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This paper is focused on providing a viable solution to wearable antenna performance disconcertment caused by the underlying human body. Direct placement of the antenna on the body yields undesired results owing to the frequency detuning effect. The simplest possible way out is to make use of a metallic reflector. Hence, a reflector backed antenna is presented for 5.8 GHz ISM band with total lateral dimensions of 28 × 28 × 13.58 mm3. The reflector makes use of a conformal high dielectric laminate coated with a thin copper layer owing to which the assembled design achieves low SAR (Specific Absorption Rate). The prototype provides excellent results at the cost of some extra volume occupation in an off-body direction. Another AMC (Artificial Magnetic Conductor) backed technique is followed and implemented separately to have the structural compactness lacking in the former case. The antenna at hand is backed by a 2 × 2 array of AMC unit cells. The overall design dimensions are reduced. The reflector backed design achieves 8.2 dB gain, above 90% efficiency, and 99% bandwidth overlap with the primary antenna. The AMC backed design provides good spectrum coverage from 5.73 to 5.94 GHz with high gain. Free space response, on-body performance, and investigation of SAR analysis of the proposed designs substantiate effective wireless data transfer in body-centric communication., QC 20230213

This work proposes a new computational framework for learning a structured generative model for real-world datasets. In particular, we propose to learn a Closed-loop Transcriptionbetween a multi-class, multi-dimensional data distribution and a Linear discriminative representation (CTRL) in the feature space that consists of multiple independent multi-dimensional linear subspaces. In particular, we argue that the optimal encoding and decoding mappings sought can be formulated as a two-player minimax game between the encoder and decoderfor the learned representation. A natural utility function for this game is the so-called rate reduction, a simple information-theoretic measure for distances between mixtures of subspace-like Gaussians in the feature space. Our formulation draws inspiration from closed-loop error feedback from control systems and avoids expensive evaluating and minimizing of approximated distances between arbitrary distributions in either the data space or the feature space. To a large extent, this new formulation unifies the concepts and benefits of Auto-Encoding and GAN and naturally extends them to the settings of learning a both discriminative and generative representation for multi-class and multi-dimensional real-world data. Our extensive experiments on many benchmark imagery datasets demonstrate tremendous potential of this new closed-loop formulation: under fair comparison, visual quality of the learned decoder and classification performance of the encoder is competitive and arguably better than existing methods based on GAN, VAE, or a combination of both. Unlike existing generative models, the so-learned features of the multiple classes are structured instead of hidden: different classes are explicitly mapped onto corresponding independent principal subspaces in the feature space, and diverse visual attributes within each class are modeled by the independent principal components within each subspace.

This paper focuses on the FPGA implementation of a slew-rate reduction (SR) shaping function for envelope tracking (ET) power amplifiers (PAs). The SR envelope has been proved effective to trade-off power efficiency and linearity in ET PA systems where the envelope tracking modulator (ETM) is bandwidth limited. However, the implementation issues need to be addressed when targeting high clock rates to cope with current 5G new radio wide-band signals. This paper shows the FPGA implementation of the SR envelope generation. We explore the use of high-level synthesis (HLS) for the SR envelope generation to evaluate the performance and resource usage of the hardware architecture. The HLS design is also compared with a hand-written hardware description language (HDL) version. An in-depth analysis shows strengths and limitations of the HLS design to meet the timing constraints when considering a throughput of 614.4 MSa/s. © 2022 IEEE., Peer Reviewed, Postprint (published version)

We offer to construct flooring from reinforced concrete precast hollow slabs that ensures structural design of several slabs within floor slab instead of convenient beam-type structural design of separate slab within the flooring. Thus, we have quasi-contour design of operation of flooring slab. Flooring, consisting of several beam slabs within flooring cell in question, has finite bending stiffness in longitudinal direction that depends on geometrical and physical-mechanical parameters and also reinforcement of each separate slab. In transverse direction composite flooring slab has almost zero bending stiffness and bears load due to shear rigidity of the joint and torsion resistance of each slab. This arrangement reduces loads, applied to flooring slab. Represented results of calculations and their comparison by analytical and numerical methods (FEM)