Joint optimization of energy harvesting and data transmission in SWIPT-enabled hybrid precoding mmWave massive MIMO-NOMA systems

The integration of millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems with non-orthogonal multiple access (NOMA) significantly enhances spectral efficiency, a critical advancement for fifth-generation (5G) and beyond networks. Energy-constrained devices can harvest energy...

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Published in:	Cluster computing Vol. 28; no. 8; p. 532
Main Authors:	Ghamry, Walid K., Shukry, Suzan
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.09.2025 Springer Nature B.V
Subjects:	Algorithms Antennas Clusters Communication Computer Communication Networks Computer Science Data transmission Decoding Energy consumption Energy efficiency Energy harvesting Millimeter waves MIMO communication Multiple objective analysis Nonorthogonal multiple access Operating Systems Optimization Power management Power transfer Processor Architectures Tradeoffs Transmission rate (communications) User groups Massive MIMO-NOMA Hybrid precoding Power splitting SWIPT Power allocation MmWave
ISSN:	1386-7857, 1573-7543
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Abstract	The integration of millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems with non-orthogonal multiple access (NOMA) significantly enhances spectral efficiency, a critical advancement for fifth-generation (5G) and beyond networks. Energy-constrained devices can harvest energy while decoding information through integrating simultaneous wireless information and power transfer (SWIPT), significantly enhancing overall energy efficiency. However, this integration introduces a fundamental trade-off between energy harvesting and data transmission rates, presenting a critical optimization challenge. This paper explores the intricate trade-off between these two objectives in SWIPT-enabled mmWave massive MIMO-NOMA systems. A joint optimization framework is proposed for power allocation and power splitting (PS) control, aimed at maximizing both harvested energy and total transmission rate while ensuring that user equipment (UE) meets predefined energy and rate thresholds. To address the conflicting objectives, a novel performance metric, termed total achievable throughput ( ), is introduced, which combines the throughput transformed from harvested energy and data transmission rate. The resulting multi-objective optimization problem is reformulated into a single-objective optimization problem. To solve this optimization problem, an initial selecting cluster-head (SCH) and user grouping algorithm is proposed. This algorithm identifies a cluster head for each beam and organizes UEs into groups based on normalized channel correlation. An analog radio-frequency (RF) precoder is then designed for the selected user groups, followed by a digital baseband precoder to minimize inter-beam interference and maximize . The nonconvex optimization problem is then separated into two convex sub-problems, which are addressed iteratively. Both independent and equal PS scenarios are explored. Simulation results validate the proposed algorithms, demonstrating substantial improvements in energy efficiency and compared to conventional SWIPT-enabled mmWave MIMO-orthogonal multiple access (OMA) systems.
AbstractList	The integration of millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems with non-orthogonal multiple access (NOMA) significantly enhances spectral efficiency, a critical advancement for fifth-generation (5G) and beyond networks. Energy-constrained devices can harvest energy while decoding information through integrating simultaneous wireless information and power transfer (SWIPT), significantly enhancing overall energy efficiency. However, this integration introduces a fundamental trade-off between energy harvesting and data transmission rates, presenting a critical optimization challenge. This paper explores the intricate trade-off between these two objectives in SWIPT-enabled mmWave massive MIMO-NOMA systems. A joint optimization framework is proposed for power allocation and power splitting (PS) control, aimed at maximizing both harvested energy and total transmission rate while ensuring that user equipment (UE) meets predefined energy and rate thresholds. To address the conflicting objectives, a novel performance metric, termed total achievable throughput ( ), is introduced, which combines the throughput transformed from harvested energy and data transmission rate. The resulting multi-objective optimization problem is reformulated into a single-objective optimization problem. To solve this optimization problem, an initial selecting cluster-head (SCH) and user grouping algorithm is proposed. This algorithm identifies a cluster head for each beam and organizes UEs into groups based on normalized channel correlation. An analog radio-frequency (RF) precoder is then designed for the selected user groups, followed by a digital baseband precoder to minimize inter-beam interference and maximize . The nonconvex optimization problem is then separated into two convex sub-problems, which are addressed iteratively. Both independent and equal PS scenarios are explored. Simulation results validate the proposed algorithms, demonstrating substantial improvements in energy efficiency and compared to conventional SWIPT-enabled mmWave MIMO-orthogonal multiple access (OMA) systems. The integration of millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems with non-orthogonal multiple access (NOMA) significantly enhances spectral efficiency, a critical advancement for fifth-generation (5G) and beyond networks. Energy-constrained devices can harvest energy while decoding information through integrating simultaneous wireless information and power transfer (SWIPT), significantly enhancing overall energy efficiency. However, this integration introduces a fundamental trade-off between energy harvesting and data transmission rates, presenting a critical optimization challenge. This paper explores the intricate trade-off between these two objectives in SWIPT-enabled mmWave massive MIMO-NOMA systems. A joint optimization framework is proposed for power allocation and power splitting (PS) control, aimed at maximizing both harvested energy and total transmission rate while ensuring that user equipment (UE) meets predefined energy and rate thresholds. To address the conflicting objectives, a novel performance metric, termed total achievable throughput (), is introduced, which combines the throughput transformed from harvested energy and data transmission rate. The resulting multi-objective optimization problem is reformulated into a single-objective optimization problem. To solve this optimization problem, an initial selecting cluster-head (SCH) and user grouping algorithm is proposed. This algorithm identifies a cluster head for each beam and organizes UEs into groups based on normalized channel correlation. An analog radio-frequency (RF) precoder is then designed for the selected user groups, followed by a digital baseband precoder to minimize inter-beam interference and maximize . The nonconvex optimization problem is then separated into two convex sub-problems, which are addressed iteratively. Both independent and equal PS scenarios are explored. Simulation results validate the proposed algorithms, demonstrating substantial improvements in energy efficiency and compared to conventional SWIPT-enabled mmWave MIMO-orthogonal multiple access (OMA) systems.
ArticleNumber	532
Author	Shukry, Suzan Ghamry, Walid K.
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Copyright_xml	– notice: The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025 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. – notice: The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.
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Snippet	The integration of millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems with non-orthogonal multiple access (NOMA) significantly...
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SubjectTerms	Algorithms Antennas Clusters Communication Computer Communication Networks Computer Science Data transmission Decoding Energy consumption Energy efficiency Energy harvesting Millimeter waves MIMO communication Multiple objective analysis Nonorthogonal multiple access Operating Systems Optimization Power management Power transfer Processor Architectures Tradeoffs Transmission rate (communications) User groups
Title	Joint optimization of energy harvesting and data transmission in SWIPT-enabled hybrid precoding mmWave massive MIMO-NOMA systems
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