Energy Efficiency Optimization in Integrated Satellite-Terrestrial UAV-Enabled Cell-Free Massive MIMO

TL;DR

This paper proposes an algorithm to optimize energy efficiency in satellite-UAV integrated networks with cell-free massive MIMO, demonstrating significant spectral efficiency improvements with a small number of UAVs.

Contribution

It introduces a successive convex approximation algorithm for energy efficiency maximization in UAV-based CF-mMIMO networks, considering practical power and QoS constraints.

Findings

The algorithm effectively maximizes UAV layer energy efficiency.

A small number of UAVs with optimized power can significantly enhance satellite network performance.

Simulation results confirm the algorithm's effectiveness in real-world scenarios.

Abstract

Integrating cell-free massive MIMO (CF-mMIMO) into satellite-unmanned aerial vehicle (UAV) networks offers an effective solution for enhancing connectivity. In this setup, UAVs serve as access points (APs) of a terrestrial CF-mMIMO network extending the satellite network capabilities, thereby ensuring robust, high-quality communication links. In this work, we propose a successive convex approximation algorithm for maximizing the downlink energy efficiency (EE) at the UAVs under per-UAV power budget and user quality-of-service constraints. We derive a closed-form expression for the EE that accounts for maximum-ratio transmission and statistical channel knowledge at the users. Simulation results show the effectiveness of the proposed algorithm in maximizing the EE at the UAV layer. Moreover, we observe that a few tens of UAVs transmitting with a fine-tuned power are sufficient to empower the service of satellite networks and significantly increase the spectral efficiency.