Multiobjective-Optimization-Based Transmit Beamforming for Multitarget and Multiuser MIMO-ISAC Systems Article Swipe
Chunwei Meng
,
Zhiqing Wei
,
Dingyou Ma
,
Wanli Ni
,
Liyan Su
,
Zhiyong Feng
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1109/jiot.2024.3413687
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1109/jiot.2024.3413687
Integrated sensing and communication (ISAC) is an enabling technology for the\nsixth-generation mobile communications, which equips the wireless communication\nnetworks with sensing capabilities. In this paper, we investigate transmit\nbeamforming design for multiple-input and multiple-output (MIMO)-ISAC systems\nin scenarios with multiple radar targets and communication users. A general\nform of multi-target sensing mutual information (MI) is derived, along with its\nupper bound, which can be interpreted as the sum of individual single-target\nsensing MI. Additionally, this upper bound can be achieved by suppressing the\ncross-correlation among reflected signals from different targets, which aligns\nwith the principles of adaptive MIMO radar. Then, we propose a multi-objective\noptimization framework based on the signal-to-interference-plus-noise ratio of\neach user and the tight upper bound of sensing MI, introducing the Pareto\nboundary to characterize the achievable communication-sensing performance\nboundary of the proposed ISAC system. To achieve the Pareto boundary, the\nmax-min system utility function method is employed, while considering the\nfairness between communication users and radar targets. Subsequently, the\nbisection search method is employed to find a specific Pareto optimal solution\nby solving a series of convex feasible problems. Finally, simulation results\nvalidate that the proposed method achieves a better tradeoff between multi-user\ncommunication and multi-target sensing performance. Additionally, utilizing the\ntight upper bound of sensing MI as a performance metric can enhance the\nmulti-target resolution capability and angle estimation accuracy.\n
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1109/jiot.2024.3413687
- OA Status
- green
- Cited By
- 14
- References
- 46
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4396986789
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4396986789Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1109/jiot.2024.3413687Digital Object Identifier
- Title
-
Multiobjective-Optimization-Based Transmit Beamforming for Multitarget and Multiuser MIMO-ISAC SystemsWork title
- Type
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preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2024Year of publication
- Publication date
-
2024-06-13Full publication date if available
- Authors
-
Chunwei Meng, Zhiqing Wei, Dingyou Ma, Wanli Ni, Liyan Su, Zhiyong FengList of authors in order
- Landing page
-
https://doi.org/10.1109/jiot.2024.3413687Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2405.09022Direct OA link when available
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Beamforming, MIMO, Computer science, Upper and lower bounds, Metric (unit), Radar, Electronic engineering, Real-time computing, Telecommunications, Engineering, Mathematics, Mathematical analysis, Operations managementTop concepts (fields/topics) attached by OpenAlex
- Cited by
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14Total citation count in OpenAlex
- Citations by year (recent)
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2025: 11, 2024: 3Per-year citation counts (last 5 years)
- References (count)
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46Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.method | 135, 150, 173 |
| abstract_inverted_index.metric | 195 |
| abstract_inverted_index.mobile | 11 |
| abstract_inverted_index.mutual | 47 |
| abstract_inverted_index.paper, | 23 |
| abstract_inverted_index.radar. | 90 |
| abstract_inverted_index.search | 149 |
| abstract_inverted_index.series | 162 |
| abstract_inverted_index.system | 132 |
| abstract_inverted_index.users. | 41 |
| abstract_inverted_index.achieve | 127 |
| abstract_inverted_index.between | 141, 178 |
| abstract_inverted_index.enhance | 197 |
| abstract_inverted_index.optimal | 158 |
| abstract_inverted_index.propose | 93 |
| abstract_inverted_index.sensing | 1, 19, 46, 110, 182, 190 |
| abstract_inverted_index.signals | 79 |
| abstract_inverted_index.solving | 160 |
| abstract_inverted_index.system. | 125 |
| abstract_inverted_index.targets | 38 |
| abstract_inverted_index.utility | 133 |
| abstract_inverted_index.Finally, | 167 |
| abstract_inverted_index.achieved | 73 |
| abstract_inverted_index.achieves | 174 |
| abstract_inverted_index.adaptive | 88 |
| abstract_inverted_index.derived, | 51 |
| abstract_inverted_index.employed | 152 |
| abstract_inverted_index.enabling | 7 |
| abstract_inverted_index.feasible | 165 |
| abstract_inverted_index.function | 134 |
| abstract_inverted_index.multiple | 36 |
| abstract_inverted_index.of\neach | 102 |
| abstract_inverted_index.proposed | 123, 172 |
| abstract_inverted_index.specific | 156 |
| abstract_inverted_index.targets, | 82 |
| abstract_inverted_index.targets. | 146 |
| abstract_inverted_index.tradeoff | 177 |
| abstract_inverted_index.wireless | 16 |
| abstract_inverted_index.boundary, | 130 |
| abstract_inverted_index.different | 81 |
| abstract_inverted_index.employed, | 137 |
| abstract_inverted_index.framework | 96 |
| abstract_inverted_index.problems. | 166 |
| abstract_inverted_index.reflected | 78 |
| abstract_inverted_index.scenarios | 34 |
| abstract_inverted_index.utilizing | 185 |
| abstract_inverted_index.Integrated | 0 |
| abstract_inverted_index.achievable | 118 |
| abstract_inverted_index.capability | 200 |
| abstract_inverted_index.estimation | 203 |
| abstract_inverted_index.individual | 64 |
| abstract_inverted_index.its\nupper | 54 |
| abstract_inverted_index.principles | 86 |
| abstract_inverted_index.resolution | 199 |
| abstract_inverted_index.simulation | 168 |
| abstract_inverted_index.technology | 8 |
| abstract_inverted_index.the\ntight | 186 |
| abstract_inverted_index.(MIMO)-ISAC | 32 |
| abstract_inverted_index.accuracy.\n | 204 |
| abstract_inverted_index.considering | 139 |
| abstract_inverted_index.information | 48 |
| abstract_inverted_index.interpreted | 59 |
| abstract_inverted_index.introducing | 112 |
| abstract_inverted_index.investigate | 25 |
| abstract_inverted_index.performance | 194 |
| abstract_inverted_index.suppressing | 75 |
| abstract_inverted_index.systems\nin | 33 |
| abstract_inverted_index.aligns\nwith | 84 |
| abstract_inverted_index.characterize | 116 |
| abstract_inverted_index.multi-target | 45, 181 |
| abstract_inverted_index.performance. | 183 |
| abstract_inverted_index.solution\nby | 159 |
| abstract_inverted_index.the\nmax-min | 131 |
| abstract_inverted_index.Additionally, | 67, 184 |
| abstract_inverted_index.Subsequently, | 147 |
| abstract_inverted_index.capabilities. | 20 |
| abstract_inverted_index.communication | 3, 40, 142 |
| abstract_inverted_index.general\nform | 43 |
| abstract_inverted_index.the\nfairness | 140 |
| abstract_inverted_index.multiple-input | 29 |
| abstract_inverted_index.the\nbisection | 148 |
| abstract_inverted_index.communications, | 12 |
| abstract_inverted_index.multiple-output | 31 |
| abstract_inverted_index.Pareto\nboundary | 114 |
| abstract_inverted_index.results\nvalidate | 169 |
| abstract_inverted_index.the\nmulti-target | 198 |
| abstract_inverted_index.communication-sensing | 119 |
| abstract_inverted_index.performance\nboundary | 120 |
| abstract_inverted_index.the\nsixth-generation | 10 |
| abstract_inverted_index.transmit\nbeamforming | 26 |
| abstract_inverted_index.single-target\nsensing | 65 |
| abstract_inverted_index.the\ncross-correlation | 76 |
| abstract_inverted_index.communication\nnetworks | 17 |
| abstract_inverted_index.multi-user\ncommunication | 179 |
| abstract_inverted_index.multi-objective\noptimization | 95 |
| abstract_inverted_index.signal-to-interference-plus-noise | 100 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 96 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile.value | 0.98864039 |
| citation_normalized_percentile.is_in_top_1_percent | True |
| citation_normalized_percentile.is_in_top_10_percent | True |