arXiv subjects

Giorgio Quer

Publications and source records attributed to Giorgio Quer.

4 recordsLinked to original sources

arXiv2025

Channel, Mode and Power Optimization for non-Orthogonal D2D Communications: a Hybrid Approach

The increasing traffic demand in cellular networks has recently led to the investigation of new strategies to save precious resources like spectrum and energy. Direct device-to-device (D2D) communication becomes a promising solution if the two terminals are located in close proximity. In this case, the D2D communications should coexist with cellular transmissions, so they must be carefully scheduled in order to avoid harmful interference impacts. In this paper, we outline a novel framework encompassing channel allocation, mode selection and power control for D2D communications. Power allocation is done in a distributed and cognitive fashion at the beginning of each time slot, based on local information, while channel/mode selection is performed in a centralized manner only at the beginning of an epoch, a time interval including a series of subsequent time slots. This hybrid approach guarantees an effective tradeoff between overhead and adaptivity. We analyze in depth the distributed power allocation mechanism, and we state a theorem which allows to derive the optimal power allocation strategy and to compute the corresponding throughput. Extensive simulations confirm the benefits granted by our approach, when compared with state-of-the-art distributed schemes, in terms of throughput and fairness.

cs.NI↗

arXiv2024

The Minimum Information about CLinical Artificial Intelligence Checklist for Generative Modeling Research (MI-CLAIM-GEN)

Recent advances in generative models, including large language models (LLMs), vision language models (VLMs), and diffusion models, have accelerated the field of natural language and image processing in medicine and marked a significant paradigm shift in how biomedical models can be developed and deployed. While these models are highly adaptable to new tasks, scaling and evaluating their usage presents new challenges not addressed in previous frameworks. In particular, the ability of these models to produce useful outputs with little to no specialized training data ("zero-" or "few-shot" approaches), as well as the open-ended nature of their outputs, necessitate the development of new guidelines for robust reporting of clinical generative model research. In response to gaps in standards and best practices for the development of clinical AI tools identified by US Executive Order 141103 and several emerging national networks for clinical AI evaluation, we begin to formalize some of these guidelines by building on the original MI-CLAIM checklist. The new checklist, MI-CLAIM-GEN (Table 1), aims to address differences in training, evaluation, interpretability, and reproducibility of new generative models compared to non-generative ("predictive") AI models. This MI-CLAIM-GEN checklist also seeks to clarify cohort selection reporting with unstructured clinical data and adds additional items on alignment with ethical standards for clinical AI research.

cs.CL↗

arXiv2017

Optimal Context Aware Transmission Strategy for non-Orthogonal D2D Communications

The increasing traffic demand in cellular networks has recently led to the investigation of new strategies to save precious resources like spectrum and energy. A possible solution employs direct device-to-device (D2D) communications, which is particularly promising when the two terminals involved in the communications are located in close proximity. The D2D communications should coexist with other transmissions, so they must be careful scheduled in order to avoid harmful interference impacts. In this paper, we analyze how a distributed context-awareness, obtained by observing few local channel and topology parameters, can be used to adaptively exploit D2D communications. We develop a rigorous theoretical analysis to quantify the balance between the gain offered by a D2D transmission, and its impact on the other network communications. Based on this analysis, we derive two theorems that define the optimal strategy to be employed, in terms of throughput maximization, when a single or multiple transmit power levels are available for the D2D communications. We compare this strategy to the state-of-the-art in the same network scenario, showing how context awareness can be exploited to achieve a higher sum throughput and an improved fairness.

cs.NI↗

arXiv2016

Mobile Relays for Smart Cities: Mathematical Proofs

The increasing number of connected vehicles in densely populated urban areas provides an interesting opportunity to counteract the high wireless data demands in high density and highly mobile scenarios. The idea is to support the macro base station (BS) with a secondary communication tier composed of a set of smart and connected vehicles that are in movement in the urban area. As a first step towards a comprehensive cost-benefit analysis of this architecture, this paper considers the case where these vehicles are equipped with femto-mobile Access Points (fmAPs) and constitute a mobile out-of-band relay infrastructure. In particular, three techniques to select an fmAP (if more than one is available) are proposed and the maximal feasible gain in the packet delivery rate and data rate as a function of the vehicle density, average vehicle speeds, handoff overhead cost, as well as physical layer parameters is characterized. The analytical and simulation results provide a first benchmark characterizing this architecture and the definition of guidelines for its future realistic study and implementation.

cs.IT↗