Energy Efficient Resource Allocation for H-NOMA Assisted B5G HetNets
The resource allocation solution offered based on non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) schemes are sub-optimal to address the challenging quality of service (QoS) and higher data rate viz-a-viz energy efficiency (EE) requirements in 5th generation (5G) cellular...
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| Format: | Article |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9866750/ |
| _version_ | 1798032045999390720 |
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| author | Umar Ghafoor Humayun Zubair Khan Mudassar Ali Adil Masood Siddiqui Muhammad Naeem Imran Rashid |
| author_facet | Umar Ghafoor Humayun Zubair Khan Mudassar Ali Adil Masood Siddiqui Muhammad Naeem Imran Rashid |
| author_sort | Umar Ghafoor |
| collection | DOAJ |
| description | The resource allocation solution offered based on non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) schemes are sub-optimal to address the challenging quality of service (QoS) and higher data rate viz-a-viz energy efficiency (EE) requirements in 5th generation (5G) cellular networks. In this work, we maximize the EE using user equipment (UE) clustering (UE-C) with downlink hybrid NOMA (H-NOMA) assisted beyond 5G (B5G) HetNets. We formulate an optimization problem incorporating UE admission in a cluster, UE association with a base station (BS), and power allocation assisted by H-NOMA, i.e., OMA and NOMA schemes in the macro base station (MBS) only and heterogeneous networks (HetNets) environments. The problem formulated is a type of non-linear concave fractional programming (CFP) problem. The Charnes-Cooper transformation (CCT) is applied to the formulated non-linear CFP problem to convert it into a concave optimization, i.e., mixed-integer non-linear programming (MINLP) problem. A two-phase <inline-formula> <tex-math notation="LaTeX">$\epsilon $ </tex-math></inline-formula>-optimal outer approximation algorithm (OAA) is used to solve the MINLP problem. The simulation results show that H-NOMA with HetNets outperforms H-NOMA with MBS only in terms of UE admission, UE association, throughput, and EE. |
| first_indexed | 2024-04-11T20:06:33Z |
| format | Article |
| id | doaj.art-f8e20ffd0798429c969ee2db5db8220b |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-11T20:06:33Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-f8e20ffd0798429c969ee2db5db8220b2022-12-22T04:05:18ZengIEEEIEEE Access2169-35362022-01-0110916999171110.1109/ACCESS.2022.32015279866750Energy Efficient Resource Allocation for H-NOMA Assisted B5G HetNetsUmar Ghafoor0https://orcid.org/0000-0002-1661-4061Humayun Zubair Khan1https://orcid.org/0000-0002-2665-5676Mudassar Ali2https://orcid.org/0000-0002-8402-5920Adil Masood Siddiqui3Muhammad Naeem4https://orcid.org/0000-0001-9734-4608Imran Rashid5https://orcid.org/0000-0001-8958-672XDepartment of Electrical Engineering, Military College of Signals, National University of Sciences and Technology, Islamabad, PakistanDepartment of Electrical Engineering, Military College of Signals, National University of Sciences and Technology, Islamabad, PakistanDepartment of Electrical Engineering, Military College of Signals, National University of Sciences and Technology, Islamabad, PakistanDepartment of Electrical Engineering, Military College of Signals, National University of Sciences and Technology, Islamabad, PakistanDepartment of Electrical and Computer Engineering, COMSATS University Islamabad, Wah Campus, Wah Cantt, PakistanDepartment of Electrical Engineering, Military College of Signals, National University of Sciences and Technology, Islamabad, PakistanThe resource allocation solution offered based on non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) schemes are sub-optimal to address the challenging quality of service (QoS) and higher data rate viz-a-viz energy efficiency (EE) requirements in 5th generation (5G) cellular networks. In this work, we maximize the EE using user equipment (UE) clustering (UE-C) with downlink hybrid NOMA (H-NOMA) assisted beyond 5G (B5G) HetNets. We formulate an optimization problem incorporating UE admission in a cluster, UE association with a base station (BS), and power allocation assisted by H-NOMA, i.e., OMA and NOMA schemes in the macro base station (MBS) only and heterogeneous networks (HetNets) environments. The problem formulated is a type of non-linear concave fractional programming (CFP) problem. The Charnes-Cooper transformation (CCT) is applied to the formulated non-linear CFP problem to convert it into a concave optimization, i.e., mixed-integer non-linear programming (MINLP) problem. A two-phase <inline-formula> <tex-math notation="LaTeX">$\epsilon $ </tex-math></inline-formula>-optimal outer approximation algorithm (OAA) is used to solve the MINLP problem. The simulation results show that H-NOMA with HetNets outperforms H-NOMA with MBS only in terms of UE admission, UE association, throughput, and EE.https://ieeexplore.ieee.org/document/9866750/UE-clusteringH-NOMAfractional programmingMINLPenergy efficiency |
| spellingShingle | Umar Ghafoor Humayun Zubair Khan Mudassar Ali Adil Masood Siddiqui Muhammad Naeem Imran Rashid Energy Efficient Resource Allocation for H-NOMA Assisted B5G HetNets IEEE Access UE-clustering H-NOMA fractional programming MINLP energy efficiency |
| title | Energy Efficient Resource Allocation for H-NOMA Assisted B5G HetNets |
| title_full | Energy Efficient Resource Allocation for H-NOMA Assisted B5G HetNets |
| title_fullStr | Energy Efficient Resource Allocation for H-NOMA Assisted B5G HetNets |
| title_full_unstemmed | Energy Efficient Resource Allocation for H-NOMA Assisted B5G HetNets |
| title_short | Energy Efficient Resource Allocation for H-NOMA Assisted B5G HetNets |
| title_sort | energy efficient resource allocation for h noma assisted b5g hetnets |
| topic | UE-clustering H-NOMA fractional programming MINLP energy efficiency |
| url | https://ieeexplore.ieee.org/document/9866750/ |
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