室内可见光多用户MIMO系统改进BD预编码算法  

Optimal BD Precoding Algorithm for Indoor Visible Light Multiuser MIMO System

作　　者：吴鹏飞[1] 潘婷 WU Peng-Fei;PAN Ting(School of Automation and Information Engineering,Xi’an University of Technology,Xi’an 710048,China)

机构地区：[1]西安理工大学自动化与信息工程学院,西安710048

出　　处：《计算机系统应用》2022年第12期227-234,共8页Computer Systems & Applications

摘　　要：块对角化(block diagonalization,BD)算法是一种多输入多输出的传统线性预编码算法,其核心思想是通过奇异值分解(singular value decomposition,SVD)找到干扰矩阵零空间的正交基,从而完全消除多用户干扰(multiuser interference,MUI),但是随着收发端数目的增多,BD预编码算法所需的计算复杂也大大增加,成为了制约其发展的关键因素之一.为此,本文提出了一种改进的低复杂度BD算法——基于正交分解中的施密特正交化求逆与格基规约操作的组合算法,对传统BD算法两次高复杂度操作的奇异值分解用施密特正交化和格基规约操作进行替换,从而降低算法复杂度.结果表明,本文改进算法的计算复杂度上降低了46.7%,系统和容量上得到了2–10 bits/Hz的提高,同时误码率上得到了2个量级的优化.Block diagonalization(BD)belongs to a traditional linear precoding algorithm with multiple inputs and outputs,and its core idea is to find the orthogonal basis of the null space in interference matrixes through singular value decomposition(SVD),so as to eliminate the multiuser interference(MUI).However,as the number of transmitters and receivers increases,the BD precoding algorithm faces more complex computation,which has become one of the key factors restricting its development.Therefore,this study proposes an optimal low-complexity BD algorithm.The algorithm is based on the combination algorithm of Schmidt orthogonalization inversion and lattice reduction operation in orthogonal decomposition,and it replaces the SVD of two high-complexity operations on the traditional BD algorithm by Schmidt orthogonalization inversion and lattice reduction operation and thus reduces the algorithm complexity.The results show that the computational complexity of the optimal algorithm is reduced by 46.7%,and the system and capacity are increased by 2–10 bits/Hz.Furthermore,the bit error rate is improved by two orders of magnitude.

关 键 词：块对角化算法 多输入多输出 算法复杂度 奇异值分解 多用户干扰 

分 类 号：TN929.1[电子电信—通信与信息系统]