Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2405.07013 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866914793246425088 |
|---|---|
| author | Demir, Özlem Tuğfe Méndez-Monsanto, Lianet Bastianello, Nicola Fitzgerald, Emma Callebaut, Gilles |
| author_facet | Demir, Özlem Tuğfe Méndez-Monsanto, Lianet Bastianello, Nicola Fitzgerald, Emma Callebaut, Gilles |
| contents | The physical layer foundations of cell-free massive MIMO (CF-mMIMO) have been well-established. As a next step, researchers are investigating practical and energy-efficient network implementations. This paper focuses on multiple sets of access points (APs) where user equipments (UEs) are served in each set, termed a federation, without inter-federation interference. The combination of federations and CF-mMIMO shows promise for highly-loaded scenarios. Our aim is to minimize the total energy consumption while adhering to UE downlink data rate constraints. The energy expenditure of the full system is modelled using a detailed hardware model of the APs. We jointly design the AP-UE association variables, determine active APs, and assign APs and UEs to federations. To solve this highly combinatorial problem, we develop a novel alternating optimization algorithm. Simulation results for an indoor factory demonstrate the advantages of considering multiple federations, particularly when facing large data rate requirements. Furthermore, we show that adopting a more distributed CF-mMIMO architecture is necessary to meet the data rate requirements. Conversely, if feasible, using a less distributed system with more antennas at each AP is more advantageous from an energy savings perspective. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_07013 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Energy Reduction in Cell-Free Massive MIMO through Fine-Grained Resource Management Demir, Özlem Tuğfe Méndez-Monsanto, Lianet Bastianello, Nicola Fitzgerald, Emma Callebaut, Gilles Signal Processing Information Theory The physical layer foundations of cell-free massive MIMO (CF-mMIMO) have been well-established. As a next step, researchers are investigating practical and energy-efficient network implementations. This paper focuses on multiple sets of access points (APs) where user equipments (UEs) are served in each set, termed a federation, without inter-federation interference. The combination of federations and CF-mMIMO shows promise for highly-loaded scenarios. Our aim is to minimize the total energy consumption while adhering to UE downlink data rate constraints. The energy expenditure of the full system is modelled using a detailed hardware model of the APs. We jointly design the AP-UE association variables, determine active APs, and assign APs and UEs to federations. To solve this highly combinatorial problem, we develop a novel alternating optimization algorithm. Simulation results for an indoor factory demonstrate the advantages of considering multiple federations, particularly when facing large data rate requirements. Furthermore, we show that adopting a more distributed CF-mMIMO architecture is necessary to meet the data rate requirements. Conversely, if feasible, using a less distributed system with more antennas at each AP is more advantageous from an energy savings perspective. |
| title | Energy Reduction in Cell-Free Massive MIMO through Fine-Grained Resource Management |
| topic | Signal Processing Information Theory |
| url | https://arxiv.org/abs/2405.07013 |