Power Control and Clustering for Terrestrial and Aerial Users in D-MIMO Networks

While the majority of the D-MIMO studies consider dedicated networks serving only terrestrial users, this paper investigates the cluster formation and data power control problems for the uplink of D-MIMO networks that simultaneously serve terrestrial and aerial users. In this context, we formulate optimization models for mobile networks to improve three main areas: minimum and total spectral efficiency, as well as total energy efficiency, ensuring an all-around enhancement of network performance. Due to the combinatorial nature of the formulated non-linear programming problems, we solve these problems following a two-step procedure. The first stage employs a simple and suboptimal method for decentralized cluster formation, while the second stage advances to sophisticated centralized power control algorithms, utilizing strategies from convex optimization and fractional programming theories. In our analysis, we comprehensively examine the impact of aerial user mobility on optimization metrics, assessing the effectiveness of power control versus traditional solutions in scenarios involving mobility.

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Publication Details

Published
2024-12-12
DOI
https://doi.org/10.1109/wcnps65035.2024.10814221
Primary Topic
Advanced MIMO Systems Optimization
Type
article
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article

Power Control and Clustering for Terrestrial and Aerial Users in D-MIMO Networks

Gábor Fodor, Juno V. Saraiva, Yuri C. B. Silva, Roberto P. Antonioli et al.
Advanced MIMO Systems Optimization
article

Power Control and Clustering for Terrestrial and Aerial Users in D-MIMO Networks

Gábor Fodor, Juno V. Saraiva, Yuri C. B. Silva, Roberto P. Antonioli, Walter C. Freitas
article en

Abstract

While the majority of the D-MIMO studies consider dedicated networks serving only terrestrial users, this paper investigates the cluster formation and data power control problems for the uplink of D-MIMO networks that simultaneously serve terrestrial and aerial users. In this context, we formulate optimization models for mobile networks to improve three main areas: minimum and total spectral efficiency, as well as total energy efficiency, ensuring an all-around enhancement of network performance. Due to the combinatorial nature of the formulated non-linear programming problems, we solve these problems following a two-step procedure. The first stage employs a simple and suboptimal method for decentralized cluster formation, while the second stage advances to sophisticated centralized power control algorithms, utilizing strategies from convex optimization and fractional programming theories. In our analysis, we comprehensively examine the impact of aerial user mobility on optimization metrics, assessing the effectiveness of power control versus traditional solutions in scenarios involving mobility.

Ericsson (Sweden) (SE)
Affordable and clean energy
Openalex Percentile: Top 77%
Advanced MIMO Systems Optimization
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