1. Large-Scale MIMO Receiver Based on Finite-Alphabet Sparse Detection and Concave-Convex Optimization
- Author
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Abdeldjalil Aissa-El-Bey, Yacine Meslem, Mustapha Djeddou, École Militaire Polytechnique [Alger] (EMP), Lab-STICC_IMTA_CACS_COM, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT), Département Signal et Communications (IMT Atlantique - SC), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), and Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)
- Subjects
Scheme (programming language) ,Concave-convex optimiza- tion ,Computer science ,Finite-alphabet signals ,MIMO ,Detector ,020302 automobile design & engineering ,020206 networking & telecommunications ,Scale (descriptive set theory) ,02 engineering and technology ,Multiplexing ,0203 mechanical engineering ,Convex optimization ,0202 electrical engineering, electronic engineering, information engineering ,Alphabet ,Large-scale MIMO ,Convex function ,computer ,Algorithm ,Sparse representation ,[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing ,computer.programming_language ,Computer Science::Information Theory - Abstract
International audience; In this paper, we propose a new receiver for detecting signals in large-scale Spatially Multiplexed (SP) Multiple-Input-Multiple-Output (MIMO) systems that may have fewer receive antennas than transmitted symbols (overloaded case). Relying on the idea of Finite-Alphabet Sparse (FAS) detection, we formulate the Maximum Likelihood (ML) criterion as a Difference-of-Convex (DC) programming problem that can be simply and efficiently solved using the Concave-Convex Procedure (CCP) technique. Since, the considered problem is non-convex, we theoretically discuss the behavior of the derived algorithm. Numerical experiments confirm the superiority of the proposed detection scheme, when compared with recent detection methods based on convex optimization, in a variety of large-scale MIMO transmission scenarios including the overloaded case.
- Published
- 2020