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However, the issue of resource allocation in NOMA is dynamic and produces a high computation burden when using traditional methods. In this paper, a symmetry-aware double deep Q network (DDQN) algorithm in deep reinforcement learning is employed to allocate power to users in NOMA while guaranteeing quality of service for the weakest users. The research process is divided into two parts. Firstly, users in the communication system are grouped using a method that synergistically considers gain difference and similarity, exploiting symmetrical properties within the user groups. Secondly, the DDQN algorithm is used to allocate power to multiple users in a NOMA system, which utilizes the inherent symmetry in the signal-to-interference noise ratio of each user as an objective function. By recognizing and leveraging these symmetrical patterns, the algorithm can dynamically adjust the power allocation to optimize system performance. Finally, the proposed algorithm is compared with conventional NOMA power allocation algorithms and shows significant improvements in system performance. The results of the convergence function show that the algorithm proposed in this paper can converge in approximately 1800 iterations, which effectively solves the problem of large arithmetic and complex processes existing in the traditional method.<\/jats:p>","DOI":"10.3390\/sym16121613","type":"journal-article","created":{"date-parts":[[2024,12,5]],"date-time":"2024-12-05T04:13:03Z","timestamp":1733371983000},"page":"1613","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Downlink Non-Orthogonal Multiple Access Power Allocation Algorithm Based on Double Deep Q Network for Ensuring User\u2019s Quality of Service"],"prefix":"10.3390","volume":"16","author":[{"given":"Ying","family":"Lin","sequence":"first","affiliation":[{"name":"School of Computer and Communication, Lanzhou University of Technology, No. 36, Pengjiaping Road, Qilihe District, Lanzhou 730050, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xingbo","family":"Gong","sequence":"additional","affiliation":[{"name":"School of Computer and Communication, Lanzhou University of Technology, No. 36, Pengjiaping Road, Qilihe District, Lanzhou 730050, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongwei","family":"Xiong","sequence":"additional","affiliation":[{"name":"School of Computer and Communication, Lanzhou University of Technology, No. 36, Pengjiaping Road, Qilihe District, Lanzhou 730050, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haomin","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer and Communication, Lanzhou University of Technology, No. 36, Pengjiaping Road, Qilihe District, Lanzhou 730050, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiangcheng","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer and Communication, Lanzhou University of Technology, No. 36, Pengjiaping Road, Qilihe District, Lanzhou 730050, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Sufyan, A., Khan, K.B., Khashan, O.A., Mir, T., and Mir, U. 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