Fairness-Aware Secure Integrated Sensing and Communications with Fractional Programming
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arXiv
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| Autores principales: | , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866913942684565504 |
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| author | Boroujeni, Ali Khandan Ranasinghe, Kuranage Roche Rayan de Abreu, Giuseppe Thadeu Freitas Köpsell, Stefan Bagheri, Ghazal Schaefer, Rafael F. |
| author_facet | Boroujeni, Ali Khandan Ranasinghe, Kuranage Roche Rayan de Abreu, Giuseppe Thadeu Freitas Köpsell, Stefan Bagheri, Ghazal Schaefer, Rafael F. |
| contents | We propose a novel secure integrated sensing and communications (ISAC) system designed to serve multiple communication users (CUs) and targets. To that end, we formulate an optimization problem that maximizes the secrecy rate under constraints balancing both communication and sensing requirements. To enhance fairness among users, an entropy-regularized fairness metric is introduced within the problem framework. We then propose a solution employing an accelerated quadratic transform (QT) with a non-homogeneous bound to iteratively solve two subproblems, thereby effectively optimizing the overall objective. This approach ensures robust security and fairness in resource allocation for ISAC systems. Finally, simulation results verify the performance gains in terms of average secrecy rate, average data rate, and beam gain. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_11224 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Fairness-Aware Secure Integrated Sensing and Communications with Fractional Programming Boroujeni, Ali Khandan Ranasinghe, Kuranage Roche Rayan de Abreu, Giuseppe Thadeu Freitas Köpsell, Stefan Bagheri, Ghazal Schaefer, Rafael F. Signal Processing We propose a novel secure integrated sensing and communications (ISAC) system designed to serve multiple communication users (CUs) and targets. To that end, we formulate an optimization problem that maximizes the secrecy rate under constraints balancing both communication and sensing requirements. To enhance fairness among users, an entropy-regularized fairness metric is introduced within the problem framework. We then propose a solution employing an accelerated quadratic transform (QT) with a non-homogeneous bound to iteratively solve two subproblems, thereby effectively optimizing the overall objective. This approach ensures robust security and fairness in resource allocation for ISAC systems. Finally, simulation results verify the performance gains in terms of average secrecy rate, average data rate, and beam gain. |
| title | Fairness-Aware Secure Integrated Sensing and Communications with Fractional Programming |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2507.11224 |