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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2601.21010 |
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| _version_ | 1866912857595052032 |
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| author | Cao, Xiaomin Mohammadi, Mohammadali Ngo, Hien Quoc Matthaiou, Michail |
| author_facet | Cao, Xiaomin Mohammadi, Mohammadali Ngo, Hien Quoc Matthaiou, Michail |
| contents | In this paper, we consider power consumption reduction in extremely large antenna arrays (ELAAs) for integrated sensing and communication (ISAC) applications. Although ELAAs are critical for achieving high-resolution near-field sensing, fully activating all antenna elements in conventional digital architectures leads to prohibitive power demands. To address this, we propose an energy-efficient subarray activation framework that selects an optimal subset of subarrays to minimize the total power consumption, subject to quality-of-service (QoS) constraints for both sensing and communication. We formulate a novel optimization problem and solve it using a successive convex approximation (SCA)-based iterative algorithm. The simulation results confirm that the proposed method significantly reduces power consumption while maintaining dual-function performance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_21010 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Power consumption Reduction in ELAA-Assisted ISAC Systems Cao, Xiaomin Mohammadi, Mohammadali Ngo, Hien Quoc Matthaiou, Michail Information Theory In this paper, we consider power consumption reduction in extremely large antenna arrays (ELAAs) for integrated sensing and communication (ISAC) applications. Although ELAAs are critical for achieving high-resolution near-field sensing, fully activating all antenna elements in conventional digital architectures leads to prohibitive power demands. To address this, we propose an energy-efficient subarray activation framework that selects an optimal subset of subarrays to minimize the total power consumption, subject to quality-of-service (QoS) constraints for both sensing and communication. We formulate a novel optimization problem and solve it using a successive convex approximation (SCA)-based iterative algorithm. The simulation results confirm that the proposed method significantly reduces power consumption while maintaining dual-function performance. |
| title | Power consumption Reduction in ELAA-Assisted ISAC Systems |
| topic | Information Theory |
| url | https://arxiv.org/abs/2601.21010 |