arXiv subjects

Stefano Andrenacci

Publications and source records attributed to Stefano Andrenacci.

5 recordsLinked to original sources

arXiv2026

Constrained MARL for Coexisting TN-NTN Resource Allocation: Scalability and Flexibility

This paper considers the joint TN-NTN constrained resource allocation, where terrestrial base stations and non-terrestrial base stations coexist in the spectrum. We focus on large-scale and practical scenarios characterized by large numbers of transmission channels and users, alongside highly dynamic user behaviors. As common learning solutions fail to address these challenges, we propose a decomposition solution based on the special properties of the cross-segment interference, and then tackle the original problem via solving subproblems in a sequential learning manner. Furthermore, to enhance the flexibility of the learned policies, we design a stochastic training environment that captures the key characteristics of real-world systems. Simulation results tested on the full 20MHz bandwidth with various numerologies show that our solution significantly improves scalability compared to existing solutions and remains robust in highly dynamic scenarios.

cs.IT↗

arXiv2024

Optimal Linear Precoding Under Realistic Satellite Communications Scenarios

In this paper, optimal linear precoding for the multibeam geostationary earth orbit (GEO) satellite with the multi-user (MU) multiple-input-multiple-output (MIMO) downlink scenario is addressed. Multiple-user interference is one of the major issues faced by the satellites serving the multiple users operating at the common time-frequency resource block in the downlink channel. To mitigate this issue, the optimal linear precoders are implemented at the gateways (GWs). The precoding computation is performed by utilizing the channel state information obtained at user terminals (UTs). The optimal linear precoders are derived considering beamformer update and power control with an iterative per-antenna power optimization algorithm with a limited required number of iterations. The efficacy of the proposed algorithm is validated using the In-Lab experiment for 16X16 precoding with multi-beam satellite for transmitting and receiving the precoded data with digital video broadcasting satellite-second generation extension (DVB- S2X) standard for the GW and the UTs. The software defined radio platforms are employed for emulating the GWs, UTs, and satellite links. The validation is supported by comparing the proposed optimal linear precoder with full frequency reuse (FFR), and minimum mean square error (MMSE) schemes. The experimental results demonstrate that with the optimal linear precoders it is possible to successfully cancel the inter-user interference in the simulated satellite FFR link. Thus, optimal linear precoding brings gains in terms of enhanced signal-to-noise-and-interference ratio, and increased system throughput and spectral efficiency.

eess.SP↗

arXiv2023

ML-based PBCH symbol detection and equalization for 5G Non-Terrestrial Networks

This paper delves into the application of Machine Learning (ML) techniques in the realm of 5G Non-Terrestrial Networks (5G-NTN), particularly focusing on symbol detection and equalization for the Physical Broadcast Channel (PBCH). As 5G-NTN gains prominence within the 3GPP ecosystem, ML offers significant potential to enhance wireless communication performance. To investigate these possibilities, we present ML-based models trained with both synthetic and real data from a real 5G over-the-satellite testbed. Our analysis includes examining the performance of these models under various Signal-to-Noise Ratio (SNR) scenarios and evaluating their effectiveness in symbol enhancement and channel equalization tasks. The results highlight the ML performance in controlled settings and their adaptability to real-world challenges, shedding light on the potential benefits of the application of ML in 5G-NTN.

eess.SP↗

arXiv2021

End-to-end Precoding Validation over a Live GEO Satellite Forward Link

In this paper we demonstrate end-to-end precoded multi-user multiple-input single-output (MU-MISO) communications over a live GEO satellite link. Precoded communications enable full frequency reuse (FFR) schemes in satellite communications (SATCOM) to achieve broader service availability and higher spectrum efficiency than with the conventional four-color (4CR) and two-color (2CR) reuse approaches. In this scope, we develop an over-the-air test-bed for end-to-end precoding validations. We use an actual multi-beam satellite to transmit and receive precoded signals using the DVB-S2X standard based gateway and user terminals. The developed system is capable of end-to-end real-time communications over the satellite link including channel measurements and precompensation. It is shown, that by successfully canceling inter-user interference in the actual satellite FFR link precoding brings gains in terms of enhanced SINR and increased system goodput.

cs.IT↗

arXiv2015

DVB-S2x Enabled Precoding for High Throughput Satellite Systems

Multi-user Multiple-Input Multiple-Output (MU-MIMO) has allowed recent releases of terrestrial LTE standards to achieve significant improvements in terms of offered system capacity. The publications of the DVB-S2x standard and particularly of its novel superframe structure is a key enabler for applying similar interference management techniques -such as precoding- to multibeam High Throughput Satellite (HTS) systems. This paper presents results resulting from European Space Agency (ESA) funded R&D activities concerning the practical issues that arise when precoding is applied over an aggressive frequency re-use HTS network. In addressing these issues, the paper also proposes pragmatic solutions that have been developed in order to overcome these limitations. Through the application of a comprehensive system simulator, it is demonstrated that important capacity gains (beyond 40%) are to be expected from applying precoding even after introducing a number of significant practical impairments.

cs.IT↗