High-speed vehicular environments require optical systems capable of joint sensing, positioning, and communication (JSPC) without mechanical tracking. Existing optical and integrated sensing-communication approaches often rely on point-source emitters or camera-based receivers, limiting spatial coverage and update rate under highway dynamics. This work introduces a new class of tracking-free optical JSPC systems that combine structured line-laser illumination with modulating retroreflector (MRR) arrays on vehicles. Two orthogonal line lasers perform synchronized longitudinal and transverse scanning to provide continuous, wide-area coverage across the roadway. A coverage-driven analytical framework models the coupling between beam divergence, scan geometry, and dwell-time allocation, enabling joint evaluation of sensing reliability and communication quality. An optimization scheme is developed to adapt scanning and divergence parameters for uniform coverage and power efficiency. Simulation results demonstrate significant improvements in spatial coverage uniformity, link stability, and reliability within a fixed scan period. These results establish a practical pathway toward scalable, turbulence-resilient optical architectures for next-generation vehicular JSPC networks.

As 6G and beyond aim for sustainable, high-capacity wireless connectivity, optical wireless communication (OWC) has emerged as a compelling solution. Recent advances in vertical-cavity surface-emitting laser (VCSEL) arrays have significantly enhanced OWC performance, enabling high-speed, low-power data transmission. However, dense VCSEL deployments introduce challenges related to interference and energy efficiency (EE). This paper proposes a scalable precoding framework for EE maximization in fully cooperative VCSEL-based OWC broadcast systems. We formulate a non-convex optimization problem to design the precoding matrix under practical optical constraints while guaranteeing minimum user rates. To solve this, we apply Dinkelbach’s method to handle the fractional objective and the inner approximation technique to iteratively convexify and solve the problem. Simulation results show that our approach consistently outperforms regularized zero-forcing in terms of EE, particularly in large-scale deployments, demonstrating its potential for next-generation sustainable dense OWC networks.

Abstract In this paper, the problem of opportunistic spectrum sharing for the next generation of wireless systems empowered by the cloud radio access network (C‐RAN) is studied. More precisely, low‐priority users employ cooperative spectrum sensing to detect a vacant portion of the spectrum that is not currently used by high‐priority users. The authors' aim is to maximize the overall throughput of the low‐priority users while guaranteeing the quality of service of the high‐priority users. This objective is attained by optimally adjusting spectrum sensing time, with respect to target probabilities of detection and false alarm, as well as dynamically allocating C‐RAN resources, that is, powers, sub‐carriers, remote radio heads, and base‐band units. To solve this problem, which is non‐convex and NP‐hard, a low‐complex iterative solution is proposed. Numerical results demonstrate the necessity of sensing time adjustment as well as effectiveness of the proposed solution.

The integration of unmanned aerial vehicles (UAVs) and millimeter wave (mmWave) wireless systems has been recently proposed to provide high data rate aerial links for next generation wireless networks. However, establishing UAV-based mmWave links is quite challenging due to the random fluctuations of hovering UAVs which can induce antenna gain mismatch between transmitter and receiver. To assess the benefit of UAV-based mmWave links, in this paper, tractable, closed-form statistical channel models are derived for three UAV communication scenarios: (i) a direct UAV-to-UAV link, (ii) an aerial relay link in which source, relay, and destination are hovering UAVs, and (iii) a relay link in which a hovering UAV connects a ground source to a ground destination. The accuracy of the derived analytical expressions is corroborated by performing Monte-Carlo simulations. Numerical results are then used to study the effect of antenna directivity gain under different channel conditions for establishing reliable UAV-based mmWave links in terms of achieving minimum outage probability. It is shown that the performance of such links is largely dependent on the random fluctuations of hovering UAVs. Moreover, higher antenna directivity gains achieve better performance at low SNR regime. Nevertheless, at the high SNR regime, lower antenna directivity gains result in a more reliable communication link. The developed results can therefore be applied as a benchmark for finding the optimal antenna directivity gain of UAVs under the different levels of instability without resorting to time-consuming simulations.