| 基于禁忌搜索和Q-learning的CR-NOMA系统的功率分配算法 |
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| 引用本文： | 周烁,仇润鹤,唐旻俊. 基于禁忌搜索和Q-learning的CR-NOMA系统的功率分配算法[J]. 计算机应用, 2021, 41(7): 2026-2032. DOI: 10.11772/j.issn.1001-9081.2020081249 |
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| 作者姓名： | 周烁 仇润鹤 唐旻俊 |
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| 作者单位： | 1. 东华大学 信息科学与技术学院, 上海 201620;2. 数字化纺织服装技术教育部工程研究中心(东华大学), 上海 201620 |
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| 基金项目： | 国家自然科学基金面上项目（61671143）。 |
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| 摘 要： | 针对下一代移动通信对于高速率和大规模连接的需求,对认知无线电(CR)-非正交多址接入(NOMA)混合系统中通过优化功率分配来提升次用户总传输速率进行研究,提出一种基于禁忌搜索和Q-learning的功率分配(PATSQ)算法.首先,认知基站在系统环境中观测并学习用户的功率分配,次用户采用NOMA方式接入授权信道.其次,...
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| 关 键 词： | 非正交多址接入 认知无线电 功率分配 禁忌搜索 Q-learning 服务质量 马尔可夫决策过程 |
| 收稿时间： | 2020-08-18 |
| 修稿时间： | 2020-12-23 |
Power allocation algorithm for CR-NOMA system based on tabu search and Q-learning |
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| ZHOU Shuo,QIU Runhe,TANG Minjun. Power allocation algorithm for CR-NOMA system based on tabu search and Q-learning[J]. Journal of Computer Applications, 2021, 41(7): 2026-2032. DOI: 10.11772/j.issn.1001-9081.2020081249 |
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| Authors: | ZHOU Shuo QIU Runhe TANG Minjun |
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| Affiliation: | 1. College of Information Sciences and Technology, Donghua University, Shanghai 201620, China;2. Engineering Research Center of Digitized Textile and Fashion Technology, Ministry of Education(Donghua University), Shanghai 201620, China |
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| Abstract: | For the demand of high speed and massive connections of next-generation mobile communication, improving the total secondary users' transmission rate by the optimization of power allocation in Cognitive Radio-Non-Orthogonal Multi-Access (CR-NOMA) hybrid system was studied, and an algorithm of Power Allocation based on Tabu Search and Q-learning (PATSQ) was proposed. Firstly, the users' power allocation was observed and learnt by the cognitive base station in the system environment, and the secondary users used NOMA to access the authorized channel. Then, the power allocation, channel state and total transmission rate in the power allocation problem were expressed as action, state and reward in the Markov decision process, which was solved by combining tabu search and Q-learning and an optimal tabu Q-table was obtained. Finally, under the constraints of primary and secondary users' Quality of Service (QoS) and maximum transmitting power, optimal power allocation factors were obtained by the cognitive base station by looking up the tabu Q-table, so as to maximize the total transmission rate of secondary users in the system. Simulation results show that under the same total power, the proposed algorithm is superior to Cognitive Mobile Radio Network (CMRN) algorithm, Secondary user First Decode Mode (SFDM) algorithm and the traditional equal power allocation algorithm in terms of the total transmission rate of secondary users and the number of users contained in the system. |
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| Keywords: | Non-Orthogonal Multiple Access (NOMA) cognitive radio power allocation tabu search Q-learning Quality of Service (QoS) Markov decision process |
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