This paper deals with the reconstruction of two-dimensional objects from laboratory-controlled data in microwave tomography. This inverse problem is commonly ill-posed and nonlinear, therefore we propose to solve it in a Bayesian estimation framework using an iterative scheme to solve the optimization problem. This approach allows us to introduce a priori knowledge about the object function to be reconstructed. The experimental data were obtained in a controlled environment at Institut Fresnel (Marseille, France). The considered targets are either metallic or dielectric homogeneous cylinders. In this paper, the authors have only considered the data corresponding to the transverse magnetic polarization case. For these targets, the presented results show the potentiality of the proposed regularization scheme and the interest of these experimental data for testing inverse algorithms.

No abstract

No abstract

This letter presents a comparative evaluation between three different behavioral models to perform digital predistortion (DPD) that enhances the linearity of radio‐over‐fiber (RoF)‐based front haul links for the mobile network. In particular, the intention is to jump out of the volterra box and propose models based on segmentation approach. Especially the decomposed vector rotation (DVR) model is compared to volterra polynomials such as memory and generalized memory polynomial (GMP) architectures. DPD is employed to RoF links that are based on distributed feedback laser emitting at 1310 nm, and standard single‐mode fiber for long‐term evolution 20‐MHz signal with 256‐QAM modulation format. The effectiveness of the digital predistortion methodology is investigated for varying input powers in terms of normalized mean square error, adjacent channel power ratio, and error vector magnitude. The experimental results demonstrate that DVR achieves elevated linearization when compared to memory polynomial and GMP models.

No abstract

No abstract

The article proposes a Digital Predistortion (DPD) methodology that substantially meliorates the linearity of limited range Mobile Front Haul links for the extant Long-Term Evolution (LTE) and future (5G) networks. Specifically, the DPD is employed to Radio over Fiber links that contrive of Vertical Cavity Surface Emitting Lasers (VCSELs) working at 850 nm. Both, Memory and Generalized Memory Polynomial models are implied to Single Mode (SM) and Multi-Mode (MM) VCSELs respectively. The effectiveness of the proposed DPD methodology is analyzed in terms of Normalized Mean Square Error, Normalized Magnitude, Normalized phase and Adjacent Channel Power Ratio. The demonstration has been carried out with a complete (Long Term Evolution) LTE frame of 10 ms having 5 MHz bandwidth with 64-QAM modulation configuration. Additionally, the effectuality of the proposed DPD technique is evaluated for varying levels of input power and link lengths. The experimental outcomes signify the novel capability of the implied DPD methodology for different link lengths to achieve higher system linearization.

The article demonstrates a novel Digital Predistortion (DPD) architecture for Mobile Front Haul links for the advanced Long-Term Evolution (LTE) and upcoming 5G networks. Precisely, the use of a feedback approximation method has been proposed and experimentally demonstrated herein that simplifies the complexities in realizing the practical DPD technique for Multi-Mode VCSELs and Multi-Mode Fibers based Radio over Fiber systems. As a figure of merit, linearization efficiency is provided in terms of Adjacent Channel Power Ratio, Normalized Mean Square Error and Error Vector Magnitude referring to a complete LTE frame occupying 10 MHz with 256-QAM modulation format.