Robust ISAC Transceiver Beamforming Design under Low-Resolution AD/DA Converters
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2025
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866916853042905088 |
|---|---|
| author | Xu, Tiantian He, Zhenyao Xu, Jindan Xu, Wei Wang, Jianfeng Ng, Derrick Wing Kwan |
| author_facet | Xu, Tiantian He, Zhenyao Xu, Jindan Xu, Wei Wang, Jianfeng Ng, Derrick Wing Kwan |
| contents | In this letter, we investigate the robust beamforming design for an integrated sensing and communication (ISAC) system featuring low-resolution digital-to-analog converters (DACs) and analog-to-digital converters (ADCs). Taking into account quantization noise, we aim at maximizing the radar signal-to-quantization-plus-noise ratio (SQNR) while guaranteeing the minimum required signal-to-quantization-plus-interference-plus-noise ratio (SQINR) for communication users. To address this nonconvex design problem, we first examine a scenario involving a point target and uniform-resolution DACs, where the globally optimal solution is obtained by applying the semidefinite relaxation (SDR) technique. For more general scenarios, including those with mixed-DACs and/or an extended target, we develop a low-complexity majorization-minimization (MM)-based algorithm to tackle the problem iteratively. Compared to the non-robust algorithm, the proposed algorithm demonstrates improved detection performance under practical quantization. Simulation results confirm the robustness and efficacy of our proposed algorithm in low-resolution quantization scenarios. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_15373 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Robust ISAC Transceiver Beamforming Design under Low-Resolution AD/DA Converters Xu, Tiantian He, Zhenyao Xu, Jindan Xu, Wei Wang, Jianfeng Ng, Derrick Wing Kwan Signal Processing In this letter, we investigate the robust beamforming design for an integrated sensing and communication (ISAC) system featuring low-resolution digital-to-analog converters (DACs) and analog-to-digital converters (ADCs). Taking into account quantization noise, we aim at maximizing the radar signal-to-quantization-plus-noise ratio (SQNR) while guaranteeing the minimum required signal-to-quantization-plus-interference-plus-noise ratio (SQINR) for communication users. To address this nonconvex design problem, we first examine a scenario involving a point target and uniform-resolution DACs, where the globally optimal solution is obtained by applying the semidefinite relaxation (SDR) technique. For more general scenarios, including those with mixed-DACs and/or an extended target, we develop a low-complexity majorization-minimization (MM)-based algorithm to tackle the problem iteratively. Compared to the non-robust algorithm, the proposed algorithm demonstrates improved detection performance under practical quantization. Simulation results confirm the robustness and efficacy of our proposed algorithm in low-resolution quantization scenarios. |
| title | Robust ISAC Transceiver Beamforming Design under Low-Resolution AD/DA Converters |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2507.15373 |