Evolutionary multi-objective optimization for RIS-aided MU-MISO communication systems
Abstract We study a multi-user multiple-input single-output downlink system aided by a reconfigurable intelligent surface (RIS). Users’ sum rate and transmit power are two important performance indicators in such systems. However, most existing works only optimize one of them, resulting in severe pe...
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| Autor*in: |
Li, Mengke [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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| Schlagwörter: |
Reconfigurable intelligent surface (RIS) |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| Übergeordnetes Werk: |
Enthalten in: Soft Computing - Springer-Verlag, 2003, 27(2023), 12 vom: 27. März, Seite 8091-8106 |
|---|---|
| Übergeordnetes Werk: |
volume:27 ; year:2023 ; number:12 ; day:27 ; month:03 ; pages:8091-8106 |
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| DOI / URN: |
10.1007/s00500-023-08002-5 |
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| 520 | |a Abstract We study a multi-user multiple-input single-output downlink system aided by a reconfigurable intelligent surface (RIS). Users’ sum rate and transmit power are two important performance indicators in such systems. However, most existing works only optimize one of them, resulting in severe performance degradation of the other. Motivated by this, in this paper, we formulate a multi-objective optimization problem to maximize the sum rate of users and minimize the transmit power simultaneously. According to our early work on fitness landscape analysis of sum rate maximization problems, the proposed problem is inferred to be multi-modal. To solve this non-convex and multi-modal problem, we propose a novel multi-objective evolutionary hybrid beamforming (MEHB) framework to find different trade-off solutions between the two conflicting objectives. In particular, we employ different kinds of multi-objective evolutionary algorithms and multi-modal multi-objective evolutionary algorithms as the baseline of MEHB framework, so as to design the passive beamforming. And the active beamforming at the base station is optimized by the classical zero-forcing method. The simulation results have verified the effectiveness of the dominance-based evolutionary algorithms in handling hybrid beamforming problems. | ||
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10.1007/s00500-023-08002-5 doi (DE-627)SPR052466973 (SPR)s00500-023-08002-5-e DE-627 ger DE-627 rakwb eng Li, Mengke verfasserin aut Evolutionary multi-objective optimization for RIS-aided MU-MISO communication systems 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract We study a multi-user multiple-input single-output downlink system aided by a reconfigurable intelligent surface (RIS). Users’ sum rate and transmit power are two important performance indicators in such systems. However, most existing works only optimize one of them, resulting in severe performance degradation of the other. Motivated by this, in this paper, we formulate a multi-objective optimization problem to maximize the sum rate of users and minimize the transmit power simultaneously. According to our early work on fitness landscape analysis of sum rate maximization problems, the proposed problem is inferred to be multi-modal. To solve this non-convex and multi-modal problem, we propose a novel multi-objective evolutionary hybrid beamforming (MEHB) framework to find different trade-off solutions between the two conflicting objectives. In particular, we employ different kinds of multi-objective evolutionary algorithms and multi-modal multi-objective evolutionary algorithms as the baseline of MEHB framework, so as to design the passive beamforming. And the active beamforming at the base station is optimized by the classical zero-forcing method. The simulation results have verified the effectiveness of the dominance-based evolutionary algorithms in handling hybrid beamforming problems. Reconfigurable intelligent surface (RIS) (dpeaa)DE-He213 Hybrid beamforming (dpeaa)DE-He213 multi-objective evolutionary algorithms (dpeaa)DE-He213 Multi-objective multi-modal optimization (dpeaa)DE-He213 Yan, Bai aut Zhang, Jin (orcid)0000-0002-2674-0918 aut Enthalten in Soft Computing Springer-Verlag, 2003 27(2023), 12 vom: 27. März, Seite 8091-8106 (DE-627)SPR006469531 nnns volume:27 year:2023 number:12 day:27 month:03 pages:8091-8106 https://dx.doi.org/10.1007/s00500-023-08002-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 27 2023 12 27 03 8091-8106 |
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10.1007/s00500-023-08002-5 doi (DE-627)SPR052466973 (SPR)s00500-023-08002-5-e DE-627 ger DE-627 rakwb eng Li, Mengke verfasserin aut Evolutionary multi-objective optimization for RIS-aided MU-MISO communication systems 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract We study a multi-user multiple-input single-output downlink system aided by a reconfigurable intelligent surface (RIS). Users’ sum rate and transmit power are two important performance indicators in such systems. However, most existing works only optimize one of them, resulting in severe performance degradation of the other. Motivated by this, in this paper, we formulate a multi-objective optimization problem to maximize the sum rate of users and minimize the transmit power simultaneously. According to our early work on fitness landscape analysis of sum rate maximization problems, the proposed problem is inferred to be multi-modal. To solve this non-convex and multi-modal problem, we propose a novel multi-objective evolutionary hybrid beamforming (MEHB) framework to find different trade-off solutions between the two conflicting objectives. In particular, we employ different kinds of multi-objective evolutionary algorithms and multi-modal multi-objective evolutionary algorithms as the baseline of MEHB framework, so as to design the passive beamforming. And the active beamforming at the base station is optimized by the classical zero-forcing method. The simulation results have verified the effectiveness of the dominance-based evolutionary algorithms in handling hybrid beamforming problems. Reconfigurable intelligent surface (RIS) (dpeaa)DE-He213 Hybrid beamforming (dpeaa)DE-He213 multi-objective evolutionary algorithms (dpeaa)DE-He213 Multi-objective multi-modal optimization (dpeaa)DE-He213 Yan, Bai aut Zhang, Jin (orcid)0000-0002-2674-0918 aut Enthalten in Soft Computing Springer-Verlag, 2003 27(2023), 12 vom: 27. März, Seite 8091-8106 (DE-627)SPR006469531 nnns volume:27 year:2023 number:12 day:27 month:03 pages:8091-8106 https://dx.doi.org/10.1007/s00500-023-08002-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 27 2023 12 27 03 8091-8106 |
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10.1007/s00500-023-08002-5 doi (DE-627)SPR052466973 (SPR)s00500-023-08002-5-e DE-627 ger DE-627 rakwb eng Li, Mengke verfasserin aut Evolutionary multi-objective optimization for RIS-aided MU-MISO communication systems 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract We study a multi-user multiple-input single-output downlink system aided by a reconfigurable intelligent surface (RIS). Users’ sum rate and transmit power are two important performance indicators in such systems. However, most existing works only optimize one of them, resulting in severe performance degradation of the other. Motivated by this, in this paper, we formulate a multi-objective optimization problem to maximize the sum rate of users and minimize the transmit power simultaneously. According to our early work on fitness landscape analysis of sum rate maximization problems, the proposed problem is inferred to be multi-modal. To solve this non-convex and multi-modal problem, we propose a novel multi-objective evolutionary hybrid beamforming (MEHB) framework to find different trade-off solutions between the two conflicting objectives. In particular, we employ different kinds of multi-objective evolutionary algorithms and multi-modal multi-objective evolutionary algorithms as the baseline of MEHB framework, so as to design the passive beamforming. And the active beamforming at the base station is optimized by the classical zero-forcing method. The simulation results have verified the effectiveness of the dominance-based evolutionary algorithms in handling hybrid beamforming problems. Reconfigurable intelligent surface (RIS) (dpeaa)DE-He213 Hybrid beamforming (dpeaa)DE-He213 multi-objective evolutionary algorithms (dpeaa)DE-He213 Multi-objective multi-modal optimization (dpeaa)DE-He213 Yan, Bai aut Zhang, Jin (orcid)0000-0002-2674-0918 aut Enthalten in Soft Computing Springer-Verlag, 2003 27(2023), 12 vom: 27. März, Seite 8091-8106 (DE-627)SPR006469531 nnns volume:27 year:2023 number:12 day:27 month:03 pages:8091-8106 https://dx.doi.org/10.1007/s00500-023-08002-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 27 2023 12 27 03 8091-8106 |
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10.1007/s00500-023-08002-5 doi (DE-627)SPR052466973 (SPR)s00500-023-08002-5-e DE-627 ger DE-627 rakwb eng Li, Mengke verfasserin aut Evolutionary multi-objective optimization for RIS-aided MU-MISO communication systems 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract We study a multi-user multiple-input single-output downlink system aided by a reconfigurable intelligent surface (RIS). Users’ sum rate and transmit power are two important performance indicators in such systems. However, most existing works only optimize one of them, resulting in severe performance degradation of the other. Motivated by this, in this paper, we formulate a multi-objective optimization problem to maximize the sum rate of users and minimize the transmit power simultaneously. According to our early work on fitness landscape analysis of sum rate maximization problems, the proposed problem is inferred to be multi-modal. To solve this non-convex and multi-modal problem, we propose a novel multi-objective evolutionary hybrid beamforming (MEHB) framework to find different trade-off solutions between the two conflicting objectives. In particular, we employ different kinds of multi-objective evolutionary algorithms and multi-modal multi-objective evolutionary algorithms as the baseline of MEHB framework, so as to design the passive beamforming. And the active beamforming at the base station is optimized by the classical zero-forcing method. The simulation results have verified the effectiveness of the dominance-based evolutionary algorithms in handling hybrid beamforming problems. Reconfigurable intelligent surface (RIS) (dpeaa)DE-He213 Hybrid beamforming (dpeaa)DE-He213 multi-objective evolutionary algorithms (dpeaa)DE-He213 Multi-objective multi-modal optimization (dpeaa)DE-He213 Yan, Bai aut Zhang, Jin (orcid)0000-0002-2674-0918 aut Enthalten in Soft Computing Springer-Verlag, 2003 27(2023), 12 vom: 27. März, Seite 8091-8106 (DE-627)SPR006469531 nnns volume:27 year:2023 number:12 day:27 month:03 pages:8091-8106 https://dx.doi.org/10.1007/s00500-023-08002-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 27 2023 12 27 03 8091-8106 |
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10.1007/s00500-023-08002-5 doi (DE-627)SPR052466973 (SPR)s00500-023-08002-5-e DE-627 ger DE-627 rakwb eng Li, Mengke verfasserin aut Evolutionary multi-objective optimization for RIS-aided MU-MISO communication systems 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. Abstract We study a multi-user multiple-input single-output downlink system aided by a reconfigurable intelligent surface (RIS). Users’ sum rate and transmit power are two important performance indicators in such systems. However, most existing works only optimize one of them, resulting in severe performance degradation of the other. Motivated by this, in this paper, we formulate a multi-objective optimization problem to maximize the sum rate of users and minimize the transmit power simultaneously. According to our early work on fitness landscape analysis of sum rate maximization problems, the proposed problem is inferred to be multi-modal. To solve this non-convex and multi-modal problem, we propose a novel multi-objective evolutionary hybrid beamforming (MEHB) framework to find different trade-off solutions between the two conflicting objectives. In particular, we employ different kinds of multi-objective evolutionary algorithms and multi-modal multi-objective evolutionary algorithms as the baseline of MEHB framework, so as to design the passive beamforming. And the active beamforming at the base station is optimized by the classical zero-forcing method. The simulation results have verified the effectiveness of the dominance-based evolutionary algorithms in handling hybrid beamforming problems. Reconfigurable intelligent surface (RIS) (dpeaa)DE-He213 Hybrid beamforming (dpeaa)DE-He213 multi-objective evolutionary algorithms (dpeaa)DE-He213 Multi-objective multi-modal optimization (dpeaa)DE-He213 Yan, Bai aut Zhang, Jin (orcid)0000-0002-2674-0918 aut Enthalten in Soft Computing Springer-Verlag, 2003 27(2023), 12 vom: 27. März, Seite 8091-8106 (DE-627)SPR006469531 nnns volume:27 year:2023 number:12 day:27 month:03 pages:8091-8106 https://dx.doi.org/10.1007/s00500-023-08002-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER AR 27 2023 12 27 03 8091-8106 |
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(orcid)0000-0002-2674-0918 |
| title_sort |
evolutionary multi-objective optimization for ris-aided mu-miso communication systems |
| title_auth |
Evolutionary multi-objective optimization for RIS-aided MU-MISO communication systems |
| abstract |
Abstract We study a multi-user multiple-input single-output downlink system aided by a reconfigurable intelligent surface (RIS). Users’ sum rate and transmit power are two important performance indicators in such systems. However, most existing works only optimize one of them, resulting in severe performance degradation of the other. Motivated by this, in this paper, we formulate a multi-objective optimization problem to maximize the sum rate of users and minimize the transmit power simultaneously. According to our early work on fitness landscape analysis of sum rate maximization problems, the proposed problem is inferred to be multi-modal. To solve this non-convex and multi-modal problem, we propose a novel multi-objective evolutionary hybrid beamforming (MEHB) framework to find different trade-off solutions between the two conflicting objectives. In particular, we employ different kinds of multi-objective evolutionary algorithms and multi-modal multi-objective evolutionary algorithms as the baseline of MEHB framework, so as to design the passive beamforming. And the active beamforming at the base station is optimized by the classical zero-forcing method. The simulation results have verified the effectiveness of the dominance-based evolutionary algorithms in handling hybrid beamforming problems. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstractGer |
Abstract We study a multi-user multiple-input single-output downlink system aided by a reconfigurable intelligent surface (RIS). Users’ sum rate and transmit power are two important performance indicators in such systems. However, most existing works only optimize one of them, resulting in severe performance degradation of the other. Motivated by this, in this paper, we formulate a multi-objective optimization problem to maximize the sum rate of users and minimize the transmit power simultaneously. According to our early work on fitness landscape analysis of sum rate maximization problems, the proposed problem is inferred to be multi-modal. To solve this non-convex and multi-modal problem, we propose a novel multi-objective evolutionary hybrid beamforming (MEHB) framework to find different trade-off solutions between the two conflicting objectives. In particular, we employ different kinds of multi-objective evolutionary algorithms and multi-modal multi-objective evolutionary algorithms as the baseline of MEHB framework, so as to design the passive beamforming. And the active beamforming at the base station is optimized by the classical zero-forcing method. The simulation results have verified the effectiveness of the dominance-based evolutionary algorithms in handling hybrid beamforming problems. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
| abstract_unstemmed |
Abstract We study a multi-user multiple-input single-output downlink system aided by a reconfigurable intelligent surface (RIS). Users’ sum rate and transmit power are two important performance indicators in such systems. However, most existing works only optimize one of them, resulting in severe performance degradation of the other. Motivated by this, in this paper, we formulate a multi-objective optimization problem to maximize the sum rate of users and minimize the transmit power simultaneously. According to our early work on fitness landscape analysis of sum rate maximization problems, the proposed problem is inferred to be multi-modal. To solve this non-convex and multi-modal problem, we propose a novel multi-objective evolutionary hybrid beamforming (MEHB) framework to find different trade-off solutions between the two conflicting objectives. In particular, we employ different kinds of multi-objective evolutionary algorithms and multi-modal multi-objective evolutionary algorithms as the baseline of MEHB framework, so as to design the passive beamforming. And the active beamforming at the base station is optimized by the classical zero-forcing method. The simulation results have verified the effectiveness of the dominance-based evolutionary algorithms in handling hybrid beamforming problems. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. |
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| title_short |
Evolutionary multi-objective optimization for RIS-aided MU-MISO communication systems |
| url |
https://dx.doi.org/10.1007/s00500-023-08002-5 |
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| author2 |
Yan, Bai Zhang, Jin |
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Yan, Bai Zhang, Jin |
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| doi_str |
10.1007/s00500-023-08002-5 |
| up_date |
2024-07-04T02:54:01.441Z |
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