Şenol, HabibBaşaran, MehmetErküçük, SerhatMacit, Mustafa CanŞenol, HabibErküçük, Serhat2020-12-162020-12-16202030018-95450018-9545https://hdl.handle.net/20.500.12469/3560https://doi.org/10.1109/TVT.2020.3007341This work investigates the realistic performance of IEEE 802.11af systems released for the efficient spectrum utilization of TV white space (TVWS). These systems are operated over many contiguous or non-contiguous channels based on the TVWS frequency band availability. Accordingly, we consider realistic channel estimation for TVWS system and analyze the corresponding system performance of linear minimum mean square error (LMMSE) and orthogonal matching pursuit (OMP) algorithms. While LMMSE estimates channel path gains assuming perfectly known tap delay locations, OMP estimates both channel path gains and delays. Owing to the realistic implementation and estimating the full channel state information (CSI) of sparse channels, we mainly assess the OMP performance together with the LMMSE estimation for comparison in terms of channel reconstruction and symbol detection errors. To address the channel estimation performance, Bayesian Cramer-Rao bound is derived theoretically for both perfect and imperfect CSI, and confirmed with the simulations. Simulation results demonstrate that the realistic OMP-based symbol detection performance is found to be only 1-2 dB inferior compared to the near-optimal LMMSE-based estimation with known delays in low and medium signal-to-noise-ratio regions, where communication mainly occurs in practice. In addition, the effects of channel multipath number, channel resolution and operation modes on the system performance are studied for different scenarios. The results of this work are important for the practical implementation of IEEE 802.11af-based systems.eninfo:eu-repo/semantics/embargoedAccessBCRBchannel estimationIEEE 802.11afLMMSEOMPsparse channelsymbol detectionTV white spaceRealistic Channel Estimation of IEEE 802.11af Systems in TV White SpaceArticle11066110761069WOS:00058425030001010.1109/TVT.2020.30073412-s2.0-85095684484Q1Q1