This paper presents an analysis for optimal design of switched beamforming applied to a linear array for wireless communication systems. The beam switching scheme provides coverage of a given sector in azimuth and controls the sidelobe level simultaneously. The analysis was developed considering arrays composed of Quasi-Yagi elements. The model assumes a user moving in the azimuthal direction under a constant velocity and with an estimation of the signal-to-noise ratio (SNR) at the mobile user (MU). The radio base station applies the beam that yields the best performance during transmission. The decision is based on the feedback information received from the MU. The goal of the analysis is to determine the best trade-off between the array size and number of feedback bits necessary to maximize the SNR at the receiver. The results show that a compromise between the number of beam-pointing directions and the array size should be taken into consideration for a wireless communication system design.

Global Navigation Satellite System (GNSS) Radio Occultation (RO) has provided high-quality atmospheric data assimilated in Numerical Weather Prediction (NWP) models and climatology studies for more than 20 years. In the satellite–satellite GNSS-RO geometry, the measurements are susceptible to ionospheric scintillation depending on the solar and geomagnetic activity, seasons, geographical location and local time. This study investigates the application of the Support Vector Machine (SVM) algorithm in developing an automatic detection model of F-layer scintillation in GNSS-RO measurements using power spectral density (PSD). The model is intended for future analyses on the influence of space weather and solar activity on RO data products over long time periods. A novel data set of occultations is used to train the SVM algorithm. The data set is composed of events at low latitudes on 15–20 March 2015 (St. Patrick’s Day geomagnetic storm, high solar flux) and 14–19 May 2018 (quiet period, low solar flux). A few conditional criteria were first applied to a total of 5340 occultations to define a set of 858 scintillation candidates. Models were trained with scintillation indices and PSDs as training features and were either linear or Gaussian kernel. The investigations also show that besides the intensity PSD, the (excess) phase PSD has a positive contribution in increasing the detection of true positives.

This is the accepted version of a paper published in IEEE Geoscience and Remote Sensing Letters. This paper has been peer-reviewed but does not include the final publisher proofcorrections or journal pagination.

Like any other system relying on transionospheric propagation, Global Navigation Satellite System (GNSS) Radio Occultation (GNSS‐RO) is affected by ionospheric conditions during measurements. Regions of plasma irregularities in F region create abrupt gradients in the distribution of ionized particles. Radio signals propagated through such regions suffer from constructive and destructive contributions in phase and amplitude, known as scintillations. Different approaches have been proposed in order to model and reproduce the wave propagation through ionospheric irregularities. We present simulations considering single‐slope power law model of irregularities integrated with Multiple Phase Screen (MPS) propagation. In this work, the capability of the scintillation model to reproduce features in low‐latitude MetOp measurements in the early hours of DOY 76, 2015 is evaluated. Power spectral density (PSD) analysis, scintillation index, decorrelation time, and standard deviation of neutral bending angle are considered in the comparison between the simulations and RO measurements. The results demonstrate the capability of the simulator to replicate an equivalent error contribution to the neutral bending angle measurement in cases of moderate to strong scintillation.

This paper presents a four-element linear array composed of E-shaped microstrip antennas designed to switchedbeam application in ISM (Industrial, Scientific and Medical) radio band. Particle Swarm Optimization (PSO) algorithm is used to optimize four different sets of amplitude and progressive phase shift to achieve four distinct radiation patterns controlling the major lobe direction and sidelobe level. For this application, two restrictive approaches are presented for the implementation of PSO in order to guide the algorithm to feasible solutions.