Joint Subarray Selection, User Scheduling, and Pilot Assignment for XL-MIMO
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866909995464916992 |
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| author | Ubiali, Gabriel Avanzi Filho, José Carlos Marinello Abrão, Taufik |
| author_facet | Ubiali, Gabriel Avanzi Filho, José Carlos Marinello Abrão, Taufik |
| contents | Extra-large scale MIMO (XL-MIMO) is a key technology for meeting sixth-generation (6G) requirements for high-rate connectivity and uniform quality of service (QoS); however, its deployment is challenged by the prohibitive complexity of resource management based on instantaneous channel state information (CSI). To address this intractability, this work derives novel closed-form deterministic signal-to-interference-plus-noise ratio (SINR) expressions for both centralized and distributed uplink operations. Valid for Rician fading channels with minimum mean square error (MMSE) receive combining and MMSE channel estimation, these expressions depend exclusively on long-term channel statistics, providing a tractable alternative to computationally expensive instantaneous CSI-driven optimization. Building on these results, we develop statistical-CSI-based algorithms for joint subarray selection, users scheduling, and pilot assignment, leveraging the derived SINR approximations to maximize the minimum spectral efficiency (SE) among scheduled users while preserving computational tractability. The proposed framework exploits the spatial sparsity of user equipment (UE) visibility regions (VRs) to enable more aggressive pilot reuse than is possible in conventional massive MIMO. Numerical results validate the high accuracy of the derived SINR approximations and demonstrate that the proposed algorithms significantly enhance fairness and throughput in crowded scenarios. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_13470 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Joint Subarray Selection, User Scheduling, and Pilot Assignment for XL-MIMO Ubiali, Gabriel Avanzi Filho, José Carlos Marinello Abrão, Taufik Signal Processing Extra-large scale MIMO (XL-MIMO) is a key technology for meeting sixth-generation (6G) requirements for high-rate connectivity and uniform quality of service (QoS); however, its deployment is challenged by the prohibitive complexity of resource management based on instantaneous channel state information (CSI). To address this intractability, this work derives novel closed-form deterministic signal-to-interference-plus-noise ratio (SINR) expressions for both centralized and distributed uplink operations. Valid for Rician fading channels with minimum mean square error (MMSE) receive combining and MMSE channel estimation, these expressions depend exclusively on long-term channel statistics, providing a tractable alternative to computationally expensive instantaneous CSI-driven optimization. Building on these results, we develop statistical-CSI-based algorithms for joint subarray selection, users scheduling, and pilot assignment, leveraging the derived SINR approximations to maximize the minimum spectral efficiency (SE) among scheduled users while preserving computational tractability. The proposed framework exploits the spatial sparsity of user equipment (UE) visibility regions (VRs) to enable more aggressive pilot reuse than is possible in conventional massive MIMO. Numerical results validate the high accuracy of the derived SINR approximations and demonstrate that the proposed algorithms significantly enhance fairness and throughput in crowded scenarios. |
| title | Joint Subarray Selection, User Scheduling, and Pilot Assignment for XL-MIMO |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2601.13470 |