非正交多址技术中利用对称矩阵的用户分组
现有非正交多址接入技术中, 用户分组算法的实现首先对信道相似度门限值进行判断, 选出候选成组用户; 进而对候选成组用户的信道增益差进行比较, 选出最优的成组用户.然而, 上述分步 求解算法中信道相似度门限值的设置存在一定的随机性, 导致候选成组用户的选取不准确, 从而影 响分组结果, 限制系统性能的提升.针对上述问题,提出利用对称矩阵的用户分组算法, 对用户信道 相似度进行非线性变换, 而后将用户信道相似度和增益差线性求和构建成新的信道信息矩阵, 进一步利用该矩阵的对称性进行求解.仿真分析表明该方法分组结果比设置门限的传统方法更优, 在不同用户数目时系统容量均得到提升.在传统方法门限值为0.9...
Saved in:
Published in | 电讯技术 Vol. 57; no. 1; pp. 9 - 13 |
---|---|
Main Author | |
Format | Journal Article |
Language | Chinese |
Published |
重庆邮电大学 移动通信技术重庆市重点实验室,重庆,400065
2017
|
Subjects | |
Online Access | Get full text |
ISSN | 1001-893X |
DOI | 10.3969/j.issn.1001-893x.2017.01.002 |
Cover
Summary: | 现有非正交多址接入技术中, 用户分组算法的实现首先对信道相似度门限值进行判断, 选出候选成组用户; 进而对候选成组用户的信道增益差进行比较, 选出最优的成组用户.然而, 上述分步 求解算法中信道相似度门限值的设置存在一定的随机性, 导致候选成组用户的选取不准确, 从而影 响分组结果, 限制系统性能的提升.针对上述问题,提出利用对称矩阵的用户分组算法, 对用户信道 相似度进行非线性变换, 而后将用户信道相似度和增益差线性求和构建成新的信道信息矩阵, 进一步利用该矩阵的对称性进行求解.仿真分析表明该方法分组结果比设置门限的传统方法更优, 在不同用户数目时系统容量均得到提升.在传统方法门限值为0.95时, 所提算法系统容量在用户数为16时提升了13.4 Mb/s. |
---|---|
Bibliography: | In the non-orthogonal multiple access( NOMA) technology,the existing user clustering algorithm is achieved by judging the threshold value of channel similarity to get the candidate users firstly,and then the optimal grouping users are selected by comparing the channel gain-difference of the candidate grouping users. However,the threshold setting of channel similarity has a certain randomness which leads to inaccu-racy of the selection of candidate grouping users in the above multi-stage algorithm,and further affects the results of user clustering and improvement of system performance. In order to solve above problem,a user clustering algorithm using symmetric matrix in NOMA technology is proposed,wherein a nonlinear transfor-mation of channel similarity is performed,and then a new matrix which denotes channel state information of user channel similarity and user channel gian-difference is constructed. Furthermore,all the solutions of user clustering groups can be obtained by utilizing symmetry characteristic |
ISSN: | 1001-893X |
DOI: | 10.3969/j.issn.1001-893x.2017.01.002 |