Optical reconfigurable intelligent reflecting surface (ORIS), as a new type of programmable optical communication equipment, can reconstruct the optical channel environment and expand the application scenarios of optical wireless communications (OWC), which have attracted widespread attention. However, with the increasing demand for OWC scale in B5G and even 6G scenarios, the coverage range of a single ORIS (below 300 m) can no longer meet communication needs. Cascaded ORISs’ technology has become an inevitable trend in the development of ORIS, which has not been deeply studied in existing work. To address the above challenges, in this paper we set up cascaded ORISs in a typical long-distance free space optcis (FSO) scenario and conduct a detailed analysis of their channels and performance. This system employs cascaded ORISs to extend ORIS coverage and expand the overall scale of the FSO system, thereby enabling the FSO link to evolve from a traditional point-to-point configuration to a broader, spatially distributed communication layout. The physical model of multiple ORISs’ cascades and the effect on their communication performance are analyzed in detail. Meanwhile, the closed-form expressions of the bit error rate (BER) and outage probability of the multi-hop cascaded ORISs-assisted FSO system are derived and verified by simulations. Based on the theoretical results and simulation results, the influence of each parameter on the system performance is carefully analyzed, which provides guidance for the design of the actual system.

The vision of 6G communication demands autonomous and resilient networking in environments without fixed infrastructure. Yet most multi-agent reinforcement learning (MARL) approaches focus on isolated stages—exploration, relay formation, or access—under static deployments and centralized control, limiting adaptability. We propose the AI Agent Access (A3) Network, a unified, embodied intelligence-driven framework that transforms multi-agent networking into a dynamic, decentralized, and end-to-end system. Unlike prior schemes, the A3Network integrates exploration, target user access, and backhaul maintenance within a single learning process, while supporting on-demand agent addition during runtime. Its decentralized policies ensure that even a single agent can operate independently with limited observations, while coordinated agents achieve scalable, communication-optimized coverage. By embedding link-level communication metrics into actor–critic learning, the A3Network couples topology formation with robust decision-making. Numerical simulations demonstrate that the A3Network not only balances exploration and communication efficiency but also delivers system-level adaptability absent in existing MARL frameworks, offering a new paradigm for 6G multi-agent networks.

Optical reconfigurable intelligent reflecting surface (ORIS), as a new type of programmable optical communication device, can deflect, split, and shape incident light, thereby intelligently reconstructing the optical wireless communication (OWC) environment. The application of ORIS has effectively expanded the application scenarios of OWC and improved system performance and robustness, which has attracted widespread attention. However, the existing ORIS is limited by its basic structure, and has problems such as low stability and poor signal quality in long-distance transmission. Aiming at the pain points of the existing ORIS, this paper proposes an optical reconfigurable distributed sources and reflecting surface (ORDSS) for distributed OWC. By arranging distributed sources in partial areas of the metasurface, users’ performance optimization is achieved based on power compensation and beam adaptive optimization algorithms. In this work, we performed physical modeling of an ORDSS-assisted OWC system, incorporating factors such as the characteristics and spatial distribution of ORDSS sources and reflection units, surface jitter of the ORDSS, pointing errors, and atmospheric attenuation. We derived the expression for the receiving performance of the ORDSS-assisted OWC system and compared it with that of conventional ORIS-assisted OWC systems to evaluate the performance gains brought by ORDSS. Building on the physical model and performance analysis, we investigated an adaptive power control algorithm for the distributed sources in ORDSS. In addition, we explored power compensation mechanisms based on ORDSS distributed sources to enhance system performance in mobile communication scenarios.

The sixth-generation (6G) mobile network and the Industrial Internet of Things (IIoT) demand high-speed, low-latency communication in diverse environments. Hybrid free-space optical (FSO)/radio frequency (RF) systems offer a promising solution by combining the strengths of both technologies. However, maintaining robustness under dynamic atmospheric conditions remains a challenge. To tackle this issue, we propose a feedback-free hybrid FSO/RF system that analyzes atmospheric conditions from camera-captured images and utilizes a deep learning network for real-time power allocation. By dynamically optimizing link utilization, it mitigates obstacles and weather fluctuations while eliminating feedback overhead, enhancing efficiency. Simulations show that our feedback-free system maintains superior bit error rate (BER) and outage performance while offering greater stability and adaptability to dynamic environments. Compared to state-of-the-art methods, it achieves more reliable performance under varying conditions. By leveraging camera-based perception instead of feedback links, it optimally adjusts FSO/RF utilization, providing a practical, scalable framework for next-generation IoT applications and ensuring reliable communication under varying conditions.

Light-emitting diode (LED) based visible light positioning (VLP) has been widely studied to provide high-accuracy and low-cost localization services. Existing single-LED VLP systems suffer from severe energy attenuation when the receiver is far from the LED. Even though multiple LEDs could be deployed, the fusion of their positioning information remains an open problem. In this paper, we propose a multi-LED indoor VLP system with LED signal selection or combining. The receiver contains several differently-oriented photodiodes (PDs) working cooperatively as an angle-of-arrival estimator, and each LED individually provides the receiver with a localization result. With these single-LED positioning results, we select the results with the minimum localization error, or combine the results according to their distributions. Closed-form positioning error expressions are derived for the proposed methods. Moreover, increasing the LED number is shown to reduce the positioning error, but the reduction is negligible when the LED number is sufficiently large. Finally, an experimental testbench is built to verify the feasibility of the proposed methods, and a millimeter-level accuracy has been achieved, which is better than that of the classic trilateration method.

This article studies the topic of probabilistic on-off division multiple access (ODMA) system design under multiple input-multiple output (MIMO) and massive MIMO with hybrid analog/digital architectures for unsourced random access (URA). Though probabilistic ODMA in Gaussian multiple access channel (GMAC) manifests desirable capacity, probabilistic ODMA extension towards MIMO and hybrid massive MIMO encounters problems have not been discussed. Specifically, a portion of data bits are utilized to select on-off patterns and not transmitted. These pattern-correlated bits and others are restored iteratively with pilot-free transmission in the so-called process of joint pattern and data detection. Discrepant to the state-of-arts, such as interleaving division multiple access (IDMA), where prior of patterns is an essential prerequest for the later detection, probabilistic ODMA detects pattern and data simultaneously with only linearly modulated signals. In this work, two probabilistic ODMA transceiver designs are proposed by different ranks of signal component matrix in MIMO and hybrid massive MIMO. Overall, our proposed designs retain the simplicity of the original ODMA and further exploits the sparsity of on-off patterns. For MIMO, on-off patterns are correlated with common codebook and a receiver is designed in the spirit of uncoupled URA. For hybrid massive MIMO, a novel probabilistic ODMA transceiver achieves probabilistic channel estimation via low-rank matrix completion aided by the sparsity of on-off patterns. Meanwhile, joint pattern and data detection is accomplished by iterative treating interference as noise (TIN) strategy. Extensive simulations are conducted under fair comparisons with state-of-the-arts to verify the validity of the proposed schemes.

With the continuous improvement of the communication frequency band, optical wireless communication (OWC) has attracted extensive attention. Due to the short wavelength and high directivity of optical signals, OWC has high requirements for precise positioning and beam alignment, which additionally increases the positioning and computing burden of the base station. In order to solve this pain point problem, this paper proposes an optical integrated sensing and communication system based on combination of optical intelligent reflecting surface (OIRS) and photodiode (PD) array. This system enables the integration of sensing and communication functionalities with a single transmission, a single device, and ultimately a single network infrastructure, which saves a lot of resources and improves system performance. Based on the OWC channel model and the OIRS physical model, we deduce the probability distribution function (PDF) of channel fading and the closed-form expression of system performance, which shows the influence of various parameters on performance. Simulations have been performed to verify the accuracy of the derived results. Based on theoretical results and simulation results, we make suggestions for system design.

In this paper, we consider the channel modeling of a heterogeneous vehicular integrated sensing and communication (ISAC) system, where a dual-functional multi-antenna base station (BS) intends to communicate with a multi-antenna vehicular receiver (MR) and sense the surrounding environments simultaneously. The time-varying complex channel impulse responses (CIRs) of the sensing and communication channels are derived, respectively, in which the sensing and communication channels are correlated with shared clusters. The proposed models show great generality for the capability in covering both monostatic and bistatic sensing scenarios, and as well for considering both static clusters/targets and mobile clusters/targets. Important channel statistical characteristics, including time-varying spatial cross-correlation function (CCF) and temporal auto-correlation function (ACF), are derived and analyzed. Numerically results are provided to show the propagation characteristics of the proposed ISAC channel model. Finally, the proposed model is validated via the agreement between theoretical and simulated as well as measurement results.

Free space optical communication has been applied in many scenarios because of its security, low cost and high rates. In such scenarios, a tracking system is necessary to ensure an acceptable signal power. Free space optical links were considered unable to support fast moving nodes, such as unmanned aerial vehicles, cars or pedestrians, in optical mobile communication because existing tracking schemes fail to track the nodes accurately and rapidly. In this paper, we propose a novel tracking system exploiting multiple beacon lasers. Each beacon laser's power is measured to estimate the orientation of the target. Unlike existing schemes which drive servo motors multiple times based on consecutive measurements and feedback, our scheme can directly estimate the next optimal targeting shift for the servo motors based on a single measurement, allowing the tracking system to converge much faster. Closed-form outage probability expression is derived for the optical mobile communication system with ideal tracking, where pointing error and moving statistics are considered. To maintain sufficient average power and reduce the outage probability, the recommended beam divergence of the main laser is expressed in closed form as a function of the target's statistics of random shift, providing insights to the system design.