Reinforcement Learning-Based Joint User Pairing and Power Allocation in MIMO-NOMA Systems
In this paper, we consider a multiple-input multiple-output (MIMO)—non-orthogonal multiple access (NOMA) system with reinforcement learning (RL). NOMA, which is a technique for increasing the spectrum efficiency, has been extensively studied in fifth-generation (5G) wireless communication systems. T...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-12-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/20/24/7094 |
| _version_ | 1797545048192057344 |
|---|---|
| author | Jaehee Lee Jaewoo So |
| author_facet | Jaehee Lee Jaewoo So |
| author_sort | Jaehee Lee |
| collection | DOAJ |
| description | In this paper, we consider a multiple-input multiple-output (MIMO)—non-orthogonal multiple access (NOMA) system with reinforcement learning (RL). NOMA, which is a technique for increasing the spectrum efficiency, has been extensively studied in fifth-generation (5G) wireless communication systems. The application of MIMO to NOMA can result in an even higher spectral efficiency. Moreover, user pairing and power allocation problem are important techniques in NOMA. However, NOMA has a fundamental limitation of the high computational complexity due to rapidly changing radio channels. This limitation makes it difficult to utilize the characteristics of the channel and allocate radio resources efficiently. To reduce the computational complexity, we propose an RL-based joint user pairing and power allocation scheme. By applying Q-learning, we are able to perform user pairing and power allocation simultaneously, which reduces the computational complexity. The simulation results show that the proposed scheme achieves a sum rate similar to that achieved with the exhaustive search (ES). |
| first_indexed | 2024-03-10T14:10:07Z |
| format | Article |
| id | doaj.art-cacaccc8c9e84afd8d6ede7d297d06c0 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T14:10:07Z |
| publishDate | 2020-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-cacaccc8c9e84afd8d6ede7d297d06c02023-11-21T00:19:13ZengMDPI AGSensors1424-82202020-12-012024709410.3390/s20247094Reinforcement Learning-Based Joint User Pairing and Power Allocation in MIMO-NOMA SystemsJaehee Lee0Jaewoo So1Department of Electronic Engineering, Sogang University, Seoul 04107, KoreaDepartment of Electronic Engineering, Sogang University, Seoul 04107, KoreaIn this paper, we consider a multiple-input multiple-output (MIMO)—non-orthogonal multiple access (NOMA) system with reinforcement learning (RL). NOMA, which is a technique for increasing the spectrum efficiency, has been extensively studied in fifth-generation (5G) wireless communication systems. The application of MIMO to NOMA can result in an even higher spectral efficiency. Moreover, user pairing and power allocation problem are important techniques in NOMA. However, NOMA has a fundamental limitation of the high computational complexity due to rapidly changing radio channels. This limitation makes it difficult to utilize the characteristics of the channel and allocate radio resources efficiently. To reduce the computational complexity, we propose an RL-based joint user pairing and power allocation scheme. By applying Q-learning, we are able to perform user pairing and power allocation simultaneously, which reduces the computational complexity. The simulation results show that the proposed scheme achieves a sum rate similar to that achieved with the exhaustive search (ES).https://www.mdpi.com/1424-8220/20/24/7094non-orthogonal multiple accessmultiple-input multiple-outputuser pairingpower allocationreinforcement learning |
| spellingShingle | Jaehee Lee Jaewoo So Reinforcement Learning-Based Joint User Pairing and Power Allocation in MIMO-NOMA Systems Sensors non-orthogonal multiple access multiple-input multiple-output user pairing power allocation reinforcement learning |
| title | Reinforcement Learning-Based Joint User Pairing and Power Allocation in MIMO-NOMA Systems |
| title_full | Reinforcement Learning-Based Joint User Pairing and Power Allocation in MIMO-NOMA Systems |
| title_fullStr | Reinforcement Learning-Based Joint User Pairing and Power Allocation in MIMO-NOMA Systems |
| title_full_unstemmed | Reinforcement Learning-Based Joint User Pairing and Power Allocation in MIMO-NOMA Systems |
| title_short | Reinforcement Learning-Based Joint User Pairing and Power Allocation in MIMO-NOMA Systems |
| title_sort | reinforcement learning based joint user pairing and power allocation in mimo noma systems |
| topic | non-orthogonal multiple access multiple-input multiple-output user pairing power allocation reinforcement learning |
| url | https://www.mdpi.com/1424-8220/20/24/7094 |
| work_keys_str_mv | AT jaeheelee reinforcementlearningbasedjointuserpairingandpowerallocationinmimonomasystems AT jaewooso reinforcementlearningbasedjointuserpairingandpowerallocationinmimonomasystems |