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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2406.14126 |
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| _version_ | 1866909228092882944 |
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| author | Andersson, Martin Vu, Tung T. Frenger, Pål Larsson, Erik G. |
| author_facet | Andersson, Martin Vu, Tung T. Frenger, Pål Larsson, Erik G. |
| contents | We consider a cell-free massive multiple-input multiple-output (CFmMIMO) network operating in dynamic time division duplex (DTDD). The switching point between the uplink (UL) and downlink (DL) data transmission phases can be adapted dynamically to the instantaneous quality-of-service (QoS) requirements in order to improve energy efficiency (EE). To this end, we formulate a problem of optimizing the DTDD switching point jointly with the UL and DL power control coefficients, and the large-scale fading decoding (LSFD) weights for EE maximization. Then, we propose an iterative algorithm to solve the formulated challenging problem using successive convex approximation with an approximate stationary solution. Simulation results show that optimizing switching points remarkably improves EE compared with baseline schemes that adjust switching points heuristically. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_14126 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Joint Optimization of Switching Point and Power Control in Dynamic TDD Cell-Free Massive MIMO Andersson, Martin Vu, Tung T. Frenger, Pål Larsson, Erik G. Signal Processing Information Theory We consider a cell-free massive multiple-input multiple-output (CFmMIMO) network operating in dynamic time division duplex (DTDD). The switching point between the uplink (UL) and downlink (DL) data transmission phases can be adapted dynamically to the instantaneous quality-of-service (QoS) requirements in order to improve energy efficiency (EE). To this end, we formulate a problem of optimizing the DTDD switching point jointly with the UL and DL power control coefficients, and the large-scale fading decoding (LSFD) weights for EE maximization. Then, we propose an iterative algorithm to solve the formulated challenging problem using successive convex approximation with an approximate stationary solution. Simulation results show that optimizing switching points remarkably improves EE compared with baseline schemes that adjust switching points heuristically. |
| title | Joint Optimization of Switching Point and Power Control in Dynamic TDD Cell-Free Massive MIMO |
| topic | Signal Processing Information Theory |
| url | https://arxiv.org/abs/2406.14126 |