Beamforming Design for Integrated Sensing and Communications Using Uplink-Downlink Duality
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arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866916215182589952 |
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| author | Attiah, Kareem M. Yu, Wei |
| author_facet | Attiah, Kareem M. Yu, Wei |
| contents | This paper presents a novel optimization framework for beamforming design in integrated sensing and communication systems where a base station seeks to minimize the Bayesian Cramér-Rao bound of a sensing problem while satisfying quality of service constraints for the communication users. Prior approaches formulate the design problem as a semidefinite program for which acquiring a beamforming solution is computationally expensive. In this work, we show that the computational burden can be considerably alleviated. To achieve this, we transform the design problem to a tractable form that not only provides a new understanding of Cramér-Rao bound optimization, but also allows for an uplink-downlink duality relation to be developed. Such a duality result gives rise to an efficient algorithm that enables the beamforming design problem to be solved at a much lower complexity as compared to the-state-of-the-art methods. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_13392 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Beamforming Design for Integrated Sensing and Communications Using Uplink-Downlink Duality Attiah, Kareem M. Yu, Wei Information Theory Signal Processing Optimization and Control This paper presents a novel optimization framework for beamforming design in integrated sensing and communication systems where a base station seeks to minimize the Bayesian Cramér-Rao bound of a sensing problem while satisfying quality of service constraints for the communication users. Prior approaches formulate the design problem as a semidefinite program for which acquiring a beamforming solution is computationally expensive. In this work, we show that the computational burden can be considerably alleviated. To achieve this, we transform the design problem to a tractable form that not only provides a new understanding of Cramér-Rao bound optimization, but also allows for an uplink-downlink duality relation to be developed. Such a duality result gives rise to an efficient algorithm that enables the beamforming design problem to be solved at a much lower complexity as compared to the-state-of-the-art methods. |
| title | Beamforming Design for Integrated Sensing and Communications Using Uplink-Downlink Duality |
| topic | Information Theory Signal Processing Optimization and Control |
| url | https://arxiv.org/abs/2404.13392 |