Distributed MIMO Networks with Rotary ULAs for Indoor Scenarios under Rician Fading
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866910627906191360 |
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| author | Tominaga, Eduardo Noboro López, Onel Luis Alcaraz Svensson, Tommy Souza, Richard Demo Alves, Hirley |
| author_facet | Tominaga, Eduardo Noboro López, Onel Luis Alcaraz Svensson, Tommy Souza, Richard Demo Alves, Hirley |
| contents | The Fifth-Generation (5G) wireless communications networks introduced native support for Machine-Type Communications (MTC) use cases. Nevertheless, current 5G networks cannot fully meet the very stringent requirements regarding latency, reliability, and number of connected devices of most MTC use cases. Industry and academia have been working on the evolution from 5G to Sixth Generation (6G) networks. One of the main novelties is adopting Distributed Multiple-Input Multiple-Output (D-MIMO) networks. However, most works studying D-MIMO consider antenna arrays with no movement capabilities, even though some recent works have shown that this could bring substantial performance improvements. In this work, we propose the utilization of Access Points (APs) equipped with Rotary Uniform Linear Arrays (RULAs) for this purpose. Considering a spatially correlated Rician fading model, the optimal angular position of the RULAs is jointly computed by the central processing unit using particle swarm optimization as a function of the location of the active devices. Considering the impact of imperfect location estimates, our numerical results show that the RULAs's optimal rotation brings substantial performance gains in terms of mean per-user spectral efficiency. The improvement grows with the strength of the line-of-sight components of the channel vectors. Given the total number of antenna elements, we study the trade-off between the number of APs and the number of antenna elements per AP, revealing an optimal number of APs for the cases of APs equipped with static ULAs and RULAs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_19078 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Distributed MIMO Networks with Rotary ULAs for Indoor Scenarios under Rician Fading Tominaga, Eduardo Noboro López, Onel Luis Alcaraz Svensson, Tommy Souza, Richard Demo Alves, Hirley Signal Processing The Fifth-Generation (5G) wireless communications networks introduced native support for Machine-Type Communications (MTC) use cases. Nevertheless, current 5G networks cannot fully meet the very stringent requirements regarding latency, reliability, and number of connected devices of most MTC use cases. Industry and academia have been working on the evolution from 5G to Sixth Generation (6G) networks. One of the main novelties is adopting Distributed Multiple-Input Multiple-Output (D-MIMO) networks. However, most works studying D-MIMO consider antenna arrays with no movement capabilities, even though some recent works have shown that this could bring substantial performance improvements. In this work, we propose the utilization of Access Points (APs) equipped with Rotary Uniform Linear Arrays (RULAs) for this purpose. Considering a spatially correlated Rician fading model, the optimal angular position of the RULAs is jointly computed by the central processing unit using particle swarm optimization as a function of the location of the active devices. Considering the impact of imperfect location estimates, our numerical results show that the RULAs's optimal rotation brings substantial performance gains in terms of mean per-user spectral efficiency. The improvement grows with the strength of the line-of-sight components of the channel vectors. Given the total number of antenna elements, we study the trade-off between the number of APs and the number of antenna elements per AP, revealing an optimal number of APs for the cases of APs equipped with static ULAs and RULAs. |
| title | Distributed MIMO Networks with Rotary ULAs for Indoor Scenarios under Rician Fading |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2406.19078 |