Joint Optimization of Massive MIMO System Resources Based on Service QoS
Aiming at the problem of low throughput and energy efficiency caused by the mutual restriction of energy efficiency and spectral efficiency in massive MIMO systems and the fact that resource allocation does not consider the factors of user service QoS and the upper and lower speed limits, a resource...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-06-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/12/13/2870 |
| _version_ | 1797591838205411328 |
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| author | Qingli Liu Rui Li Mengqian Li |
| author_facet | Qingli Liu Rui Li Mengqian Li |
| author_sort | Qingli Liu |
| collection | DOAJ |
| description | Aiming at the problem of low throughput and energy efficiency caused by the mutual restriction of energy efficiency and spectral efficiency in massive MIMO systems and the fact that resource allocation does not consider the factors of user service QoS and the upper and lower speed limits, a resource joint optimization method based on user service QoS guarantee is proposed. The method first performs user scheduling according to service delay and channel state under the condition of equal power distribution and calculates the current system capacity, and then combines transmit antenna power and service QoS constraints to redistribute power, and corrects the system capacity, establishing the objective function for the joint optimization of the spectral efficiency and energy efficiency. An algorithm combining deep learning and Q learning is used to solve the problem, and finally, the purpose of joint optimization is achieved. The simulation shows that the joint optimization method proposed in this paper can control the timeout of user data packets more finely and, at the same time, obtain greater energy efficiency and throughput. |
| first_indexed | 2024-03-11T01:43:03Z |
| format | Article |
| id | doaj.art-80568fd7c0ad4b38b3220b2c1b32d64a |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-11T01:43:03Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-80568fd7c0ad4b38b3220b2c1b32d64a2023-11-18T16:24:37ZengMDPI AGElectronics2079-92922023-06-011213287010.3390/electronics12132870Joint Optimization of Massive MIMO System Resources Based on Service QoSQingli Liu0Rui Li1Mengqian Li2Communication and Network Laboratory, Dalian University, Dalian 116622, ChinaCommunication and Network Laboratory, Dalian University, Dalian 116622, ChinaCommunication and Network Laboratory, Dalian University, Dalian 116622, ChinaAiming at the problem of low throughput and energy efficiency caused by the mutual restriction of energy efficiency and spectral efficiency in massive MIMO systems and the fact that resource allocation does not consider the factors of user service QoS and the upper and lower speed limits, a resource joint optimization method based on user service QoS guarantee is proposed. The method first performs user scheduling according to service delay and channel state under the condition of equal power distribution and calculates the current system capacity, and then combines transmit antenna power and service QoS constraints to redistribute power, and corrects the system capacity, establishing the objective function for the joint optimization of the spectral efficiency and energy efficiency. An algorithm combining deep learning and Q learning is used to solve the problem, and finally, the purpose of joint optimization is achieved. The simulation shows that the joint optimization method proposed in this paper can control the timeout of user data packets more finely and, at the same time, obtain greater energy efficiency and throughput.https://www.mdpi.com/2079-9292/12/13/2870massive MIMO systemtraffic delaychannel statejoint optimization |
| spellingShingle | Qingli Liu Rui Li Mengqian Li Joint Optimization of Massive MIMO System Resources Based on Service QoS Electronics massive MIMO system traffic delay channel state joint optimization |
| title | Joint Optimization of Massive MIMO System Resources Based on Service QoS |
| title_full | Joint Optimization of Massive MIMO System Resources Based on Service QoS |
| title_fullStr | Joint Optimization of Massive MIMO System Resources Based on Service QoS |
| title_full_unstemmed | Joint Optimization of Massive MIMO System Resources Based on Service QoS |
| title_short | Joint Optimization of Massive MIMO System Resources Based on Service QoS |
| title_sort | joint optimization of massive mimo system resources based on service qos |
| topic | massive MIMO system traffic delay channel state joint optimization |
| url | https://www.mdpi.com/2079-9292/12/13/2870 |
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