Show simple item record

dc.contributor.authorJamoos, Ali
dc.contributor.authorAldababsa, Mahmoud
dc.date.accessioned2018-08-13T07:34:52Z
dc.date.available2018-08-13T07:34:52Z
dc.date.issued2014-02-01
dc.identifier.issn2356-6140
dc.identifier.urihttps://dspace.alquds.edu/handle/20.500.12213/732
dc.description.abstractWe address the problem of estimating time-varying fading channels in filter bank multicarrier (FBMC/OQAM) wireless systems based on pilot symbols. The standard solution to this problem is the least square (LS) estimator or the minimum mean square error (MMSE) estimator with possible adaptive implementation using recursive least square (RLS) algorithm or least mean square (LMS) algorithm. However, these adaptive filters cannot well-exploit fading channel statistics. To take advantage of fading channel statistics, the time evolution of the fading channel is modeled by an autoregressive process and tracked by Kalman filter. Nevertheless, this requires the autoregressive parameters which are usually unknown. Thus, we propose to jointly estimate the FBMC/OQAM fading channels and their autoregressive parameters based on dual optimal Kalman filters. Once the fading channel coefficients at pilot symbol positions are estimated by the proposed method, the fading channel coefficients at data symbol positions are then estimated by using some interpolation methods such as linear, spline, or low-pass interpolation. The comparative simulation study we carried out with existing techniques confirms the effectiveness of the proposed method.en_US
dc.language.isoen_USen_US
dc.publisherSAGE-Hindawi Access to Researchen_US
dc.titleEstimation of FBMC/OQAM Fading Channels Using Dual Kalman Filtersen_US
dc.typeArticleen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record