Please use this identifier to cite or link to this item: http://repositorio.ufc.br/handle/riufc/60180
Type: Artigo de Evento
Title: Estimation of Very Large MIMO Channels Using Compressed Sensing
Title in English: Estimation of Very Large MIMO Channels Using Compressed Sensing
Authors: Araújo, Daniel Costa
Almeida, André Lima Férrer de
Mota, João César Moura
Hui, Dennis
Keywords: Very-large MIMO channels;Compressed sensing;Sparsity;Channel estimation;Matching pursuit
Issue Date: 2013
Publisher: https://www.sbrt.org.br/sbrt2013
Citation: ARAÚJO, Daniel Costa; ALMEIDA, André Lima Férrer de; MOTA, João Cesar Moura; HUI, Dennis. Estimation of very large MIMO channels using compressed sensing . In: SIMPÓSIO BRASILEIRO DE TELECOMUNICAÇÕES - SBrT, XXXI., 01-04 dez. 2013, Fortaleza, CE. Anais[...], Fortaleza, CE., 2013.
Abstract in Brazilian Portuguese: In this paper, we propose an efficient pilot-assisted technique for the estimation of very-large MIMO (multiple-input multiple-output) channels exploiting the inherent sparsity of the channel. We first obtain an appropriate sparse decomposition model from a virtual channel representation of the very-large MIMO channel. Based on this model, we capitalize on a fundamental result of the compressed sensing (CS) to show that the channel matrix can be accurately estimated from very short training sequences compared to the number of used transmit antennas. We compare the normalized mean square error (NMSE) obtained using the proposed CS-based channel estimator, the least-square (LS) estimator and the Cramer-Rao lower bound (CRLB). The simulation results show that the proposed estimator obtains good performance, being 5 dB from the CRLB.
URI: http://www.repositorio.ufc.br/handle/riufc/60180
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