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<p>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 (<InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10586_2025_5542_Article_IEq1.gif" Format="GIF" Height="17" Rendition="HTML" Resolution="72" Type="Linedraw" Width="48" /> </InlineMediaObject> <EquationSource Format="TEX">\(AR^{TH} \,\)</EquationSource> </InlineEquation>), 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 <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10586_2025_5542_Article_IEq1.gif" Format="GIF" Height="17" Rendition="HTML" Resolution="72" Type="Linedraw" Width="48" /> </InlineMediaObject> <EquationSource Format="TEX">\(AR^{TH} \,\)</EquationSource> </InlineEquation> 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 <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10586_2025_5542_Article_IEq1.gif" Format="GIF" Height="17" Rendition="HTML" Resolution="72" Type="Linedraw" Width="48" /> </InlineMediaObject> <EquationSource Format="TEX">\(AR^{TH} \,\)</EquationSource> </InlineEquation>. 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 <InlineEquation ID="IEq4"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10586_2025_5542_Article_IEq1.gif" Format="GIF" Height="17" Rendition="HTML" Resolution="72" Type="Linedraw" Width="48" /> </InlineMediaObject> <EquationSource Format="TEX">\(AR^{TH} \,\)</EquationSource> </InlineEquation> compared to conventional SWIPT-enabled mmWave MIMO-orthogonal multiple access (OMA) systems.</p>

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

  • 期刊论文

  • 发表日期：

    2025年8月19日

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  • Walid K. Ghamry,
  • Suzan Shukry

摘要

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 ( \(AR^{TH} \,\) ), 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 \(AR^{TH} \,\) 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 \(AR^{TH} \,\) . 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 \(AR^{TH} \,\) compared to conventional SWIPT-enabled mmWave MIMO-orthogonal multiple access (OMA) systems.