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dc.contributor.authorAl-Naffouri, Tareq Y.
dc.date.accessioned2016-11-03T06:58:33Z
dc.date.available2016-11-03T06:58:33Z
dc.date.issued2016-01-21
dc.identifier.citationAl-Naffouri TY (2015) Efficient channel estimation in massive MIMO systems - a distributed approach. 2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP). Available: http://dx.doi.org/10.1109/CAMSAP.2015.7383821.
dc.identifier.doi10.1109/CAMSAP.2015.7383821
dc.identifier.urihttp://hdl.handle.net/10754/621362
dc.description.abstractWe present two efficient algorithms for distributed estimation of channels in massive MIMO systems. The two cases of 1) generic, and 2) sparse channels is considered. The algorithms estimate the impulse response for each channel observed by the antennas at the receiver (base station) in a coordinated manner by sharing minimal information among neighboring antennas. Simulations demonstrate the superior performance of the proposed methods as compared to other methods.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectFrequency response
dc.subjectMIMO
dc.subjectOFDM
dc.subjectWireless communication
dc.titleEfficient channel estimation in massive MIMO systems - a distributed approach
dc.typeConference Paper
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.identifier.journal2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)
dc.conference.date13 December 2015 through 16 December 2015
dc.conference.name6th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2015
dc.contributor.institutionDepartment of Electrical Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia
kaust.personAl-Naffouri, Tareq Y.
dc.date.published-online2016-01-21
dc.date.published-print2015-12


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