Distributed Channel Estimation and Pilot Contamination Analysis for Massive MIMO-OFDM Systems

Handle URI:
http://hdl.handle.net/10754/622535
Title:
Distributed Channel Estimation and Pilot Contamination Analysis for Massive MIMO-OFDM Systems
Authors:
Zaib, Alam; Masood, Mudassir; Ali, Anum; Xu, Weiyu; Al-Naffouri, Tareq Y. ( 0000-0003-2843-5084 )
Abstract:
By virtue of large antenna arrays, massive MIMO systems have a potential to yield higher spectral and energy efficiency in comparison with the conventional MIMO systems. This paper addresses uplink channel estimation in massive MIMO-OFDM systems with frequency selective channels. We propose an efficient distributed minimum mean square error (MMSE) algorithm that can achieve near optimal channel estimates at low complexity by exploiting the strong spatial correlation among antenna array elements. The proposed method involves solving a reduced dimensional MMSE problem at each antenna followed by a repetitive sharing of information through collaboration among neighboring array elements. To further enhance the channel estimates and/or reduce the number of reserved pilot tones, we propose a data-aided estimation technique that relies on finding a set of most reliable data carriers. Furthermore, we use stochastic geometry to quantify the pilot contamination, and in turn use this information to analyze the effect of pilot contamination on channel MSE. The simulation results validate our analysis and show near optimal performance of the proposed estimation algorithms.
KAUST Department:
Electrical Engineering Program
Citation:
Zaib A, Masood M, Ali A, Xu W, Al-Naffouri TY (2016) Distributed Channel Estimation and Pilot Contamination Analysis for Massive MIMO-OFDM Systems. IEEE Transactions on Communications 64: 4607–4621. Available: http://dx.doi.org/10.1109/TCOMM.2016.2593924.
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
IEEE Transactions on Communications
Issue Date:
22-Jul-2016
DOI:
10.1109/TCOMM.2016.2593924
Type:
Article
ISSN:
0090-6778
Sponsors:
This publication is based upon work supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. OSR-2016-KKI-2899.
Additional Links:
http://ieeexplore.ieee.org/document/7519073/
Appears in Collections:
Articles; Electrical Engineering Program

Full metadata record

DC FieldValue Language
dc.contributor.authorZaib, Alamen
dc.contributor.authorMasood, Mudassiren
dc.contributor.authorAli, Anumen
dc.contributor.authorXu, Weiyuen
dc.contributor.authorAl-Naffouri, Tareq Y.en
dc.date.accessioned2017-01-02T09:55:29Z-
dc.date.available2017-01-02T09:55:29Z-
dc.date.issued2016-07-22en
dc.identifier.citationZaib A, Masood M, Ali A, Xu W, Al-Naffouri TY (2016) Distributed Channel Estimation and Pilot Contamination Analysis for Massive MIMO-OFDM Systems. IEEE Transactions on Communications 64: 4607–4621. Available: http://dx.doi.org/10.1109/TCOMM.2016.2593924.en
dc.identifier.issn0090-6778en
dc.identifier.doi10.1109/TCOMM.2016.2593924en
dc.identifier.urihttp://hdl.handle.net/10754/622535-
dc.description.abstractBy virtue of large antenna arrays, massive MIMO systems have a potential to yield higher spectral and energy efficiency in comparison with the conventional MIMO systems. This paper addresses uplink channel estimation in massive MIMO-OFDM systems with frequency selective channels. We propose an efficient distributed minimum mean square error (MMSE) algorithm that can achieve near optimal channel estimates at low complexity by exploiting the strong spatial correlation among antenna array elements. The proposed method involves solving a reduced dimensional MMSE problem at each antenna followed by a repetitive sharing of information through collaboration among neighboring array elements. To further enhance the channel estimates and/or reduce the number of reserved pilot tones, we propose a data-aided estimation technique that relies on finding a set of most reliable data carriers. Furthermore, we use stochastic geometry to quantify the pilot contamination, and in turn use this information to analyze the effect of pilot contamination on channel MSE. The simulation results validate our analysis and show near optimal performance of the proposed estimation algorithms.en
dc.description.sponsorshipThis publication is based upon work supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. OSR-2016-KKI-2899.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.urlhttp://ieeexplore.ieee.org/document/7519073/en
dc.subjectMMSEen
dc.subjectChannel estimationen
dc.subjectmassive MIMOen
dc.subjectstochastic geometryen
dc.subjectOFDMen
dc.titleDistributed Channel Estimation and Pilot Contamination Analysis for Massive MIMO-OFDM Systemsen
dc.typeArticleen
dc.contributor.departmentElectrical Engineering Programen
dc.identifier.journalIEEE Transactions on Communicationsen
dc.contributor.institutionDepartment of Electrical Engineering, COMSATS Institute of Information Technology, Abbottabad, Pakistanen
dc.contributor.institutionDepartment of Electrical Engineering, King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabiaen
dc.contributor.institutionDepartment of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, USAen
dc.contributor.institutionDepartment of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA, USAen
kaust.authorAl-Naffouri, Tareq Y.en
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