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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Souto, N. & Dinis, R. (2016). MIMO detection and equalization for single carrier systems using the alternating direction method of multipliers. IEEE Signal Processing Letters. 23 (12), 1751-1755
Exportar Referência (IEEE) 
N. M. Souto and R. Dinis,  "MIMO detection and equalization for single carrier systems using the alternating direction method of multipliers", in IEEE Signal Processing Letters, vol. 23, no. 12, pp. 1751-1755, 2016
Exportar BibTeX 
@article{souto2016_1714750002215,
	author = "Souto, N. and Dinis, R.",
	title = "MIMO detection and equalization for single carrier systems using the alternating direction method of multipliers",
	journal = "IEEE Signal Processing Letters",
	year = "2016",
	volume = "23",
	number = "12",
	doi = "10.1109/LSP.2016.2618959",
	pages = "1751-1755",
	url = "http://ieeexplore.ieee.org/document/7593341/"
}
Exportar RIS 
TY  - JOUR
TI  - MIMO detection and equalization for single carrier systems using the alternating direction method of multipliers
T2  - IEEE Signal Processing Letters
VL  - 23
IS  - 12
AU  - Souto, N.
AU  - Dinis, R.
PY  - 2016
SP  - 1751-1755
SN  - 1070-9908
DO  - 10.1109/LSP.2016.2618959
UR  - http://ieeexplore.ieee.org/document/7593341/
AB  - In this letter, a multiple-input multiple-output detection algorithm based on the alternating direction method of the multipliers (ADMM) is proposed for single-carrier transmissions in time dispersive channels. The ADMM is applied as a heuristic to solve the maximum likelihood detection problem for arbitrary signal constellations formulated in the frequency domain. This approach allows most of the decoding steps to be implemented in the frequency domain with an overall reduced complexity cost. Simulation results show that the performances close to the matched filter bound can be attained in large problem sizes, even in overloaded scenarios.
ER  -