Browsing by Author "Ozturk, C."
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Item Open Access Filtering characteristics of hybrid integrated polymer and compound semiconductor waveguides(IEEE, 2002) Ozturk, C.; Huntington, A.; Aydınlı, Atilla; Byun, Y.T.; Dagli, N.This paper reports a study on a compact filter fabricated using hybrid integration of compound semiconductors and polymers. A GaAs epilayer is glued onto a polymer channel waveguide forming a highly asymmetrical directional coupler. This approach results in a narrow band filter due to very different dispersion characteristics of the compound semiconductor and the polymer materials. Furthermore, fiber coupling loss has been significantly reduced, since the input and output coupling is done through the polymer waveguide. Filtering characteristics can be engineered by changing the thickness and the length of the semiconductor epilayer. This can be done precisely using etch stop layers and noncritical lithography. The spectral response of such a filter can also be tuned electronically either using the electro-optic properties of the compound semiconductor or the thermo-optic properties of the polymer.Item Open Access RIS-aided near-field localization under phase-dependent amplitude variations(Institute of Electrical and Electronics Engineers , 2023-08-14) Ozturk, C.; Keskin, M. F.; Wymeersch, H.; Gezici, SinanWe investigate the problem of reconfigurable intelligent surface (RIS)-aided near-field localization of a user equipment (UE) served by a base station (BS) under phase-dependent amplitude variations at each RIS element. Through a misspecified Cramér-Rao bound (MCRB) analysis and a resulting lower bound (LB) on localization, we show that when the UE is unaware of amplitude variations (i.e., assumes unit-amplitude responses), severe performance penalties can arise, especially at high signal-to-noise ratios (SNRs). Leveraging Jacobi-Anger expansion to decouple range-azimuth-elevation dimensions, we develop a low-complexity approximated mismatched maximum likelihood (AMML) estimator, which is asymptotically tight to the LB. To mitigate performance loss due to model mismatch, we propose to jointly estimate the UE location and the RIS amplitude model parameters. The corresponding Cramér-Rao bound (CRB) is derived, as well as an iterative refinement algorithm, which employs the AMML method as a subroutine and alternatingly updates individual parameters of the RIS amplitude model. Simulation results indicate fast convergence and performance close to the CRB. The proposed method can successfully recover the performance loss of the AMML under a wide range of RIS parameters and effectively calibrate the RIS amplitude model online with the help of a user that has an a-priori unknown location.