The dynamic power allocation to maximize the achievable sum rate for massive MIMO‐NOMA systems
Abstract The demand of mobile networks and quality of service have recently increased to higher Spectral Efficiency (SE) or Energy Efficiency (EE) and massive connectivity for 5G wireless communications. The concept of beamforming Multiple‐Input Multiple‐Output (MIMO) is capable of significantly red...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-10-01
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| Series: | IET Communications |
| Online Access: | https://doi.org/10.1049/cmu2.12457 |
| _version_ | 1817983355942076416 |
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| author | Zahra Amirifar Jamshid Abouei |
| author_facet | Zahra Amirifar Jamshid Abouei |
| author_sort | Zahra Amirifar |
| collection | DOAJ |
| description | Abstract The demand of mobile networks and quality of service have recently increased to higher Spectral Efficiency (SE) or Energy Efficiency (EE) and massive connectivity for 5G wireless communications. The concept of beamforming Multiple‐Input Multiple‐Output (MIMO) is capable of significantly reducing the amount of required Radio Frequency Chains (RFCs) used by massive MIMO systems without remarkable performance loss. However, in existing beamformed MIMO, the amount of supported devices cannot be higher than the amount of RFCs using the same time‐frequency resources, and it is the basic limit for these systems. To address this issue, non‐orthogonal multiple access (NOMA) has been recently recommended, which can accommodate higher covered using via non‐orthogonal resource allocation. Nevertheless, power allocation is a core factor of the NOMA scheme. However, maximizing the sum rate problem based on power allocation in Massive MIMO‐NOMA scenarios is non‐convex and non‐linear, which creates a very challenging situation to acquire the closed‐form approach. Thus, in this paper, an approach to this difficulty is outlined for Massive MIMO‐NOMA systems to maximize the sum rate as a convex and linear problem. Simulation results of the suggested Beamformed MIMO‐NOMA (BMN) algorithm show that a higher achievable sum rate is achieved compared with the usual beamformed MIMO. |
| first_indexed | 2024-04-13T23:32:11Z |
| format | Article |
| id | doaj.art-13420de000af47c29656a42af8a16e64 |
| institution | Directory Open Access Journal |
| issn | 1751-8628 1751-8636 |
| language | English |
| last_indexed | 2024-04-13T23:32:11Z |
| publishDate | 2022-10-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Communications |
| spelling | doaj.art-13420de000af47c29656a42af8a16e642022-12-22T02:24:52ZengWileyIET Communications1751-86281751-86362022-10-0116172036204410.1049/cmu2.12457The dynamic power allocation to maximize the achievable sum rate for massive MIMO‐NOMA systemsZahra Amirifar0Jamshid Abouei1Department of Electrical Engineering Yazd University Yazd IranDepartment of Electrical Engineering Yazd University Yazd IranAbstract The demand of mobile networks and quality of service have recently increased to higher Spectral Efficiency (SE) or Energy Efficiency (EE) and massive connectivity for 5G wireless communications. The concept of beamforming Multiple‐Input Multiple‐Output (MIMO) is capable of significantly reducing the amount of required Radio Frequency Chains (RFCs) used by massive MIMO systems without remarkable performance loss. However, in existing beamformed MIMO, the amount of supported devices cannot be higher than the amount of RFCs using the same time‐frequency resources, and it is the basic limit for these systems. To address this issue, non‐orthogonal multiple access (NOMA) has been recently recommended, which can accommodate higher covered using via non‐orthogonal resource allocation. Nevertheless, power allocation is a core factor of the NOMA scheme. However, maximizing the sum rate problem based on power allocation in Massive MIMO‐NOMA scenarios is non‐convex and non‐linear, which creates a very challenging situation to acquire the closed‐form approach. Thus, in this paper, an approach to this difficulty is outlined for Massive MIMO‐NOMA systems to maximize the sum rate as a convex and linear problem. Simulation results of the suggested Beamformed MIMO‐NOMA (BMN) algorithm show that a higher achievable sum rate is achieved compared with the usual beamformed MIMO.https://doi.org/10.1049/cmu2.12457 |
| spellingShingle | Zahra Amirifar Jamshid Abouei The dynamic power allocation to maximize the achievable sum rate for massive MIMO‐NOMA systems IET Communications |
| title | The dynamic power allocation to maximize the achievable sum rate for massive MIMO‐NOMA systems |
| title_full | The dynamic power allocation to maximize the achievable sum rate for massive MIMO‐NOMA systems |
| title_fullStr | The dynamic power allocation to maximize the achievable sum rate for massive MIMO‐NOMA systems |
| title_full_unstemmed | The dynamic power allocation to maximize the achievable sum rate for massive MIMO‐NOMA systems |
| title_short | The dynamic power allocation to maximize the achievable sum rate for massive MIMO‐NOMA systems |
| title_sort | dynamic power allocation to maximize the achievable sum rate for massive mimo noma systems |
| url | https://doi.org/10.1049/cmu2.12457 |
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