Angle Of Departure Research Articles

Simultaneous Channel Estimation and Localization of Terahertz Massive MIMO Systems via Bayesian Tensor Decomposition

In this letter, a Bayesian tensor-based scheme is proposed for simultaneous channel estimation and localization (SCEAL) in wideband terahertz (THz) massive multiple-input multiple-output (MIMO) systems with hybrid analog-digital architectures. Considering the beam squint effect, we construct the received training signal into a sixth-order tensor model, including the angle-of-arrival (AOA)/angle-of-departure (AOD), time delay, and path gains. Then, a real-valued Bayesian inference algorithm is developed to fit the constructed tensor model for SCEAL. The proposed algorithm achieves SCEAL with and without line-of-sight (LOS) path, and offers higher accuracy compared to the state-of-the-art algorithms. Simulations verify the effectiveness of the proposed algorithm.

The impact of particular exercises according to the fluidity of kinetic transfer for some variables Biomechanics for the moment of upgrading and the achievement of a long jump of the talented

The research contained introduction, problem, hypotheses and objectives, as it touched upon the impact of particular exercises according to the fluidity of kinetic transfer on some biomechanical variables at the moment of upgrading for the research sample from the talented long-jumpers . As the research touched on the stages of the smooth transport motion the penultimate step and the last step of the speed. And the starting speed of the body, the angle of departure, the fluidity of motion, the kinetic transfer and the achievement of the sample members. Where the results for the control and experimental groups and the relationship that took place according to the kinetic transfer fluidity of the particular exercises that the researchers used in the study variables. The researchers also reached the results of the control and experimental groups in the variables of the study in the achievement of the sample members in the impact of these particular exercises and what they reached in the pre and posttest of the sample members. The research concluded that the use of such exercises operatively affected according to the fluidity of the kinetic transfer of the biomechanical variables and the achievement of the sample members.

Fine Beam Tracking Using Spatio–Temporal Interpolation in Wireless Power Transfer Systems

The use of transmit beamforming in a radio-frequency wireless power transfer (WPT) system can improve the energy transmission efficiency by concentrating the transmit power in the angle of departure (AoD). Optimal beamforming requires information regarding the AoD or the channel between the transmitter and receiver. A previously proposed WPT system continually estimates the optimal AoD using custom-designed pilot signals, which are known as beam-steered pilot signals and are transmitted periodically at every frame. Herein, we propose a spatio–temporal interpolation technique to improve the accuracy of beam tracking for such a WPT system. Specifically, thin-plate spline interpolation is adopted in the space domain to overcome the limited angular resolution of the beam-steered pilot signals in a three-dimensional channel. In the time domain, polynomial interpolation is performed to track the changing AoD during consecutive frames. Numerical results show that the proposed technique can improve the WPT efficiency as well as the mean square error performance of the beamforming weight vector.

Fast Beam Discovery and Adaptive Transmission Under Frequency Selective Attenuations in Sub-Terahertz Bands

Sub-THz-based communication needs ultra-large antenna arrays to generate pencil-like beams under the stringent requirements of line-of-sight (LoS) to overcome the effect of the rapid attenuation of signal strength, including atmospheric attenuation. In addition, the complexity of attaining narrower beamwidth, which also requires fast and perfect alignment between the TX-RX pair, makes the sector sweeping-based beam discovery approach no longer suitable. To solve these challenging problems, in this paper we propose a leaky waveguide (LWG)-assisted, high-resolution codebook-based beam discovery, precoding, and combining scheme together with an adaptive frequency hopping spread spectrum (FHSS) for a network with relays and small base stations (SBS). The proposed method can help the transmitter quickly determine a suitable beam pattern for an LoS path requiring only limited feedback information. In the beam discovery phase, we use LWG to attain valuable information about the angle of departure (AoD) and angle of arrival (AoA). LWG has also been used to identify frequency selective attenuated regions, which can change from time to time depending on the local atmospheric moisture conditions. To mitigate the impact of such attenuations, we opt for an adaptive Frequency Hopping Spread Spectrum (FHSS). The simulation results indicate that our beam discovery and FHSS based method can achieve a much higher performance than baseline methods.

Reconfigurable Intelligent Surface Aided Position and Orientation Estimation Based on Joint Beamforming With Limited Feedback

The sparsity of millimeter wave (mmWave) channels in angular and temporal domains has been exploited for channel estimation, while the associated channel parameters can be utilized for localization. However, line-of-sight (LoS) blockage makes localization highly challenging, which may lead to big positioning inaccuracy. One promising solution is to employ reconfigurable intelligent surfaces (RIS) to generate virtual line-of-sight (VLoS) paths. Hence, it is essential to investigate the wireless positioning in RIS-aided mmWave systems. In this paper, an adaptive joint LoS and VLoS localization scheme is proposed, where the VLoS is constructed by a beamforming protocol operated between RIS and mobile station (MS). More specifically, to sense the location and orientation of a MS, a novel interlaced scanning beam sweeping algorithm is proposed to acquire the optimal beams. In this algorithm, LoS and VLoS paths are separately estimated and the optimal beams are selected according to the received signal strength so as to mitigate the LoS blockage problem. Then, based on the selected beams and received signal strength, angle of arrival (AoA), angle of departure (AoD), angle of reflection (AoR) and time of arrival (ToA) are estimated. Finally, with the aid of these estimated parameters, the location and orientation of the MS are estimated. We derive the Cramer-Rao lower bounds (CRLBs) for both location estimation and orientation estimation, and compare them with the corresponding results obtained from simulations. We compare the performance of our proposed scheme with that attained by three legacy schemes, when various aspects are considered. The performance results show the superiority of our proposed beam training algorithm, which is capable of achieving a localization error within 15 cm and an orientation error within 0.003 rads. Furthermore, the training overhead is 100 times less than that of the conventional exhaustive search algorithm, while obtaining a 13 dBm power gain when compared with the hierarchical codebook based search algorithm.

Accurate Wideband Channel Estimation for THz Massive MIMO Systems

This letter addresses the wideband channel estimation problem for terahertz (THz) massive multiple input multiple output (MIMO) systems. The proposed wideband channel estimation scheme consists of three stages. First, the wideband channel estimation is formulated as a joint sparse signal recovery problem based on an on-grid signal model; and the coarse estimates of angles of arrivals (AoAs) and angles of departure (AoDs) of the paths can be obtained by an orthogonal matching pursuit (OMP) based method. Then, an expectation-maximization (EM) based method is proposed to refine the estimates of AoAs and AoDs by recasting the wideband channel estimation problem. Finally, given the estimates of AoAs, AoDs and composite path gains, the delays and gains of the paths are further extracted with the help of constructed dictionary matrices. Simulation results show that the proposed scheme can improve channel estimation accuracy by up to 5dB of the signal-to-noise ratio (SNR) compared to the perfect AoAs and AoDs aided oracle least square (LS) method.

ФОРМАЛІЗОВАНИЙ ОПИС ПРОЦЕСУ ЗАКИДАННЯ ЕЛЕМЕНТУ, ЩО ТРАЛИТЬ НАТЯЖНІ ДАТЧИКИ ЦІЛІ ВИБУХОНЕБЕЗПЕЧНИХ ПРЕДМЕТІВ

As a result of the aggression of the Russian Federation in 2014, as well as the large-scale invasion in February 2022, Ukraine became the most explosive contaminated country in the world. The relevance of the issue of reconnaissance and demining of the area from explosive devices both during and in the absence of combat operations has increased many times over. The experience of war shows that the enemy, despite international conventions banning certain types of mine weapons, uses its entire arsenal of mines and improvised explosive devices, which are often set to be unremovable. The most widespread and dangerous IEDs during the war were those with tensioned target sensors (tripwires).Due to the moral and physical obsolescence of reconnaissance and demining equipment in the units of the Armed Forces and the SES of Ukraine, manual reconnaissance and demining is the main method of reconnaissance and demining, which poses a great danger to sappers. To reduce the risk to the personnel of demining groups and pyrotechnic units, it is proposed to use a mechanical means of trawling for UXOs with tension target sensors. Based on the analysis of existing approaches to modeling demining processes, in particular the use of means for trawling tension sensors of explosive objects, a formalized description of the throwing of the element that trawls the tension sensors of the target is proposed, which, unlike the existing ones, takes into account the increase in the specific mass of the trawling means (a combination of the trawling element and the cable) during the flight. One of the most difficult issues in modeling is to determine the dependence of the flight parameters of the trawling element on the dynamics of the mass gain of the cable (cord). The kinematic parameters of the trawling element under study are: angle of departure, range, height, time, and flight speed. The proposed improvements to the mathematical model and the sequence of calculations will improve the accuracy of the results of modeling the process of trawling the tension sensors of an explosive target when substantiating the requirements for this type of demining equipment.

A Non-Stationary 3D-GBSM V2V Channel Model for Wideband Massive MIMO Systems

This letter presents a non-stationary 3D-GBSM vehicle to vehicle (V2V) channel model in tunnel environment based on massive multiple-input multiple-output (MIMO) antenna arrays. Instead of plane wavefront assumptions used in traditional MIMO systems, the proposed channel model considers spherical wavefront assumption for V2V communications. Firstly, the channel impulse response (CIR) and closed-form expression for probability density function (PDF) of angle-of-departure (AoD) and angle-of-arrival (AoA) in elevation and azimuth planes are derived. Afterwards, the expressions for the spatial cross-correlation function (S-CCF) and doppler power spectrum density (DPSD) due to the non-stationarity of transmitting (NT) and receiving (MR) antenna arrays are derived by considering different time separation, antenna arrays spacing, moving velocity, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> -factor for line of sight (LoS) and non-line of sight (NLoS) propagation paths. The statistical characteristics of the proposed V2V wideband massive MIMO model are validated by measurement, analytical, and simulation results, verifying the effectiveness and adaptability of the proposed model in high-speed train (HST) environment.

An ESPRIT-Based Supervised Channel Estimation Method Using Tensor Train Decomposition for mmWave 3-D MIMO-OFDM Systems

This paper focuses on the downlink supervised channel estimation problem for the millimeter wave threedimensional multiple-input multiple-output orthogonal frequency division multiplexing (mmWave 3D MIMO-OFDM) systems, where both the transmitter and the receiver are equipped with uniform rectangular arrays (URAs). Based on the sparse scattering nature, the mmWave channel is modeled as a low-rank higher-order tensor. By formulating the channel and the received training signal as tensors, a fast ESPRIT-based Vandermondestructured tensor decomposition method is proposed to estimate the channel parameters involving angles of arrival and departure (AoAs/AoDs), delays and path gains. In specific, we first establish the relationship of the tensor ranks between the tensor train (TT) model and the higher-order tensor CANDECOMP/PARAFAC (CP) signal model. Then the TT decomposition is used to estimate the signal subspace and derive the shift invariance equation, which exploits the higher-order tensor low-rankness of the signal and the Vandermonde structure in the frequency domain. Based on the derived analytical estimation errors, theoretical justifications are provided to unveil the advantage of using TT decomposition. Moreover, we extend the proposed method in an iterative manner to pursue higher accuracy. According to our simulation results, compared with the state-of-the-art, the proposed method achieves higher estimation accuracy on both the channel parameters and the entire channel. In addition, up to 87% of computing time can be saved in comparison to the current best iterative algorithm in the experiments.

Development and Architecture of the &lt;i&gt;Nepeta transiliensis&lt;/i&gt; (Lamiaceae) Rhizome

The ontogeny and structural organization of the rhizome of Nepeta transiliensis individuals in the high-mountain conditions of the Zailiyskiy Alatau have been studied. Various types of buds (renewal buds, dormant buds) take part in shoot formation, from which various types of elongated shoots are formed. Using the architectural approach to the description of plants, the main structural units – rhizome modules – are identified. Different branching of modules leads to the construction of different rhizome axes. In the rhizomatous axes, the angles of departure of the lateral modules from the maternal one differ, the development of the modules occurs sequentially from the renewal buds or with a delay from the dormant buds. The set of rhizomatous axes forms a branched rhizome complex and leads to the formation of rhizome tiers. In general, the rhizome of N. transiliensis is of the “intermediate” type, which combines the features of a geometric and non-geometric rhizome.

Multi-colony tracking reveals segregation in foraging range, space use, and timing in a tropical seabird

Colonial animals experience density-dependent competition for food, which is posited to influence foraging range and lead to inter-colony segregation. However, such patterns are poorly studied in the tropics, where predictable day lengths, oligotrophic conditions, and facultative foraging may alter the relationships between foraging and intra-specific competition. Here, we GPS-tracked 207 breeding red-footed boobiesSula sula rubripes(RFB) from 4 neighbouring Chagos Archipelago colonies (~1100 to 9200 breeding pairs) in the central Indian Ocean, to determine how foraging strategies (i.e. effort, segregation, and timing) vary with colony, while accounting for sex, monsoon season, stage of reproduction, year, and individual. During incubation and chick-rearing, RFBs commute to pelagic foraging grounds (maximum distance mean ± SE: 112.9 ± 3.7 km; total distance: 298.4 ± 6.2 km) over 1 to 5 d (18.5 ± 1.6 h). Foraging effort was highest at the largest colony, and greater among females than males. Departure angles varied among colonies, leading to foraging areas that were largely spatially segregated. Timing of departures and arrivals were strongly constrained by daylight hours, although females and birds at the largest colony left earliest. Our study highlights the importance of inter-colony differences in tropical seabird foraging, which may relate to different levels of intra-specific competition. Moreover, links between foraging times and colony size suggest a previously undescribed outcome of density-dependent competition, highlighting the importance of understanding colonial living across multiple dimensions.

Одномерная математическая модель колебаний ствола с поперечным сечением произвольной формы

The problem of longitudinal and transverse vibrations of a barrel with arbitrary cross-sectional shapes is considered and solved in the framework of a one-dimensional model. The study shows that the amplitude of transverse vibrations in the vertical plane significantly exceeds that in the horizontal plane. This paper proposes to reduce the amplitude of vibrations by changing the shape of the barrel cross-section, namely by adding stiffeners. The numerical algorithm for solving the problem is developed on the basis of the integro-interpolation method. The verification of the numerical integration method is carried out, and the grid convergence is verified by means of the modeling of barrel vibrations for a 30 mm automatic cannon. The study of the impact of the barrel cross-section shape shows that the use of stiffeners can reduce the initial deflection and the amplitude of muzzle vibrations when firing in bursts. The obtained results demonstrate a narrow spread of projectile departure angles, and, consequently, the improved shooting accuracy of the automatic cannon.

Experimental Validation and Applications of mm-Wave 8 × 8 Antenna-in-Package (AiP) Array Platform

Phased array antennas play an indispensable role in millimeter-wave (mmWave) communications. The Antenna-in-package (AiP) system combines advanced antenna and packaging technology, making it highly valuable for various cellular, radar and automative applications. The benefits it brings in terms of small size, low development costs, low power consumption and fast beam-steering capability further drive the vast deployment of phased array antennas in mmWave systems. In this paper, an 8 × 8 AiP experimental platform is presented and its operating performance is measured and analyzed. Further, two application examples of the AiP are presented, namely, a platform for investigating the phased array calibration performance of different methods, and an AiP-based channel sounder for channel characterization. The performance of the channel sounder is verified by analysing the angle of arrival (AoA), angle of departure (AoD) and propagation delay of the measured dominant propagation components (DPCs).

Training Beam Sequence Design for mmWave Tracking Systems With and Without Environmental Knowledge

In this paper, we consider a millimeter wave multiple-input single-output tracking system, where the time-varying angle of departure (AoD) is assumed to change following a discrete state Markov process. Depending on whether the associated AoD transition function is available or not, we propose two different training beam sequence design approaches. Specifically, in the case when the AoD transition function is available, we leverage the maximum a posteriori criterion to estimate the updated AoD in each beam tracking period. Since it is infeasible to derive an explicit expression for the resultant estimation error rate, we turn to its upper bound, which possesses a closed-form expression and is therefore used as the objective function to optimize the training beam sequence. Considering the complicated objective function and the unit modulus constraints imposed by the analog phase shifters, we resort to a particle swarm algorithm to solve the formulated optimization problem. In the case when the AoD transition function is unavailable, we turn to the maximum likelihood criterion for AoD estimation. To cope with the unknown AoD transition function, we reformulate the beam tracking problem as a partially observable Markov decision process problem and develop an actor-critic reinforcement learning framework to obtain an efficient training beam sequence design. Numerical results demonstrate superiorities of the proposed training beam sequence design approaches for both two cases.

Highly integrated hydrogen sensor based on inverse surface plasmon polaritons

We report a novel hydrogen sensor based on inverse surface plasmon polaritons (ISPPs) which may be used in integrated optical circuit. If a light beam hits a prism with Kretschmann configuration at a proper angle, the surface plasmon polaritons (SPPs) will be excited at the surface of the metal film. And the angle depends on the optical properties of the film. We use a palladium (Pd) film which changes its dielectric function in hydrogen gas. Thus, the incident angle can be used to indicate the concentration of hydrogen. Our sensor inverted all the process: SPPs are excited by a grating integrated on the Pd film, and decoupled by the prism, the angle of departure will indicate the hydrogen concentration. According to our simulation, if the concentration of hydrogen increases by 1%, the angle changes by and the intensity decreases by 1.55%. Our proposal can be used to improve the integration of ISPPs sensors.

Antenna Array Topologies for mmWave Massive MIMO Systems: Spectral Efficiency Analysis

This article investigates the achievable spectral efficiency (SE) of millimeter wave massive multiple-input multiple-output systems with three different array topologies deployed at the base station (BS), namely uniform rectangular array (URA), uniform linear array (ULA) or uniform circular array (UCA). To be practical, both small scale fading and large scale path loss, and shadowing effects are considered in the analysis. A 3D channel model taking both the azimuth and elevation domains into account is adopted for the analysis of the URA and UCA topologies. Considering randomly distributed users in the cell, we firstly deduce the distribution functions of the distances between the users and the BS, and the azimuth and elevation angles of departure, respectively. Based on the derived probability distribution, tight approximations on the achievable SE with maximum ration transmission under the three antenna array topologies are derived. Analytical results show that under all the three topologies, the total achievable SE increases with the number of BS antennas, but decreases with the radius of cell and decay exponent. Moreover, it converges to a saturated value in the high SNR regime and a large inter-element spacing. It is also found that the UCA configuration has a superior achievable SE than the URA and ULA cases, and thus is the best choice for mmWave massive MIMO systems in terms of the achievable SE.

Toward Reliable Indoor Tracking Based on Motion Features and Multipath-Assisted

Recently, indoor target localization and tracking with only one access point (AP) have attracted significant attention in wireless sensor networks (WSNs). Despite much research in this field, a universal and accurate solution is still rare in reality. To this end, we propose a system that achieves reliable decimeter-level indoor tracking with only one AP in this article. We first use the 3-D orthogonal matching pursuit (OMP) to recover the angle of arrival (AoA), angle of departure (AoD), and time of flight (ToF) of the multipath signals. We construct a fusion tracking model based on these channel parameters, which can adapt to different situations. Concretely, when there are available reflection paths, we combine the target motion features and the geometric features of multipath reflections to achieve improved multipath-assisted tracking. In addition, we provide an auxiliary tracking method with only the direct path in the absence of available reflective paths. After that, we use a Bayesian framework to analyze the fusion tracking model and formulate it as a hidden Markov model (HMM). Then, we construct a particle filter to address the HMM instead of the Kalman filter because of the nonlinear model. Finally, we validate the proposed system in various indoor environments on a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4\times $ </tex-math></inline-formula> 4 multiple input multiple output (MIMO) system implemented by software-defined radio (SDR) X310 devices. The experimental results show that the proposed system has good tracking performance and a median trajectory error of 0.44 m, comparable to the prior state-of-the-art systems.

Generative Neural Network Channel Modeling for Millimeter-Wave UAV Communication

The millimeter wave bands are being increasingly considered for wireless communication to unmanned aerial vehicles (UAVs). Critical to this undertaking are statistical channel models that describe the distribution of constituent parameters in scenarios of interest. This paper presents a general modeling methodology based on data-training a generative neural network. The proposed generative model has a two-stage structure that first predicts the link state (line-of-sight, non-line-of-sight, or outage), and subsequently feeds this state into a conditional variational autoencoder (VAE) that generates the path losses, delays, and angles of arrival and departure for all the propagation paths. The methodology is demonstrated for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathrm {28~GHz}$ </tex-math></inline-formula> air-to-ground channels between UAVs and a cellular system in representative urban environments, with training datasets produced through ray tracing. The demonstration extends to both standard base stations (installed at street level and downtilted) as well as dedicated base stations (mounted on rooftops and uptilted). The proposed approach is able to capture complex statistical relations in the data and it significantly outperforms standard 3GPP models, even after refitting the parameters of those models to the data.

Reconfigurable Intelligent Surface Enabled Interference Nulling and Signal Power Maximization in mmWave Bands

Reconfigurable intelligent surface (RIS) has emerged as a promising mean to enhance wireless transmission. The effective reflected paths provided by RIS are able to alleviate the susceptibility to blockage effects, especially in high-frequency band communications, where signals experience severe path loss and high directivity. This paper is concerned with an RIS-assisted system over the millimeter wave (mmWave) channel characterized by sparse propagation paths. A base station tries to connect with the desired user through an RIS, while the undesired user can also receive the signal transmitted from BS unavoidably, which is treated as the interference signal. All terminals are assumed to be equipped with a single antenna for the sake of simplicity. The paper aims to propose an appropriate design of the phase shifts of each element at the RIS so as to maximize the received signal power transmitted from the base station (BS) at the desired user, while nulling the received interference signal power at the undesired user. The proposed reflecting design relies on the decomposition of the reflecting beamforming vectors and all channel path vectors into Kronecker product of factors being uni-modulus vectors. By exploiting characteristics of Kronecker mixed products, different factors of the reflecting are designed for either nulling the interference signal at the undesired user, or coherently combining data paths at the desired user. Furthermore, a channel estimation strategy is proposed to enable the proposed reflecting beamforming design. The magnitude, azimuth, and elevation arrival and departure angles of desired and undesired paths are estimated by an efficient 2-dimension (2-D) line spectrum optimization technique based on the atomic norm minimization (ANM) framework. The performance of the reflecting designs and channel estimation scheme is analyzed and demonstrated by simulation results.

Robust Downlink Precoding for LEO Satellite Systems With Per-Antenna Power Constraints

Downlink precoding has been widely accepted as a crucial technique in low-earth-orbit (LEO) satellite communications due to its advantages in improving the space division multiplexing capability and enhancing spectrum efficiency. Because of the strong spatial directivity in the satellite channels, the downlink precoder can be efficiently designed based on the angle of departure (AoD)-based channel state information (CSI). However, acquiring perfect AoD-based CSI is challenging due to the angle estimation error and attitude jitter of the LEO satellites. In light of this, this paper investigates the precoder design for the LEO satellite downlinks with imperfect AoD-based CSI. For robust design, we treat the angle deviations of each user as random variables, which are supposed to exhibit a particular distribution, then integrate them within a certain range to achieve the robustness of the proposed downlink precoder against the angle mismatch. Instead of using the sum-power constraint on the transmit antennas, we adopt a more realistic per-antenna power constraint (PAPC). Accordingly, we formulate the problem to maximize the ergodic sum rate of the system. By leveraging the corresponding Lagrangian formulation and identifying the optimal precoder structure as the solution to a generalized eigenvalue problem, an iterative algorithm for the robust precoder design is derived. To reduce the computational complexity, a low-complexity version of the proposed algorithm is implemented based on deep learning techniques to meet the high demand for real-time applications in LEO satellite systems. Simulation results verify the effectiveness of the proposed precoding approach.