes (LEDs) to identify the devices accessing the 5G network. The extraction and identification mechanisms have been investigated from the theoretical perspective as well as verified experimentally. Moreover, a demonstration in a practical indoor VLC-based 5G network has been carried out to evaluate the feasibility and accuracy of this approach. The fingerprints of four identical white LEDs were extracted successfully from the received 5G NR (New Radio) signals. To perform identification, four types of machine-learning-based classifiers were employed and the resulting accuracy was up to 97.1%.