Robust Symbol Detection in Large-Scale Overloaded NOMA Systems

Robust Symbol Detection in Large-Scale Overloaded NOMA Systems

We a framework for the design of low-complexity and high-performance receivers for multidimensional overloaded non-orthogonal multiple access (NOMA) systems. The framework is built upon a novel compressed sensing (CS) regularized maximum likelihood (ML) formulation of the discrete-input detection pr...

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Bibliographic Details
Main Authors: Hiroki Iimori, Giuseppe Thadeu Freitas De Abreu, Takanori Hara, Koji Ishibashi, Razvan-Andrei Stoica, David Gonzalez G., Osvaldo Gonsa
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Open Journal of the Communications Society
Subjects:
Non-orthgonal multi-access (NOMA)
detection
overloaded systems
fractional programming
iterative least square
Online Access:https://ieeexplore.ieee.org/document/9373674/

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