Scaling quantum computers from a few qubits to large numbers remains one of the critical challenges in realizing practical quantum advantage. Multi-core quantum architectures have emerged as a promising solution, enabling scalability through distributed quantum processing units (QPUs) interconnected via classical and quantum links. However, the bottleneck of wired connections persists, as densely packed wired interconnects, both vertically across temperature stages and horizontally within the same layer, introduce spatial constraints, power dissipation, and latency, which could hinder performance as the number of QPUs increases. To overcome these limitations, this work proposes a cryo-compatible on-chip differential dipole antenna operating at 28 GHz to enable short-range wireless communication within a quantum computer cryostat. Temperature-dependent material properties are incorporated to accurately capture antenna behavior at 4 K. Moreover, by embedding the antenna in a realistic cryostat structure, we evaluate the feasibility of antenna operation within the cryogenic environment. The proposed antenna achieves a reflection coefficient of -20.8 dB in free space and -18.38 dB within the cryostat, demonstrating efficient impedance matching.

sponsorship: This research is supported by iSEE-6G project under the Horizon Europe Research and Innovation program with Grant Agreement No. 101139291. (iSEE-6G project under the Horizon Europe Research and Innovation program|101139291)

In this paper, we present a spatially consistent A2G channel model based on probabilistic LOS/NLOS segmentation to parameterize the deterministic path loss and stochastic shadow fading model. Motivated by the limitations of existing Unmanned Aerial Vehicle (UAV) channel models that overlook spatial correlation, our approach reproduces LOS/NLOS transitions along ground user trajectories in urban environments. This model captures environment-specific obstructions by means of azimuth and elevation-dependent LOS probabilities without requiring a full detailed 3D representation of the surroundings. We validate our framework against a geometry-based simulator by evaluating it across various urban settings. The results demonstrate its accuracy and computational efficiency, enabling further realistic derivations of path loss and shadow fading models and thorough outage analysis.

Although the integration between Unmanned Aerial Vehicles (UAVs) and Radio Access Network (RAN) applications is envisioned to enable a variety of new use cases and services, several practical aspects related to autonomous operations over cellular systems are still largely unexplored due to difficulties in testing and validating such integration in the real world. In this paper, we bridge the gap between simulation and real-world applications by introducing a new framework that combines real-world robotic controllers and 5th generation (5G) cellular stacks with channel and flight simulation. We consider a holistic approach where we use ArduPilot as the flight controller and OpenAirInterface (OAI) and srsRAN as the 5G cellular stacks to provide a unified solution for developing and experimenting with UAV s for cellular applications. We utilize ArduPilot Software-in-the-Loop (SITL) to simulate and control the mobility of UAVs, while OAI-RFSim and srsRAN are used to model channel conditions. Our framework is particularly useful for developing data-driven solutions that require (i) a large amount of data collected under realistic operational conditions to learn effective control policies; and (ii) a sandbox and safe testing environment that enables exploration of the action space. By addressing a UAV coverage problem and developing a greedy heuristic, we demonstrate how our framework can be used to create and test algorithms in a simulated environment, showcasing its potential as a bridge to real-world applications.

Accurate Probability of Line-of-Sight$(P_{\text{LoS}})$modeling is important in evaluating the performance of Unmanned Aerial Vehicle (UAV)-based communication systems in urban environments, where real-time communication and low latency are often major requirements. Existing$P_{L o S}$models often rely on simplified Manhattan grid layouts using International Telecommunication Union (ITU)-defined builtup parameters, which may not reflect the randomness of real cities. Therefore, this paper introduces the Urban Line-ofSight Simulator (ULS) to model$P_{\text{LoS}}$for three random city layouts with varying building sizes and shapes constructed using ITU built-up parameters. Based on the ULS simulated data, we obtained the empirical$P_{L o S}$for four standard urban environments across three different city layouts. Finally, we analyze how well Manhattan grid-based models replicate$P_{L o S}$results from random and real-world layouts, providing insights into their applicability for time-critical communication systems in urban IoT networks.

In an era where digital connectivity is increasingly foundational to daily life, the security of Wi-Fi Access Points (APs) is a critical concern. This paper addresses the vulnerabilities inherent in Wi-Fi APs, with a particular focus on those using proprietary file systems like MiniFS found in TP-Link’s AC1900 WiFi router. Through reverse engineering, we unravel the structure and operation of MiniFS, marking a significant advancement in our understanding of this previously opaque file system. Our investigation reveals not only the architecture of MiniFS but also identifies several private keys and underscores a concerning lack of cryptographic protection. These findings point to broader security vulnerabilities, emphasizing the risks of security-by-obscurity practices in an interconnected environment. Our contributions are twofold: firstly, based, on the file system structure, we develop a methodology for the extraction and analysis of MiniFS, facilitating the identification and mitigation of potential vulnerabilities. Secondly, our work lays the groundwork for further research into WiFi APs’ security, particularly those running on similar proprietary systems. By highlighting the critical need for transparency and community engagement in firmware analysis, this study contributes to the development of more secure network devices, thus enhancing the overall security posture of digital infrastructures.

Communication by jointly precoded transmission from many distributed access points (APs), called cell-free massive multiple-input multiple-output (CF mMIMO), is a promising concept for beyond 5G systems. One of the challenging aspects of CF mMIMO is the efficient management of the radio resources. We propose both reinforcement learning (RL)-based and heuristic precoding aware radio resource scheduling (RRS) algorithms aiming at maximizing sum spectral efficiency (SE). The proposed algorithms allocate resources for Maximum Ratio Transmission (MRT), Zero-Forcing (ZF), Regularised Zero-Forcing (RZF), and Optimized Zero Forcing (OZF) precoders. For the resource allocation, both the set of serving APs and the physical resource blocks are considered. In high noise scenarios, the proposed RL-based RRS algorithm combined with the MRT precoder shows 2.4 times higher sum SE than the standard Round Robin scheduler. Moreover, we demonstrate that the proposed heuristic algorithms offer similar sum SE while significantly reducing the complexity compared to the RL-based solution. We also show that the RZF and OZF precodings, which are superior to the ZF precoding in noisy environments, result overall in more transmitted power. Therefore, assuming the same radio resource schedule and precoding strategy in the neighboring cells, it will result in more inter-cell interference and an overall reduced performance.

The market size of Unmanned Aerial Vehicles (UAVs, a.k.a drones) can reach up to 10% of the global market value. In particular, drone delivery is one of the most attractive applications. The growing number of drones requires appropriate traffic management systems that will rely on cellular networks. However, it has been shown in the literature that these networks cannot provide reliable communication due to low coverage probability and frequent handovers. This article presents a potential solution targeting these problems while requiring no modifications of the existing infrastructure. Namely, equipping the UAV with multiple cellular modems to connect to different providers’ networks introduces network diversity resulting in 98% coverage probability at the flight altitude of 100 meters. In contrast, one network ensures only 80% coverage. At the same time, the size of the outage zones becomes up to ten times smaller and the frequency of harmful handovers is reduced to zero. The results are obtained with a physical-layer simulator utilizing a real urban 3D environment, cellular network parameters (e.g., site locations, antenna orientation and gains), and specific aerial channel models.

In this paper, we present a fixed mmWave Multi-User Multiple-Input Multiple-Output (MIMO) system for fixed wireless access with a unique architecture. A digital MIMO system is combined with an analog multi-beam antenna array which uses a high-dimension 16×16 Butler matrix to obtain 16 orthogonal beams. A system model of this architecture is presented and used to simulate its performance comparing to the performance of common-used patch antennas. Several MIMO precoding techniques are considered and compared with basic analog beamforming. To verify these results, a prototype is built and a dedicated measurement campaign is performed. The results show that the system model is a good approximation and that the use of the multi-beam antenna array is a good alternative to patch antennas for a large number of users.

This paper presents the concept of an UAV-mounted passive radar. Since the radar has no active transmitter and uses signals transmitted by illuminators of opportunity (IOO), it is a low cost, lightweight, low-power consuming solution perfectly fitting for mobile applications, especially for mounting on a UAV. Moreover, it does not require supplemental frequency allocation and creates no additional interference to existing wireless networks. Longterm evolution (LTE) is a good candidate for illuminators of opportunity (IOO) due to the fact that orthogonal frequency division multiplexing (OFDM) signals are used. Moreover, LTE base stations are widely deployed. In this paper, the detection performance of a drone-mounted passive radar is presented, with various settings in terms of targets, wireless propagation, realistic antenna patterns and signal processing.

This paper evaluates MIMO radio channel measurements at 3.8 GHz, conducted in various urban microcellular environments in the city of Louvain-la-Neuve, Belgium. Large-scale parameters, such as shadow fading, delay and angular spreads as well as dense multipath power are extracted and compared with values provided by existing models. A joint specular-dense multipath cluster-based model is then parametrized from the experimental data, detailing cluster spread and correlation properties.

This paper presents a physical-statistical radio channel power delay profiles model for room-to-room communication systems combining the room electromagnetic theory for modeling deterministic channel components with a geometry-based stochastic channel model with time-variant statistics for modeling stochastic components. The deterministic channel component, i.e., mean power delay spectrum, is comprised of specularly reflected paths plus diffuse components due to scattering and diffraction. The specular components are modeled with a set Dirac function, whereas the diffuse components modeling approach is a room electromagnetic theory-based model. Dynamic indoor communication channels are characterized by a non-stationary time- and delay-fading process due to changes in the environment. We analyze and model the time-delay variability of channels using K-factor for small-scale variations and the t-location scale distribution parameters for large-scale variations. It turns out that these parameters cannot be assumed to be constant in time and delay. After modeling of time-delay variations of the first order statistics, we generate channel realizations with appropriate second order statistics. As the result, the presented model enables to describe the evolution of the power delay profile in the time domain.

In this paper, an experimental performance evaluation is carried out within a communication scenario that features two of the key enablers of 5G: (i) the use of post-OFDM modulations and (ii) an efficient use of the spectrum via spectrum sharing. The experimental lab set-up has been assembled so as to operate in conditions as realistic as possible via the actual realtime implementation of the involved transceivers and also via the utilization of propagation channels which have been recorded in a field measurement campaign and which are loaded in a channel emulator that also operates in real-time. The experimental results show that co-existence in a shared spectrum scenario is possible and that the performance degradation is kept at a low level as long as one of the two users is making use of spectrally agile post-OFDM modulations such as filterbank multicarrier (FBMC).