Grassmannian Constellation Based on Antipodal Points and Orthogonal Design and Its Simplified Detecting Algorithm
Joint Authors
Peng, Li
Hu, Dacong
Zhang, Lin
Qin, Zhen
Source
Journal of Computer Networks and Communications
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-04-03
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
This study presents a framework of the unitary space time modulation (USTM) constellation based on antipodal points over Grassmannian manifold.
The antipodal constellation enables an intrinsic simplified ML detecting algorithm.
The algebraic orthogonal USTM constellation is also an antipodal constellation which, apart from being adaptive to the antipodal simplified ML detector, also has another simplified ML detector based on its self-indexing features, and the latter is simpler because of getting rid of the matrix operation.
A searching orthogonal USTM constellation based on the grid search algorithm is obtained under the presented framework and its minimum Frobenius chordal distance and simulation performance are be superior to those of the algebraic orthogonal USTM constellation.
American Psychological Association (APA)
Peng, Li& Hu, Dacong& Zhang, Lin& Qin, Zhen. 2017. Grassmannian Constellation Based on Antipodal Points and Orthogonal Design and Its Simplified Detecting Algorithm. Journal of Computer Networks and Communications،Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1173326
Modern Language Association (MLA)
Peng, Li…[et al.]. Grassmannian Constellation Based on Antipodal Points and Orthogonal Design and Its Simplified Detecting Algorithm. Journal of Computer Networks and Communications No. 2017 (2017), pp.1-8.
https://search.emarefa.net/detail/BIM-1173326
American Medical Association (AMA)
Peng, Li& Hu, Dacong& Zhang, Lin& Qin, Zhen. Grassmannian Constellation Based on Antipodal Points and Orthogonal Design and Its Simplified Detecting Algorithm. Journal of Computer Networks and Communications. 2017. Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1173326
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1173326