Novel low-complexity MIMO detection based on constellation shift binary classification
Name
1083762686-MIT.pdf
Description
Full printable version
Size
2.11 MB
Format
Adobe PDF
Checksum (MD5)
e461d56c5b733108cdf48913669880f2
Author(s)
AlHajri, Mohamed Ibrahim
Advisor(s)
Lizhong Zheng.
Alternative Title
Novel low-complexity Multiple Input Multiple Output detection based on constellation shift binary classification
Date Issued
2018
Publisher
Massachusetts Institute of Technology
Abstract
This thesis develops a novel technique for low-complexity MIMO detection known as Constellation Shift Binary Classification (CSBC). The proposed method utilizes the constellation structure to deduce a constellation shift that is used to reduce the problem of detecting the symbol into binary classification. The proposed method is proven to outperform other common techniques such as ZF and LMMSE. The proposed CSBC is a novel MIMO detection technique since it utilizes the constellation structure together with a binary classifier that is based on neural networks.
Description
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 77-86).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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