04 CONTRIBUTO IN ATTO DI CONVEGNO

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Geometry and Wideband Performance of a Maximal Ratio Combining Beam

This paper discusses the geometrical features and wideband performance of the beam with maximal ratio combining coefficients for a generic multi-antenna receiver. In particular, in case the channel is a linear combination of plane waves, we show that such a beam can be decomposed in a linear combination of beams pointed in the direction of each plane wave, and we compute how many directions can be effectively utilized. This highlights that such a beam is better exploiting the spatial diversit...

On the Limits of Digital Twins for Safe Deep Reinforcement Learning in Robotic Networks

Successfully training models which address the complex nature of real environments in Smart Cities and robotic networks is challenging, due to the vast amount of data needed. When employing Reinforcement Learning (RL) models, it is also impossible to let them explore all the actions in the real world, due to potential damages and inappropriate actions. The inherent trial-and-error nature of RL, especially in real-world applications like traffic management, makes an integration with Digital Tw...

Impact of Realistic GNSS Location Errors on REM-Based Beam Management in Urban Millimeter-Wave Networks

Millimeter-wave (mm-wave) is envisioned to provide seamless multi-Gbps connectivity for future cellular networks and relies on directional links to overcome the high path and penetration loss and the spatially sparse nature of the mm-wave channel. Initial access and seamless mobile connectivity thus require active and precise alignment of the directional antenna beams between the base station and user equipment, which imposes a significant overhead. To address this, context-aware beam managem...

Push- and Pull-based Effective Communication in Cyber-Physical Systems

In Cyber-Physical Systems (CPSs), two groups of actors interact toward the maximization of system performance: the sensors, observing and disseminating the system state, and the actuators, performing physical decisions based on the received information. While it is generally assumed that sensors periodically transmit updates, returning the feedback signal only when necessary, and consequently adapting the physical decisions to the communication policy, can significantly improve the efficiency...

Find the Lady: Permutation and Re-synchronization of Deep Neural Networks

Deep neural networks are characterized by multiple symmetrical, equi-loss solutions that are redundant. Thus, the order of neurons in a layer and feature maps can be given arbitrary permutations, without affecting (or minimally affecting) their output. If we shuffle these neurons, or if we apply to them some perturbations (like fine-tuning) can we put them back in the original order i.e. re-synchronize? Is there a possible corruption threat? Answering these questions is important for applicat...

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