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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Veröffentlicht in:Cluster computing Jg. 28; H. 8; S. 532
Hauptverfasser: Ghamry, Walid K., Shukry, Suzan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.09.2025
Springer Nature B.V
Schlagworte:
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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Zusammenfassung: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.
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ISSN:1386-7857
1573-7543
DOI:10.1007/s10586-025-05542-3