An Optimal Number of Indices Aided gOMP Algorithm for Multi-user Detection in NOMA System

被引：0
作者：
Shen B. [1 ]
Wu H. [1 ]
Cui T. [1 ]
Chen Q. [1 ]
机构：
[1] Key Laboratory of Mobile Communications, Chongqing University of Posts and Telecommunications, Chongqing
来源：
Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology | 2020年 / 42卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Compressive Sensing (CS); Generalized Orthogonal Matching Pursuit (gOMP); Grant-free Non-Orthogonal Multiple Access (NOMA); Multi-user detection; Optimal number of indices;
D O I：
10.11999/JEIT11_dzyxxxb-42-3-621
中图分类号：
学科分类号：
摘要：
As one of the key 5G technologies, Non-Orthogonal Multiple Access (NOMA) can improve spectrum efficiency and increase the number of user connections by utilizing the resources in a non-orthogonal manner. In the uplink grant-free NOMA system, the Compressive Sensing (CS) and generalized Orthogonal Matching Pursuit (gOMP) algorithm are introduced in active user and data detection, to enhance the system performance. The gOMP algorithm is literally generalized version of the Orthogonal Matching Pursuit (OMP) algorithm, in the sense that multiple indices are identified per iteration. Meanwhile, the optimal number of indices selected per iteration in the gOMP algorithm is addressed to obtain the optimal performance. Simulations verify that the gOMP algorithm with optimal number of indices has better recovery performance, compared with the greedy pursuit algorithms and the Gradient Projection Sparse Reconstruction (GPSR) algorithm. In addition, given different system configurations in terms of the number of active users and subcarriers, the proposed gOMP with optimal number of indices also exhibits better performance than that of the other algorithms mentioned in this paper. © 2020, Science Press. All right reserved.
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收藏
页码：621 / 628
页数：7
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