Spectrum map construction is a key technology for enhancing dynamic spectrum management and spectrum efficiency in the sixth-generation wireless communication networks. However, traditional spectrum map construction methods face a dual bottleneck in model generalizability and data dependence. Specifically, the model-driven methods struggle to adapt to dynamic and complex electromagnetic environments, whereas data-driven methods depend on the quality of training data, including sampling density and spatial correlation complexity. To address these challenges, a vision transformer-based large model for spectrum map construction is proposed, namely GenSpectraLM. Inspired by bidirectional encoder representations from transformers masked semantic inference and masked autoencoders local-global construction mechanism, GenSpectraLM employs self-supervised masked pretraining to implicitly learn electromagnetic propagation patterns from diverse datasets. Then, fine-tune is performed to achieve cross-scenario generalization. Simulation results demonstrate that GenSpectraLM achieves accurate spectrum map construction with the root mean squared error of 1.3286 at a sampling rate of 25%. It consistently outperforms benchmark methods by approximately 40%, effectively addressing data efficiency challenges in complex environments.

With the rapid development of wireless communication services, spectrum map-based localization has become an important technology in the sixth-generation (6G) wireless communication networks due to their low cost and ease of implementation. However, signal source localization based on spectrum map construction is heavily dependent on the construction accuracy of the spectrum map. This challenge is further exacerbated in urban environments due to high-density connections and complex terrain. To address the aforementioned challenges, a data-and-semantic dual-driven method is proposed, which incorporates semantic knowledge of both binary city maps and binary sampling location maps. This approach first extracts spatial dimension information that reflects signal propagation, improving the accuracy of the constructed spectrum map and signal source localization in the complex urban environments. Then, to reduce the reliance of signal source localization on the accuracy of spectrum map construction, a data-and-semantic dual-driven intelligent inference framework for simultaneously spectrum map construction and signal source localization (DSD-SCL) is proposed. Moreover, a joint training framework is employed to collaboratively optimize both spectrum map construction and signal source localization. Simulation results demonstrate that DSD-SCL exhibits superior performance in terms of stability and convergence speed. Meanwhile, it significantly enhances the construction accuracy of spectrum maps and the localization accuracy of signal sources, particularly in low sampling density and multisignal source scenarios.

The application of power over Ethernet (PoE)-enabled lighting has emerged as a groundbreaking technology with the potential to achieve cooperative control and create an energy-saving lighting network. However, fine-grained user-side lighting environment perception is crucial to improve energy efficiency and user experience. To tackle this issue, a PoE-enabled intelligent lighting network with multi-modal sensing is proposed. Specifically, a multi-modal sensor is designed and installed on the side of the luminaire to provide both fine-grained lighting environment monitor and dimming. Then, a multilayer perceptron (MLP)-based estimation scheme is proposed to estimate the illumination and color temperature information around the user activity area. Moreover, an experimental lighting network is constructed and deployed in a classroom to measure practical lighting dataset. The proposed scheme effectively estimates the lighting quality on the user side based on the measurement data. Furthermore, based on the estimated information and the collaborative control capabilities of PoE, the operating current of the luminaire is updated in real time, and thus the ambient light resource is fully utilized. Finally, the proposed lighting network achieves a 39.99% energy saving.

Spectrum maps reflect the utilization and distribution of spectrum resources in the electromagnetic environment, serving as an effective approach to support spectrum management. However, the construction of spectrum maps in urban environments is challenging because of high-density connection and complex terrain. Moreover, the existing spectrum map construction methods are typically applied to a fixed frequency, which cannot cover the entire frequency band. To address the aforementioned challenges, a UNet-based data-and-semantic dual-driven method is proposed by introducing the semantic knowledge of binary city maps and binary sampling location maps to enhance the accuracy of spectrum map construction in complex urban environments with dense communications. Moreover, a joint frequency-space reasoning model is exploited to capture the correlation of spectrum data in terms of space and frequency, enabling the realization of complete spectrum map construction without sampling all frequencies of spectrum data. The simulation results demonstrate that the proposed method can infer the spectrum utilization status of missing frequencies and improve the completeness of the spectrum map construction. Furthermore, the accuracy of spectrum map construction achieved by the proposed data-and-semantic dual-driven method outperforms the benchmark schemes, especially in scenarios with low sampling density.

The rapid evolution of next-generation communi¬cation technology has underscored the critical challenge of spectrum resource scarcity. Visible light communication (VLC) is widely recognized as a promising solution to tackle this issue. Benefits from the rich spectrum resources and no electromagnetic interference radiation, VLC can be widely used in various indoor communication scenarios. However, the accessing of the existing network for the VLC system still remains a challenge. Thus, an optical fiber-based VLC structure is proposed to unlock traditional network cable transmission for the first time. Specifically, an optoelectronic media converter is designed to efficiently connect the fiber signal and the desired electrical signal. Moreover, an analog equalizer with low implementation complexity is exploited to extend the LED bandwidth, ensuring transmitted signals without distortion. It is worth noting that the VLC receiver adopts the auto gain control amplifier to meet the signal voltage requirement of the Ethernet physical layer. Experimental testbed is conducted and corresponding results demonstrated that the transmission rate of the proposed VLC system can reach 100Mbps with sufficiently low bit error rate. Therefore, this validates the capability of the proposed system to directly connect the VLC access point with the existing optical network facilities.

Light fidelity (LiFi) is a potential key technology for future 6G networks. However, its feasibility of supporting mobile communications has not been fundamentally discussed. In this paper, we investigate the time-varying channel characteristics of mobile LiFi based on measured mobile phone rotation and movement data. Specifically, we define LiFi channel coherence time to evaluate the correlation of the channel timing sequence. Then, we derive the expression of LiFi transmission rate based on the m-pulse-amplitude-modulation (M-PAM). The derived rate expression indicates that mobile LiFi communications is feasible by using at least two photodiodes (PDs) with different orientations. Further, we propose two channel estimation schemes, and propose a LiFi channel tracking scheme to improve the communication performance. Finally, our experimental results show that the channel coherence time is on the order of tens of milliseconds, which indicates a relatively stable channel. In addition, based on the measured data, better communication performance can be realized in the multiple-input multiple-output (MIMO) scenario with a rate of 36Mbit/s, compared to other scenarios. The results also show that the proposed channel estimation and tracking schemes are effective in designing mobile LiFi systems.

Visible light positioning (VLP) has advantages over traditional indoor positioning techniques in terms of high positioning accuracy and low cost. However, in resource-constrained VLP systems, especially devices deployed on Internet-of-Things networks, both the bandwidth of the light-emitting diode (LED)-based transmitter and the sampling rate of the photodetector (PD)-based receiver are limited. In turn, this significantly limits the positioning accuracy. To address this issue and accommodate the scenario of low bandwidth and hardware cost, a novel positioning scheme with low bandwidth requirements and high-precision pulse reconstruction is proposed in the paper. Specifically, a new beacon signal is designed based on the on-off keying pulse pairs to remove the synchronization requirement and save bandwidth costs. Then, based on the maximum a posteriori probability criterion, a low sampling rate positioning scheme is exploited to estimate the location from the pulse pairs received by the PD. Moreover, an experimental test-bed is constructed to verify the effectiveness and feasibility of the proposed positioning scheme. Experimental results demonstrate that the proposed scheme achieves a positioning accuracy of 1.7 cm by using the reconstructed 2 GHz sampling rate in the case of a bandwidth of 50 MHz and a real sampling rate of 100 MHz. The positioning accuracy achieved by the proposed scheme remains within 30 cm, even under the few MHz of inherent LED bandwidth.

Visible light positioning (VLP) as a promising technology can provide high-precision indoor positioning services without electromagnetic interference, especially in multiple light-emitting diode (LED) scenarios. However, both high synchronization control cost and the multi-path interference are inevitable, which limits the performance gain of the VLP systems. In order to solve this problem, a differential phase of arrival (DPOA)-based positioning scheme is proposed in this paper to remove the reliance on time synchronization and alleviate the multi-path interference. Specifically, a dual-frequency orthogonal beacon is designed and the DPOA-based positioning algorithm is exploited to extract the differential phase information. Then, the positioning optimization problem is formulated by considering both positioning error and location constraints. Thus, the semi-definite programming (SDP) optimization method is exploited to obtain position. The simulation results demonstrate that the positioning accuracy achieved by the proposed scheme outperforms that obtained by traditional received signal strength and the time difference of arrival-based schemes, 90% positioning errors of the proposed method remain within 1.3 cm. Moreover, an experimental VLP test-bed is conducted to verify the feasibility and effectiveness of the proposed positioning scheme. The experimental results show that the average positioning error is 7.12 cm, which meets the centimetre-level positioning requirements.

In this paper, we propose joint beamforming and photo-detector (PD) orientation (BO) optimization schemes for mobile visible light communication (VLC) with the orientation adjustable receiver (OAR). Since VLC is sensitive to line-of-sight propagation, we first establish the OAR model and the human body blockage model for mobile VLC user equipment (UE). To guarantee the quality of service (QoS) of mobile VLC, we jointly optimize BO with minimal UE the power consumption for both fixed and random UE orientation cases. For the fixed UE orientation case, since the transmit beamforming and the PD orientation are mutually coupled, the joint BO optimization problem is nonconvex and intractable. To address this challenge, we propose an alternating optimization algorithm to obtain the transmit beamforming and the PD orientation. For the random UE orientation case, we further propose a robust alternating BO optimization algorithm to ensure the worst-case QoS requirement of the mobile UE. Finally, the performance of joint BO optimization design schemes are evaluated for mobile VLC through numerical experiments.

The bound of the information transmission rate of direct current biased optical orthogonal frequency division multiplexing (DCO-OFDM) for visible light communication (VLC) with finite-alphabet inputs is yet unknown, where the corresponding spectral efficiency (SE) and energy efficiency (EE) stems out as the open research problems. In this paper, we derive the exact achievable rate of the DCO-OFDM system with finite-alphabet inputs for the first time. Furthermore, we investigate SE maximization problems of the DCO-OFDM system subject to both electrical and optical power constraints. By exploiting the relationship between the mutual information and the minimum mean-squared error, we propose a multi-level mercury-water-filling power allocation scheme to achieve the maximum SE. Moreover, the EE maximization problems of the DCO-OFDM system are studied, and the Dinkelbach-type power allocation scheme is developed for the maximum EE. Numerical results verify the effectiveness of the proposed theories and power allocation schemes.

Visible light communication (VLC) is a promising technique in the fifth and beyond wireless communication networks. In this paper, a secure multiple-input single-output VLC network is studied, where simultaneous lightwave information and power transfer (SLIPT) is exploited to support energy-limited devices taking into account a practical non-linear energy harvesting model. Specifically, the optimal beamforming design problems for minimizing transmit power and maximizing the minimum secrecy rate are studied under the imperfect channel state information (CSI). S-Procedure and a bisection search is applied to tackle challenging non-convex problems and to obtain efficient resource allocation algorithm. It is proved that optimal beamforming schemes can be obtained. It is found that there is a non-trivial trade-off between the average harvested power and the minimum secrecy rate. Moreover, we show that the quality of CSI has a significant impact on achievable performance.

Visible light communication (VLC) is a promising technology for the next generation wireless communication systems due to its high spectral efficiency and energy efficiency. In this article, a secure multiple-input single-output (MISO) VLC network is studied, where simultaneous lightwave information and power transfer (SLIPT) is exploited to support multiple energy-limited devices tacking into account a practical non-linear energy harvesting model. The transmit power minimization and the minimum secrecy rate maximization problems are formulated under both perfect and imperfect channel state information, respectively. To further improve the user connectivity, those problems are also investigated in MISO-VLC networks with non-orthogonal multiple access (NOMA). To tackle these challenging non-convex problems, semidefinite program relaxation and $-Procedure are exploited. It is proved that optimal beamforming schemes can be obtained for the considered two types problems in MISO-VLC SLIPT networks, while a sub-optimal solution can be obtained for the transmit power minimization problem in those networks with NOMA. It is found that there is a non-trivial trade-off between the average harvested power and maximum-minimum secrecy rate. Moreover, it is shown that the performance achieved with NOMA outperforms that of conventional orthogonal multiple access in MISO-VLC SLIPT networks, despite the existence of imperfect channel state information.