Detecting Multiple Targets with Distributed Sensing and Communication in Cell-Free Massive MIMO
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866918102720053248 |
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| author | Behdad, Zinat Demir, Ozlem Tugfe Sung, Ki Won Cavdar, Cicek |
| author_facet | Behdad, Zinat Demir, Ozlem Tugfe Sung, Ki Won Cavdar, Cicek |
| contents | This paper investigates multi-target detection in an integrated sensing and communication (ISAC) system within a cell-free massive MIMO (CF-mMIMO) framework. We adopt a user-centric approach for communication user equipments (UEs) and a distributed sensing approach for multi-target detection. A heuristic access point (AP) mode selection algorithm and a channel-aware distributed sensing scheme are proposed, where local measurements at receive APs (RX-APs) are weighted based on the received signals signal-to-interference ratio (SIR). A maximum a posteriori ratio test (MAPRT) detector is applied under two awareness levels at RX-APs. To balance the communication-sensing trade-off, we develop a power allocation algorithm to jointly maximize the minimum detection probability and communication signal-to-interference-plus-noise ratio (SINR) while satisfying power constraints. The proposed scheme outperforms non-weighted methods. Adding test statistics from more RX-APs can degrade sensing performance due to weaker channels, but this effect can be mitigated by optimizing the weighting exponent. Additionally, assigning more sensing RX-APs to a sensing area results in approximately 10 dB loss in minimum communication SINR due to limited communication resources. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_17441 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Detecting Multiple Targets with Distributed Sensing and Communication in Cell-Free Massive MIMO Behdad, Zinat Demir, Ozlem Tugfe Sung, Ki Won Cavdar, Cicek Signal Processing This paper investigates multi-target detection in an integrated sensing and communication (ISAC) system within a cell-free massive MIMO (CF-mMIMO) framework. We adopt a user-centric approach for communication user equipments (UEs) and a distributed sensing approach for multi-target detection. A heuristic access point (AP) mode selection algorithm and a channel-aware distributed sensing scheme are proposed, where local measurements at receive APs (RX-APs) are weighted based on the received signals signal-to-interference ratio (SIR). A maximum a posteriori ratio test (MAPRT) detector is applied under two awareness levels at RX-APs. To balance the communication-sensing trade-off, we develop a power allocation algorithm to jointly maximize the minimum detection probability and communication signal-to-interference-plus-noise ratio (SINR) while satisfying power constraints. The proposed scheme outperforms non-weighted methods. Adding test statistics from more RX-APs can degrade sensing performance due to weaker channels, but this effect can be mitigated by optimizing the weighting exponent. Additionally, assigning more sensing RX-APs to a sensing area results in approximately 10 dB loss in minimum communication SINR due to limited communication resources. |
| title | Detecting Multiple Targets with Distributed Sensing and Communication in Cell-Free Massive MIMO |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2507.17441 |