Angle Of Arrival Research Articles

A Non-Kronecker Structured PFS Method for Channel Emulation in Multiprobe OTA Setups

The realistic channel environment can be characterized by a geometry-based stochastic channel (GBSC) model composed of multiple clusters, each of which consists of many rays. For the GBSC model, the power angle of arrival (AoA) spectrum of a cluster depends on the power angle of departure-Doppler (AoD-Doppler) spectrum. Hence, this model is non-Kronecker structured. In over-the-air (OTA) testing, the prefaded signal synthesis (PFS) method is valid for emulating the GBSC to measure devices under test (DUTs). However, the emulated channel under the conventional PFS method is a Kronecker case due to the independently and identically distributed fading sequences between probes when synthesizing clusters. It will lead to inaccurate link characteristics for emulation. Therefore, a non-Kronecker structured PFS (NKSPFS) method is proposed. Specifically, the rays mapped to probes are individually weighted to ensure that fading sequences between probes are independent but not identically distributed. To determine the ray weights without degrading marginal correlations for emulation, the constraints are introduced on the deviation between the target spatial-temporal correlation and the emulated spatial-temporal correlation according to the emulated spatial correlation and temporal correlation. Simulation results show that the proposed NKSPFS method outperforms the conventional PFS method in OTA testing of multi-antenna devices.

Single-Target Real-Time Passive WiFi Tracking

Device-free human tracking is an essential ingredient for ubiquitous wireless sensing. Recent passive WiFi tracking systems face the challenges of inaccurate separation of dynamic human components and time-consuming estimation of multi-dimensional signal parameters. In this work, we present a scheme named WiFi Doppler Frequency Shift (WiDFS), which can achieve single-target real-time passive tracking using channel state information (CSI) collected from commercial-off-the-shelf (COTS) WiFi devices. We consider the typical system setup including a transmitter with a single antenna and a receiver with three antennas; while our scheme can be readily extended to another setup. To remove the impact of transceiver asynchronization, we first apply CSI cross-correlation between each RX antenna pair. We then combine them to estimate a Doppler frequency shift (DFS) in a short-time window. After that, we leverage the DFS estimate to separate dynamic human components from CSI self-correlation terms of each antenna, thereby separately calculating angle-of-arrival (AoA) and human reflection distance for tracking. In addition, a hardware calibration algorithm is presented to refine the spacing between RX antennas and eliminate the hardware-related phase differences between them. A prototype demonstrates that WiDFS can achieve real-time tracking with a median position error of 72.32 cm in multipath-rich environments.

AoA-Based Low Complexity Beamforming for Aerial RIS Assisted Communications at mmWaves

Reconfigurable intelligent surface (RIS) mounted on mobile devices (aerial RIS), such as unmanned aerial vehicles, is envisioned to increase coverage for future millimeter wave (mmWave) communications. In literature, RIS beamformer is designed using channel state information (CSI) or by scanning through gNodeB and user codebooks over different training RIS weight matrices. Both of these methods incur significant training overhead. Also, the traditional subspace-based AoA estimators require several power-intensive radio frequency (RF) chains, which is not practically affordable to users. As a low-power and low-complexity alternative, we propose to design RIS beamforming weights based on angle-of-arrival (AoA) from gNodeB-to-RIS and from RIS-to-user with a single RF chain coupled to an antenna array. The proposed estimator is a combination of maximum likelihood and maximum correlation estimator and uses a single RIS training matrix. The simulation results show that, though a slightly larger number of antenna elements is required for the same spectral efficiency, the proposed approach offers a significantly energy- and computationally-efficient beamforming alternative compared to the existing subspace-based AoA estimator and CSI based techniques.

A Convergent Iteration Method for 3-D AOA Localization

Using angle-of-arrival (AOA) measurements from several sensors to locate a target in 3-D space is one of the commonly used wireless localization techniques. A challenge of this technique is that the weighted least-squares (WLS) needed for it tend to incur the threshold effect when the noise level is high or when the localization geometry is poor, because its implementation requires the inversion of a matrix whose condition number will be large under such conditions. This paper presents an iterative method that does not require any matrix operation and is proved to be convergent with any initial value. Additionally, it outperforms the WLS-based methods as validated by comprehensive simulation results.

Beam Alignment for Analog Arrays Based on Gaussian Approximation

Beam alignment is a process for receive and transmit antenna arrays to find the correct beamforming directions. It is typically based on beam scanning and peak-energy searching, which lead to time-consuming beam training process in communication protocols, such as 802.11ad for vehicular networks. In this correspondence, we propose a fast beam alignment method for analog arrays, based on directly estimating the angle-of-arrival (AoA) of the incoming signals. We propose simple and highly efficient AoA estimators, by approximating the power of the array response as a Gaussian function. One estimator is based on the power ratio and can coherently combine multiple measurements scanned at arbitrary intervals and with different beam widths. The other two are based on an innovative idea of Gaussian curve fitting with weighted least square techniques, and one of them can even work without knowing the beam width. Simulation results validate the effectiveness of the proposed scheme.

Utilizing Attitude Information for Efficient Multi-User Millimeter-Wave Communications

Sensing has played an important role in the 5G wireless network. It is well recognized that the energy efficiency of mobile devices can be further improved with the assistance of sensing. As an important sensing resource, attitude information is highly related to the angle of arrivals (AoAs) information when user equipments (UEs) rotate. It provides great potential to improve transceiver designs for multi-user millimeter-wave (mmWave) green communications. In this paper, we propose an attitude information aided block diagonalization receiver design algorithm. We first adopt angle of departure aided block diagonalization (AoD-BD) to eliminate inter-user interference (IUI). Then we compensate the rotation for each UE by only updating the receiver with attitude information from motion sensors. Compared to the joint transceiver design performance, we have theoretically proved that the sum spectral efficiency performance penalty of keeping transmitter unchanged is generally negligible. Furthermore, we consider the effect of imperfect attitude information, and derive a robust receiver by modeling the measurement error as Gaussian. Finally, the simulation results are presented to verify the effectiveness of the proposed design. It is noted that no feedback is required between the base station (BS) and UE during the rotation, which substantially reduces the system overhead.

Statistical channel model for 6G communication networks in Banda Aceh City

Wireless technology is expected to undergo considerable transformation because of the numerous services offered by 6G communication networks, which virtually entirely encompass every part of everyday life and use a variety of devices. Channel modeling is an essential factor in designing 6G communication networks. To meet the channel requirements of future 6G communication networks, it is crucial to measure the channel to consider path loss, multi-band, fading, blocking effect, multipath clustering, transmitter, and receiver moving speed/direction/time. The goal of this paper is to design and evaluate a 6G communication network in Banda Aceh City using a statistical channel model. The channel model is associated with environmental conditions such as rainfall and humidity. The method is then based on computer simulation using the NYUSIM simulator to complete the channel modeling using an operating frequency of 95 GHz with a bandwidth of 800 MHz. In the simulator, the designed 6G channel model is evaluated in both line-of-sight (LOS) and non-line-of-sight (NLOS) network environments. In addition, the designated network parameters, such as the coverage area, angle of arrival (AoA), angle of departure (AoD), and power delay profile (PDP), are simulated. The results, at AoA, the value of received power for LOS conditions ranges from -86 dBm to -101 dBm, while the value for NLOS conditions ranges from -91 dBm to -111 dBm. Under LOS conditions, the received power for AoD ranges from -86 dBm to -101 dBm, whereas under NLOS conditions, it ranges from -91 dBm to -111 dBm. In the omnidirectional PDP, the pathloss value for the LOS condition is 99.8 dB and the delay is 17.9 ns, while the pathloss value for the NLOS condition is 104.2 dB with a delay of 28.1 ns. For the directional PDP, the LOS condition yields a path loss of 106.4 dB and a delay of 2.9 ns, while the NLOS condition yields a path loss of 110.5 dB and a delay of 3 ns. Conclusions. The simulation indicated that the AoA, AoD, and PDP in terms of received power, pathloss, and propagation delay are in acceptable conditions for a 6G network in Banda Aceh City in the two observed environments. Therefore, it is conceivable to establish a 6G network in Banda Aceh City in the future.

Microwave Photonic Direction-Finding Spectrometer

In this paper, we propose an architecture wherein the radio-frequency (RF) field at the antenna array is up-converted to an optical carrier and passed through an array of optical fibers, after which an analog Fourier transform is taken in a free-space optical processor. Through the use of multiple temporal dispersion projections, implemented through varied-length optical fiber segments, the locations of RF sources in three-dimensional space spanning angle-of-arrival (AoA) and instantaneous frequency may be determined on a millisecond time scale using commercial computing hardware after detection by a charge-coupled device (CCD) camera. We present a mathematical formulation of the problem, followed by simulated and experimental results showing three-dimensional spatial-spectral localization through the solution to a system of equations brought forth through the use of Fourier optics to process the RF field.

Low-Complexity Three-Dimensional AOA-Cross Geometric Center Localization Methods via Multi-UAV Network

The angle of arrival (AOA) is widely used to locate a wireless signal emitter in unmanned aerial vehicle (UAV) localization. Compared with received signal strength (RSS) and time of arrival (TOA), AOA has higher accuracy and is not sensitive to the time synchronization of the distributed sensors. However, there are few works focusing on three-dimensional (3-D) scenarios. Furthermore, although the maximum likelihood estimator (MLE) has a relatively high performance, its computational complexity is ultra-high. Therefore, it is hard to employ it in practical applications. This paper proposed two center of inscribed sphere-based methods for 3-D AOA positioning via multiple UAVs. The first method could estimate the source position and angle measurement noise at the same time by seeking the center of an inscribed sphere, called the CIS. Firstly, every sensor measures two angles, the azimuth angle and the elevation angle. Based on that, two planes are constructed. Then, the estimated values of the source position and the angle noise are achieved by seeking the center and radius of the corresponding inscribed sphere. Deleting the estimation of the radius, the second algorithm, called MSD-LS, is born. It is not able to estimate angle noise but has lower computational complexity. Theoretical analysis and simulation results show that proposed methods could approach the Cramér–Rao lower bound (CRLB) and have lower complexity than the MLE.

Cross Dipole Antennas Solution for Angle of Arrival Estimation

The Multiple Signal Classification (MUSIC) algorithm is the most popular algorithm to estimate the Angle of Arrival (AOA) of the received signals. The analysis of this algorithm (MUSIC) with typical array antenna element ( ) shows that there are two false direction indication in the planaligned with the axis of the array. In this paper a suggested modification on array system is proposed by using two perpendiculars crossed dipole array antenna in spite of one array antenna. The suggested modification does not affect the AOA estimation algorithm. The simulation and results shows that the proposed solution overcomes the MUSIC problem without any effect on the performance of the system.

Algorithm for Topology Search Using Dilution of Precision Criterion in Ultra-Dense Network Positioning Service Area

User equipment (UE) location estimation in emerging 5G/B5G/6G Ultra-Dense Networks (UDNs) is a breakthrough technology in future wireless info-communication ecosystems. Apart from communication aspects, network infrastructure densification promises significant improvement in UE positioning accuracy. Unlike networks of previous generations, an increased number of gNodeBs (gNBs) per unit area and/or volume in UDNs allows to perform measurements for UE positioning only with those base stations whose topologies are most suitable from the geometric point of view. Quantitative measurements of gNB topology suitability include horizontal (HDOP), vertical (VDOP), and position (PDOP) dilution of the precision (DOP) criteria on the plane, in height, and in space, respectively. In the current work, we formalize a set of methods for gNB topology search using time of arrival (TOA), time difference of arrival (TDOA), angle of arrival (AOA), and combined TOA–AOA and TDOA-AOA measurements. The background of the topology search using DOP criteria is a significantly increased number of gNBs per unit volume in UDNs. Based on a simulation, we propose a novel approach for a topology search in a positioning service area, resulting in a PDOP less than one for the Gazprom Arena with only five gNBs. The contribution of the current research includes algorithm and software for an iterative search of all possible gNB and UE locations in space, minimizing UE geometric DOP. The practical application of the algorithm is the gNB topology substantiation for the given positioning scenarios in 5G/B5G/6G UDNs.

A Localization and Tracking System Using Single WiFi Link

Like its outdoor counterpart (e.g., GPS), an indoor tracking system can bring about disruptive changes in how we live and work. This paper proposes a location and tracking system using a single WiFi link based on channel state information. The system can realize real-time, decimeter-level localization and tracking. In this system, phase calibration and static path elimination are realized by multiplying the conjugate signals of different antennas. Then, a three-dimensional MUSIC algorithm is employed to estimate the angle of arrival (AOA), the time of flight (TOF), and the velocity of a target. A scheme is then developed to adjust the MUSIC search range and reduce the computation time from about ten hours to tens of seconds. The Widar2.0 data set from Tsinghua University are used for the experiments; the proposed system is found to have an average tracking error of 0.68 m in the three environments of classroom, office, and corridor, which is better than the existing single link localization and tracking system.

Outage probability analysis of maritime FSO links

In this paper, the outage performance of the maritime free-space optical (FSO) communication system is analyzed, and a new maritime FSO link configuration is presented. The channel model for maritime FSO link includes the combined effect of turbulence, pointing error, angle-of-arrival (AOA) fluctuations, and attenuation. While the maritime turbulence channel is modeled by lognormal distribution, pointing error and AOA fluctuations are assumed to be Beckmann and Rayleigh distributed, respectively. The turbulence power spectrum is considered to present the Kolmogorov characteristics, and the Rytov variance of a propagating Gaussian beam in maritime environment is obtained. The probability density function (PDF), cumulative distribution function (CDF), and outage probability of the maritime communication channel are obtained analytically. The outage performance of a maritime communication link is given depending on various parameters of the maritime environment, the Gaussian beam, and the (FSO) communication system.

Research on the broadband source localization of a vector hydrophone vertical line array in the deep sea

This paper develops an approach that estimates the range and depth of a broadband source by adopting the vector hydrophone vertical array (VHVA) in the deep ocean. The sound field in the direct wave zone is mainly composed of direct (D) and once-sea-surface-reflected (S1B0) waves. The arrival angles and time delays of the two waves are consistent. The combined beamforming technology is applied to the VHVA to accurately obtain the elevation angles and further enhance the received signal-to-noise ratio (SNR). The source ranges are then estimated according to the simple geometric relationship. The source depth estimation model is established based on the Lloyd-mirror principle, which relates the interference properties of D and S1B0 to the oscillation period of the combined signals of VHVA. The feasibility and availability of this method are validated by both simulations and sea trials in the South China Sea. The experimental results indicate the range estimation error of the moving vessel is less than 10% and the surface or submerged targets can be effectively determined. Our proposed algorithm has the strong benefits of simple principle, low computational complexity and small error. These properties indicate this algorithm can be used in target detection in the deep sea.

Climatology of HF Propagation Characteristics at Very High Latitudes From SuperDARN Observations

AbstractConventional forecasting of high‐frequency (HF, 3–30 MHz) radio wave propagation is based on a combination of ionospheric and propagation models. However, at very high latitudes this approach is seriously undermined by the intrinsically dynamic ionospheric conditions regularly perturbed by energetic particle precipitations and strong electric fields. From this perspective, the multi‐year observations of HF propagation characteristics by Super Dual Auroral Radar Network (SuperDARN) radars across auroral and polar cap regions represent a unique opportunity for systematic validation of the conventional approach, as well as for creating an empirical propagation model directly from the radar observations. Qualitative identification and quantitative characterization of the propagation modes requires an accurate knowledge of the vertical angle of arrival (elevation angle) across the high‐latitude part of the radar network. This information has become available only in recent years, facilitated by the development of reliable data‐based calibration techniques for SuperDARN interferometry. We present the solar‐cycle/seasonal/diurnal climatology of HF propagation characteristics at very high latitudes derived from two‐frequency observations by the Rankin Inlet SuperDARN radar.

Simultaneous measurements of Ka-band microwave angle of arrival and Doppler frequency shift based on a silicon DPMZM.

We propose a system for the simultaneous measurements of Ka-band microwave angle of arrival (AOA) and Doppler frequency shift (DFS) based on a high-speed silicon dual-parallel Mach-Zehnder modulator (Si-DPMZM).. An echo signal drives a sub-MZM while the combination of a phase-delay echo signal and a transmitted signal drives the other sub-MZM. Two optical bandpass filters (OBPFs) are used to select the upper and lower sidebands of the Si-DPMZM output signal, detected by low-speed photodiodes, then generating two intermediate frequency (IF) signals. Thus, both AOA and DFS (with direction) can be obtained by comparing the powers, phases and frequencies of these IF signals. The estimation error of measured AOA is less than ±3° from 0 to ±90°. Meanwhile, the DFS at 30/40 GHz were measured with an estimated error of less than 9.8 × 10-10 Hz within ±1 MHz. In addition, the fluctuation of DFS measurement is less than 3 × 10-11 Hz within 120 minutes, indicating the high stability of the system.

Target Positioning and Tracking in WSNs Based on AFSA

In wireless sensor networks (WSNs), the target positioning and tracking are very important topics. There are many different methods used in target positioning and tracking, for example, angle of arrival (AOA), time of arrival (TOA), time difference of arrival (TDOA), and received signal strength (RSS). This paper uses an artificial fish swarm algorithm (AFSA) and the received signal strength indicator (RSSI) channel model for indoor target positioning and tracking. The performance of eight different method combinations of fixed or adaptive steps, the region segmentation method (RSM), Hybrid Adaptive Vision of Prey (HAVP) method, and a Dynamic AF Selection (DAFS) method proposed in this paper for target positioning and tracking is investigated when the number of artificial fish is 100, 72, 52, 24, and 12. The simulation results show that using the proposed HAVP total average positioning error is reduced by 96.1%, and the positioning time is shortened by 26.4% for the target position. Adopting HAVP, RSM, and DAFS in target tracking, the positioning time can be greatly shortened by 42.47% without degrading the tracking success rate.

Supervised Learning Technique for First Order Multipaths Identification of V2V Scenario

In geometrical localization techniques, the propagated signal’s first-order multipath (FOMP) characteristics are used to calculate the location based on geometrical relationships. Utilizing the characteristics of higher order multipath (HOMP) results in a significant localization error. Therefore, distinguishing between FOMPs and HOMPs is an important task. The previous works used traditional methods based on a deterministic threshold to accomplish this task. Unfortunately, these methods are complicated and insufficiently accurate. This paper proposes an efficient method based on supervised learning to distinguish more accurately between the propagated FOMP and HOMP of millimeter-Wave Vehicle-to-Vehicle communication in an urban scenario. Ray tracing technique based on Shoot and Bounce Ray (SBR) is used to generate the dataset’s features including received power, propagation time, the azimuth angle of arrival (AAOA), and elevation angle of arrival (EAOA). A statistical analysis based on the probability distribution function (PDF) is presented first to study the selected features’ impact on the classification process. Then, six supervised classifiers, namely Decision Tree, Naive Bayes, Support Vector Machine, K-Nearest Neighbors, Random Forest, and artificial neural network, are trained and tested, and their performance is compared in terms of HOMP misclassification. The effect of the considered features on the classifiers’ performance is further investigated. Our results showed that all the proposed classifiers provided an acceptable classification performance. The proposed ANN showed the best performance, whereas the NB was the worst. In fact, the HOMP misclassification error varied between 2.3% and 16.7%. The EAOA exhibited the most significant influence on classification performance, while the AAOA was the least.

Semi-blind receivers based on a coupled nested Tucker-PARAFAC model for dual-polarized MIMO systems using combined TST and MSMKron codings

Over the past two decades, tensor-based approaches have generated ever-increasing interest for designing multiple-input multiple-output (MIMO) communication systems. In this paper, we propose a new double directional dual-polarized (DD-DP) MIMO system, equipped with uniform rectangular arrays (URAs) at both ends of the link, which combines a multiple Kronecker product of symbol matrices with a tensor space-time (TST) coding, called TST-MSMKron coding. It is first shown that the channel tensor is represented by a fifth-order PARAFAC decomposition, separated into two parts associated with vertically and horizontally polarized receive antennas, respectively. Then, it is established that the tensor of received signals satisfies a new coupled nested Tucker-PARAFAC model whose core tensor is the coding tensor. Capitalizing on this tensor modeling and assuming the tensor coding is known at the reception, two semi-blind receivers composed of two stages are derived for estimating the transmitted symbols and channel parameters (directions of departure (DoD) and arrival (DoA) angles, path loss coefficients). A new rectification method is proposed to ensure the Vandermonde structure of the estimated steering matrices. Parameter identifiability and computational complexity are analyzed for each receiver. Monte Carlo simulation results are provided to illustrate the effectiveness of the proposed TST-MSMKron coding and semi-blind receivers, in terms of symbol error rate (SER) and channel parameters estimation.

Intelligent Proof-of-Trustworthiness-Based Secure Safety Message Dissemination Scheme for Vehicular Ad Hoc Networks Using Blockchain and Deep Learning Techniques

Vehicular ad hoc networks have emerged as the main building block for the future cooperative intelligent transportation system (cITS) to improve road safety and traffic efficiency and to provide passenger comfort. However, vehicular networks are decentralized, characterized by high mobility and dynamicity, and vehicles move in a hostile environment; such characteristics make VANET applications suffer many security and communication issues. Recently, blockchain has been suggested to solve several VANET issues including the dissemination of trustworthy life-threatening information. However, existing dissemination schemes are inefficient for safety messages and are vulnerable to malicious nodes and rely on the majority of honest assumptions. In the VANET context, adversaries may collude to broadcast false information causing serious safety threats. This study proposes an intelligent proof-of-trustworthiness-based secure safety message dissemination scheme (PoTMDS) to efficiently share only trustworthy messages. The consistency and plausibility of the message were evaluated based on a predictive model developed using a convolutional neural network and signal properties such as the received signal strength and angle of arrival. A blockchain-based data dissemination scheme was developed to share critical messages. Each vehicle calculates the proof of trustworthiness of the disseminated messages by comparing the received message with the output of the prediction model. The results showed that the proposed scheme reduced the consensus delay by 58% and improved the detection accuracy by 7.8%. Therefore, the proposed scheme can have an important role in improving the applications of future cITS.