Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/712
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dc.contributor.authorDaba, Jihad S.en_US
dc.contributor.authorJreije, Philipen_US
dc.date.accessioned2020-12-23T08:35:27Z-
dc.date.available2020-12-23T08:35:27Z-
dc.date.issued2010-
dc.identifier.urihttps://scholarhub.balamand.edu.lb/handle/uob/712-
dc.description.abstractAntenna diversity has been shown to improve mean signal strength and reduce signal level fluctuations in the fading channel. Combinational techniques such as Maximum Ratio Combination (MRC) or Equal Gain Combination (EGC) use the multiple signal branches that exist in the wireless channel advantageously by improving the antenna diversity and performance. MRC provides better performance than EGC, but the disadvantage of this technique, although optimal, is the complexity in its implementation since it requires SNR estimation algorithms. We introduce a novel combination technique termed Root-Mean-Square Gain Combination (RMSGC). We investigate the structure of this scheme using BPSK and its performance is quantified in terms of bit error rate (BER) and a novel metric termed signal-to-scattering noise ratio or SNR peakedness. We found that RMSGC is "near optimal" in the sense that it produced results superior to EGC and very close to MRC but with much less complexity at the receiver and without the need for channel amplitudes estimation. The results of this research are promising and can find applications in internet-based 4G wireless communication comprising small pico- and femto-cells.en_US
dc.format.extent5 p.en_US
dc.language.isoengen_US
dc.publisherWSEAS Pressen_US
dc.subjectBit error rateen_US
dc.subjectEqual gain combiningen_US
dc.subjectMaximum ratio combiningen_US
dc.subjectRoot-mean-square gain combiningen_US
dc.subjectSignal-to-scattering noise ratioen_US
dc.subjectSingle-input multiple-output channelsen_US
dc.titleA novel receiver diversity combining technique for internet-based 4G wireless communicationen_US
dc.typeConference Paperen_US
dc.relation.conferenceInternational Conference on Signal Processing, Robotics and Automation (ISPRA) (9th : 20-22 February 2010 : University of Cambridge, Cambridge, United Kingdom)en_US
dc.contributor.affiliationDepartment of Electrical Engineeringen_US
dc.description.startpage127en_US
dc.description.endpage132en_US
dc.date.catalogued2018-02-05-
dc.description.statusPublisheden_US
dc.identifier.OlibID177445-
dc.identifier.openURLhttp://www.wseas.us/e-library/conferences/2010/Cambridge/ISPRA/ISPRA-21.pdfen_US
dc.relation.ispartoftextProceedings of the 9th International Conference on Signal Processing, Robotics and Automation (ISPRA'10)en_US
dc.provenance.recordsourceOliben_US
Appears in Collections:Department of Electrical Engineering
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