Direct-to-Device (D2D) satellite communications—where standard mobile devices connect directly with satellites—offer a promising solution to extend coverage and improve network resilience. This paper examines the spectrum allocation and regulatory challenges of enabling D2D satellite services in the European Union (EU), situating the analysis within the broader evolution of International Telecommunication Union (ITU) regulatory processes. While anchored in the preparations for the World Radiocommunication Conference 2027 (WRC-27), the study emphasizes that regulatory developments are dynamic and extend beyond a single conference cycle, ensuring long-term relevance for spectrum governance. The paper provides an overview of satellite communication fundamentals and defines key D2D concepts, including Internet of Things (IoT) use cases and differences between terrestrial mobile bands and Mobile-Satellite Service (MSS) bands. The analysis highlights the current EU landscape for MSS spectrum, particularly the 2 GHz S-band, and its upcoming licensing challenges. It contrasts the EU approach with international developments—notably the United States’ new “Supplemental Coverage from Space” framework and the United Kingdom’s satellite-to-mobile integration plans—to draw lessons for spectrum-sharing models. Technical and regulatory challenges for integrating D2D are identified, and potential alternative frequency bands and spectrum-sharing techniques are explored. A policy roadmap is proposed, outlining short-, medium-, and long-term actions for EU policymakers and stakeholders to enable D2D services. The study ultimately supports the formulation of a forward-looking regulatory framework that secures Europe’s role in shaping the future of hybrid satellite-terrestrial connectivity.

Radio spectrum is a limited national resource whose efficient utilization is of strategic importance. With the rapid advancement of wireless technologies, maintaining spectrum cleanliness and enabling fast and reliable anomaly detection have become critical challenges. Artificial intelligence (AI)-based approaches have recently shown great promise in addressing these issues; however, their effectiveness strongly depends on the availability of high-quality, representative, and annotated datasets. Generating such datasets is a complex task, further complicated by environmental conditions such as weather. Hungary’s nationwide spectrum monitoring network enables continuous observation of frequency bands, thereby providing the opportunity to construct large-scale and sustainable datasets. This study introduces a measurement methodology designed for the FM sound broadcasting in the VHF band (87.5–108 MHz), presents the resulting dataset, and details the annotation process. The published, openly accessible dataset is expected to serve not only as a valuable reference point but also as a benchmark for the international research community, facilitating the development, validation, and objective comparison of AI-driven spectrum monitoring solutions.

Direct-to-device satellite services are creating a new spectrum-sharing problem in frequency bands historically used by terrestrial mobile networks. The central policy question is how administrations can authorize satellite connectivity to conventional mobile devices while protecting incumbent International Mobile Telecommunications (IMT) networks, particularly in cross-border and co-channel operating conditions. This article develops a technically grounded regulatory framework for translating satellite-terrestrial coexistence analysis into implementable protection conditions. The framework distinguishes between aggregate Power Flux-Density (PFD), used to protect mobile user equipment, and aggregate Equivalent Power Flux-Density (EPFD), used to protect directional base-station receivers. These metrics are linked to a long-term interference-to-noise protection criterion and evaluated through deterministic derivation and Monte Carlo simulation. Four representative cross-border scenarios are examined, covering unmanaged and managed downlink and uplink operation. The results show that unmanaged operation can exceed terrestrial protection limits, especially where satellite-connected user equipment transmits close to terrestrial base stations. They also show that coexistence can be feasible under the stated assumptions when aggregate limits are combined with operational safeguards such as beam-power reduction, user-equipment power control, geographic separation, and coordination procedures. The article argues that aggregate interference metrics should be treated not only as engineering quantities but also as regulatory instruments for spectrum governance. The findings support a differentiated policy approach that links receiver-specific protection limits, compliance verification, cross-border coordination, and operator obligations for direct-to-device satellite deployment.

This paper presents a study of three machine-learning approaches for anomaly analysis in spectrum-monitoring data from VHF Band II radio broadcasting. Spectrum anomalies are defined as deviations from expected spectral behavior, including unexpected signal emissions, interference, and irregular variations in signal characteristics. A supervised YOLO-based object detector was evaluated for anomaly localization using independently produced expert annotations, while convolutional autoencoder-based clustering and long short-term memory (LSTM) prediction were investigated for exploratory spectral and temporal analysis, respectively. The supervised experiments examined both within-annotator and cross-annotator performance, whereas the unsupervised and temporal approaches were assessed qualitatively. The autoencoder-based approach revealed recurring spectral structures in latent space, and the LSTM model identified deviations from the recent behavior of individual broadcast transmissions. The principal quantitative results showed within-annotator $F_1$ scores ranging from 0.85 to 0.94, compared with 0.34 to 0.77 in cross-annotator evaluations. These findings indicate that the reported anomaly localization performance is sensitive to the reference annotations, highlighting the importance of annotation consistency and independent evaluation in spectrum-monitoring applications.