Orbital Angular Momentum (OAM)-based communication systems offer high-capacity multiplexing in line-of-sight (LOS) scenarios; yet, their performance is sensitive to nodal misalignment, which disrupts modal orthogonality, hindering the data multiplexing gain. To tackle this challenge, we present OrthoVortex, a novel framework that estimates the misalignment angles and applies the appropriate phase correction to restore orthogonality between modes. Unlike purely theoretical prior efforts that rely on impractical fully digital arrays or exhaustive beam scans, OrthoVortex introduces and leverages the cross-modal phase, as a unique signature for identifying the misalignment angles. OrthoVortex is a few-shot alignment technique, making it feasible for real-world implementations. Our key contributions include: (i) a robust angle estimation and phase correction framework based on the physics of OAM propagation that estimates the misalignment and restores modal orthogonality, (ii) the first-ever experimental validation of OAM beam alignment with RF transceivers, and (iii) a comprehensive analysis of practical constraints, including the impact of antenna count and bandwidth. Simulations and over-the-air measurements using low-cost, rapidly prototyped metasurfaces operating at 120 GHz demonstrate that OrthoVortex achieves fast and precise misalignment estimation (mean absolute error of $0.69^{\circ}$ for azimuth and $2.54^{\circ}$ for elevation angle). Further, OrthoVortex can mitigate the inter-modal interference, yielding more than 12 dB increase in signal-to-interference ratio and more than 4.5-fold improvement in link capacity.

This paper investigates how an airborne node can eavesdrop on the underwater acoustic communication between submerged nodes. Conventionally, such eavesdropping has been assumed impossible as acoustic signals do not cross the water-air boundary. Here, we demonstrate that underwater acoustic communications signals can be picked up and (under certain conditions) decoded using an airborne mmWave radar due to the minute vibrations induced by the communication signals on the water surface. We implemented and evaluated a proof-of-concept prototype of our method and tested it in controlled (pool) and uncontrolled environments (lake). Our results demonstrate that an airborne device can identify the modulation and bitrate of acoustic transmissions from an uncooperative underwater transmitter (victim), and even decode the transmitted symbols. Unlike conventional over-the-air communications, our results indicate that the secrecy of underwater links varies depending on the modulation type and provide insights into the underlying reasons behind these differences. We also highlight the theoretical limitations of such a threat model, and how these results may have a significant impact on the stealthiness of underwater communications, with particular concern to submarine warfare, underwater operations (e.g., oil & gas, search & rescue, mining), and conservation of endangered species. Finally, our investigation uncovers countermeasures that can be used to improve or restore the stealthiness of underwater acoustic communications against such threats.

This study examines how an airborne device can intercept underwater acoustic signals exchanged between submerged nodes. It challenges the conventional belief that acoustic communications under the water are safe against eavesdropping since acoustics do not cross the water-air boundary. We show that an airborne mmWave radar can detect and decode underwater acoustic signals by picking up minute surface vibrations induced by these signals. The proof-of-concept was tested in controlled (pool) and uncontrolled (lake) environments, proving that an airborne adversary can identify modulation type, bitrate, and decode symbols from an uncooperative underwater transmitter using its radar sensing capabilities. We demonstrate that the secrecy of underwater links depends on modulation type, providing insights into countermeasures to enhance the security of underwater acoustic communications.

In this paper, we analyze the effect of implementing variable backoff algorithms on the average peak age of information (PAoI) and the average age of information (AoI) in slotted ALOHA networks. To this end, we first analytically derive the average PAoI in exponential backoff slotted ALOHA when the number of backoff stages is finite. We also show that the reduction in average PAoI achieved by the exponential backoff algorithm can significantly increase the average AoI, which is not desirable. Then, we propose an age-based backoff algorithm and present the intuition behind it. In contrast to exponential backoff, our proposed age-based backoff algorithm reduces the average PAoI significantly, while changing the average AoI limitedly. The numerical results confirm our analytical results as well as the superiority of the proposed age-based backoff algorithm over exponential backoff.