Distributive estimation of frequency selective channels for massive MIMO systems

Alam Zaib; Mudassir Masood; Mounir Ghogho; Tareq Y. Al-Naffouri

doi:10.1109/eusipco.2015.7362511

Distributive estimation of frequency selective channels for massive MIMO systems

Alam Zaib, Mudassir Masood, Mounir Ghogho, Tareq Y. Al-Naffouri

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

We consider frequency selective channel estimation in the uplink of massive MIMO-OFDM systems, where our major concern is complexity. A low complexity distributed LMMSE algorithm is proposed that attains near optimal channel impulse response (CIR) estimates from noisy observations at receive antenna array. In proposed method, every antenna estimates the CIRs of its neighborhood followed by recursive sharing of estimates with immediate neighbors. At each step, every antenna calculates the weighted average of shared estimates which converges to near optimal LMMSE solution. The simulation results validate the near optimal performance of proposed algorithm in terms of mean square error (MSE). © 2015 EURASIP.

Original language	English (US)
Title of host publication	2015 23rd European Signal Processing Conference (EUSIPCO)
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	889-893
Number of pages	5
ISBN (Print)	9780992862633
DOIs	https://doi.org/10.1109/eusipco.2015.7362511
State	Published - Dec 28 2015

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10.1109/eusipco.2015.7362511

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@inproceedings{082f01050baa40f8867c40c2757c0394,

title = "Distributive estimation of frequency selective channels for massive MIMO systems",

abstract = "We consider frequency selective channel estimation in the uplink of massive MIMO-OFDM systems, where our major concern is complexity. A low complexity distributed LMMSE algorithm is proposed that attains near optimal channel impulse response (CIR) estimates from noisy observations at receive antenna array. In proposed method, every antenna estimates the CIRs of its neighborhood followed by recursive sharing of estimates with immediate neighbors. At each step, every antenna calculates the weighted average of shared estimates which converges to near optimal LMMSE solution. The simulation results validate the near optimal performance of proposed algorithm in terms of mean square error (MSE). {\textcopyright} 2015 EURASIP.",

author = "Alam Zaib and Mudassir Masood and Mounir Ghogho and Al-Naffouri, {Tareq Y.}",

note = "KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: KAUST, King Abdullah University of Science and Technology",

year = "2015",

month = dec,

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doi = "10.1109/eusipco.2015.7362511",

language = "English (US)",

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pages = "889--893",

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TY - GEN

T1 - Distributive estimation of frequency selective channels for massive MIMO systems

AU - Zaib, Alam

AU - Masood, Mudassir

AU - Ghogho, Mounir

AU - Al-Naffouri, Tareq Y.

N1 - KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: KAUST, King Abdullah University of Science and Technology

PY - 2015/12/28

Y1 - 2015/12/28

N2 - We consider frequency selective channel estimation in the uplink of massive MIMO-OFDM systems, where our major concern is complexity. A low complexity distributed LMMSE algorithm is proposed that attains near optimal channel impulse response (CIR) estimates from noisy observations at receive antenna array. In proposed method, every antenna estimates the CIRs of its neighborhood followed by recursive sharing of estimates with immediate neighbors. At each step, every antenna calculates the weighted average of shared estimates which converges to near optimal LMMSE solution. The simulation results validate the near optimal performance of proposed algorithm in terms of mean square error (MSE). © 2015 EURASIP.

AB - We consider frequency selective channel estimation in the uplink of massive MIMO-OFDM systems, where our major concern is complexity. A low complexity distributed LMMSE algorithm is proposed that attains near optimal channel impulse response (CIR) estimates from noisy observations at receive antenna array. In proposed method, every antenna estimates the CIRs of its neighborhood followed by recursive sharing of estimates with immediate neighbors. At each step, every antenna calculates the weighted average of shared estimates which converges to near optimal LMMSE solution. The simulation results validate the near optimal performance of proposed algorithm in terms of mean square error (MSE). © 2015 EURASIP.

UR - http://hdl.handle.net/10754/621361

UR - http://ieeexplore.ieee.org/document/7362511/

UR - http://www.scopus.com/inward/record.url?scp=84963958029&partnerID=8YFLogxK

U2 - 10.1109/eusipco.2015.7362511

DO - 10.1109/eusipco.2015.7362511

M3 - Conference contribution

SN - 9780992862633

SP - 889

EP - 893

BT - 2015 23rd European Signal Processing Conference (EUSIPCO)

PB - Institute of Electrical and Electronics Engineers (IEEE)

ER -

Distributive estimation of frequency selective channels for massive MIMO systems

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