This article presents a sub-6GHz ISM-band flexible wearable MIMO antenna array for wireless body area networks (WBANs) and biomedical telemetry devices. The array is based on metasurface inspired technology. The antenna array consists of 2×2 matrix of triangular-shaped radiation elements that were realized on 0.8 mm thick Rogers RT/duroid 5880 substrate. Radiation characteristics of the array are enhanced by isolating the surface current interaction between the individual radiators in the array. This is achieved by inserting an electromagnetic bandgap (EBG) decoupling structure between the radiating elements. The radiating elements were transformed into a metasurface by etching sub-wavelength slots inside them. The periodic arrangement of slots acts like resonant scatterers that manipulate the electromagnetic response of the surface. Results confirm that by employing the decoupling structure and sub-wavelength slots the isolation between the radiators is significantly improved (>34.8 dB). Moreover, there is an improvement in the array’s fractional bandwidth, gain and the radiation efficiency. The optimized array design for operation over 5.0-6.6 GHz has an average gain and efficiency of 10 dBi and 83%, respectively. Results show that the array’s performance is not greatly affected by a certain amount of bending. In fact, the antenna maintains a gain between 8.65-10.5 dBi and the efficiency between 77-83%. The proposed MIMO antenna array is relatively compact, can be easily fabricated on one side of a dielectric material, allows easy integration with RF circuitry, is robust, and maintains its characteristics with some bending. These features make it suitable for various wearable applications and biomedical telemetry devices.

Visually impaired people seek social integration, yet their mobility is restricted. They need a personal navigation system that can provide privacy and increase their confidence for better life quality. In this paper, based on deep learning and neural architecture search (NAS), we propose an intelligent navigation assistance system for visually impaired people. The deep learning model has achieved significant success through well-designed architecture. Subsequently, NAS has proved to be a promising technique for automatically searching for the optimal architecture and reducing human efforts for architecture design. However, this new technique requires extensive computation, limiting its wide use. Due to its high computation requirement, NAS has been less investigated for computer vision tasks, especially object detection. Therefore, we propose a fast NAS to search for an object detection framework by considering efficiency. The NAS will be used to explore the feature pyramid network and the prediction stage for an anchor-free object detection model. The proposed NAS is based on a tailored reinforcement learning technique. The searched model was evaluated on a combination of the Coco dataset and the Indoor Object Detection and Recognition (IODR) dataset. The resulting model outperformed the original model by 2.6% in average precision (AP) with acceptable computation complexity. The achieved results proved the efficiency of the proposed NAS for custom object detection.

Unmanned aerial vehicles (UAVs) need high data rate connectivity, which is achievable through mm-waves and sub-THz bands. The proposed two-port leaky wave MIMO antenna, employing a coplanar proximity technique that combines capacitive and inductive loading, addresses this need. Featuring mesh-like slots and a vertical slot to mitigate open-stopband (OSB) issues, the antenna radiates broadside and bidirectionally. H-shaped slots on a strip enhance port isolation, and a coffee bean metasurface (MTS) boosts radiation efficiency and gain. Simulations and experiments considering various realistic scenarios, each at varying vertical and horizontal distances, show steered beam patterns, circular polarization (CP), and high-gain properties, with a maximum gain of 13.8 dBi, an axial ratio (AR) 9.98 dB, and an envelope correlation coefficient (ECC) <0.003. This design supports drones-to-ground (D2G), drone-to-drone (D2D), and drone-to-satellite (D2S) communications.

A Comparative Study of Sorting Algorithms with FPGA Acceleration by High Level Synthesis