Localization of DOA trajectories -- Beyond the grid

The direction of arrival (DOA) estimation algorithms are crucial in localizing acoustic sources. Traditional localization methods rely on block-level processing to extract the directional information from multiple measurements processed together. However, these methods assume that DOA remains constant throughout the block, which may not be true in practical scenarios. Also, the performance of localization methods is limited when the true parameters do not lie on the parameter search grid. In this paper we propose two trajectory models, namely the polynomial and bandlimited trajectory models, to capture the DOA dynamics. To estimate trajectory parameters, we adopt two gridless algorithms: i) Sliding Frank-Wolfe (SFW), which solves the Beurling LASSO problem and ii) Newtonized Orthogonal Matching Pursuit (NOMP), which improves over OMP using cyclic refinement. Furthermore, we extend our analysis to include wideband processing. The simulation results indicate that the proposed trajectory localization algorithms exhibit improved performance compared to grid-based methods in terms of resolution, robustness to noise, and computational efficiency

Parameter extraction of Extended Floating Gate Field Effect Transistors (EGFETs): Estimating the threshold voltage, series resistance, and mobility degradation from I-V measurements

Extended Floating Gate Field Effect Transistors (EGFETs) are CMOS-compatible floating gate devices capable of detecting charges on their sensing area by the relative shifts in current-voltage (I-V) characteristics. The I-V shifts are generally computed by measuring the EGFET parameters in the strong inversion region of operation. This could lead to errors in estimating the device sensitivity because the simple I-V model ignores the mobility degradation and series resistance effects in EGFETs. Our goal is to model these parasitic effects and present methods to extract the key device parameters. We derive an analytical I-V model for EGFETs in the linear region of transistor operation, accounting for both the mobility degradation and series resistance effects. Based on the analytical model, three methods are presented to estimate the key parameters, namely the threshold voltage, series resistance, surface roughness parameter, low-field mobility, and effective mobility from the I-V characteristics, gate transconductance, and drain conductance. The peak transconductance method is used as a benchmark for comparing the extracted threshold voltages. Silicon-based EGFET devices are fabricated, and their I-V characteristics are measured with deionized water and three polyelectrolytes. From the I-V data, the parameter extraction methods are used to compute the values of the key parameters, and the suitability of each method is discussed. The gate transconductance methods show good agreement between the values for the key parameters, while the drain transconductance method gives lower values of the key parameters. There is scope to improve the presented methods by incorporating the effects of substrate bias and asymmetric series resistance for new extended-gate device architectures, including solution-based organic field-effect transistors.Comment: 19 pages, 8 figures, preprin

Random Matrix Model for Nakagami-Hoyt Fading

Random matrix model for the Nakagami-q (Hoyt) fading in multiple-input multiple-output (MIMO) communication channels with arbitrary number of transmitting and receiving antennas is considered. The joint probability density for the eigenvalues of H{\dag}H (or HH{\dag}), where H is the channel matrix, is shown to correspond to the Laguerre crossover ensemble of random matrices and is given in terms of a Pfaffian. Exact expression for the marginal density of eigenvalues is obtained as a series consisting of associated Laguerre polynomials. This is used to study the effect of fading on the Shannon channel capacity. Exact expressions for higher order density correlation functions are also given which can be used to study the distribution of channel capacity.Comment: 11 pages, 4 figure

AUGMENTED REALITY BASED USER GUIDANCE FOR OPTIMAL COLLABORATION EXPERIENCE IN A WIFI NETWORK

Techniques are described herein for recommending locations to users that are close to them based on the users\u27 current application requirement and current network conditions. Augmented Reality (AR) is then used to guide the user towards an area of good service. Metadata is shared back with a network controller for future requirements and guidance of other users

WAKE UP RADIO PROTECTION FROM DENIAL OF SERVICE ATTACK BASED ON BASEBAND MONITORING

A malicious attacker can drain the batteries of Internet of Things (IoT) devices by sending many wake up radio (WUR) transmissions. Accordingly, techniques are provided herein to enable an Access Point (AP) to detect any malicious WUR requests. The AP may intelligently mitigate the attack with the help of the stations (STAs)

Rhabdomyolysis and myopericarditis with renal failure in a patient of status epilepticus

Rhabdomyolysis is characterized by the destruction and leakage of muscle cell components into the circulation. Sustained and prolonged muscle activity is an important factor causing the same. Most of the reported cases in the literature were due to status epilepticus. We report the case of a 25-year-old male who developed acute renal failure and myopericarditis in association with non-traumatic rhabdomyolysis following status epilepticus