Energy Efficiency Optimization in Integrated Satellite-Terrestrial UAV-Enabled Cell-Free Massive MIMO
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866909266951012352 |
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| author | Tran, Thong-Nhat Interdonato, Giovanni |
| author_facet | Tran, Thong-Nhat Interdonato, Giovanni |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2407_17321 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Energy Efficiency Optimization in Integrated Satellite-Terrestrial UAV-Enabled Cell-Free Massive MIMO Tran, Thong-Nhat Interdonato, Giovanni Information Theory Signal Processing 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. |
| title | Energy Efficiency Optimization in Integrated Satellite-Terrestrial UAV-Enabled Cell-Free Massive MIMO |
| topic | Information Theory Signal Processing |
| url | https://arxiv.org/abs/2407.17321 |