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    袁伟娜, 王艳龙, 刘伟婷, 郭逸飞, 王硕恒. 基于贪婪策略的低复杂度功率分配算法[J]. 华东理工大学学报(自然科学版), 2021, 47(3): 340-347. DOI: 10.14135/j.cnki.1006-3080.20200119002
    引用本文: 袁伟娜, 王艳龙, 刘伟婷, 郭逸飞, 王硕恒. 基于贪婪策略的低复杂度功率分配算法[J]. 华东理工大学学报(自然科学版), 2021, 47(3): 340-347. DOI: 10.14135/j.cnki.1006-3080.20200119002
    YUAN Weina, WANG Yanlong, LIU Weiting, GUO Yifei, WANG Shuoheng. A Low Computational Complexity Power Allocation Algorithm Based on Greedy Policy[J]. Journal of East China University of Science and Technology, 2021, 47(3): 340-347. DOI: 10.14135/j.cnki.1006-3080.20200119002
    Citation: YUAN Weina, WANG Yanlong, LIU Weiting, GUO Yifei, WANG Shuoheng. A Low Computational Complexity Power Allocation Algorithm Based on Greedy Policy[J]. Journal of East China University of Science and Technology, 2021, 47(3): 340-347. DOI: 10.14135/j.cnki.1006-3080.20200119002

    基于贪婪策略的低复杂度功率分配算法

    A Low Computational Complexity Power Allocation Algorithm Based on Greedy Policy

    • 摘要: 非正交多址(Non-Orthogonal Multiple Access,NOMA)系统中发送端的功率分配算法对系统的吞吐量影响很大,而可以取得最优性能的全空间搜索功率分配(Full Search Power Allocation,FSPA)算法由于较高的复杂度,难以运用到实际系统当中。结合串行干扰消除(Successive Interference Cancellation,SIC)接收机的特点及贪心算法中的局部最优原理,提出了一种基于贪婪策略的功率分配算法。该算法的目标是最大化系统的总吞吐量,具体流程采用树的结构来呈现。自树根开始逐层进行功率分配、局部吞吐量判断、保留最优支路等操作,最后从尾节点返回至根节点的唯一通路即为最终的功率分配情况。仿真实验结果表明,该算法在系统总吞吐量与全空间搜索相差不到1.5%的情况下,成功地将复杂度由随用户数指数级的增长降低到了线性级的增长。与其他算法相比,本文算法也均有不同程度的优势。

       

      Abstract: In the non-orthogonal multiple access (NOMA) system, the power allocation algorithm at the transmitter plays a key role in the throughput performance. However, the Full Search Power Allocation (FSPA) algorithm is difficultly applied to the practical system due to its unacceptable computational complexity, although it can achieve the optimal performance. By combining the principle of the successive interference cancellation receiver, this paper proposes a novel power allocation algorithm based on greedy policy, whose main idea comes from the principle of the local optimal discrimination in greedy algorithm. The goal of this algorithm is to maximize the total throughput performance of the system. Its detailed structure can be presented in the form of tree. Starting from the root of the tree, we begin perform the power allocation, local throughput judgment, and optimal branch reservation layer by layer. After that, the only surviving path from the tail node to the first node is the final allocation result. It is proven that the proposed greedy strategy satisfies the principle without aftereffect and the obtained final power allocation is globally optimal. As the simulation results show, under the case that the total throughout of this algorithm has less than 1.5% difference from the one of full space search, the complexity is successfully decreased from the exponential growth with the number of users to the linear growth. Moreover, compared with other suboptimal algorithms, this algorithm also shows advantages of different degrees.

       

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