High-resolution Channel Research Articles

Channel estimation for Massive MIMO systems aided by intelligent reflecting surface using semi-super resolution GAN

Intelligent Reflecting Surfaces (IRSs) coupled with Massive Multiple-Input-Multiple-Output (MIMO) millimeter wave (mmWave) systems hold immense promise for the next generation of wireless communications. However, harnessing their full potential requires accurate channel state information (CSI). Despite the benefits of IRSs, such as passive element integration and energy efficiency, precise channel estimation becomes a formidable challenge due to the absence of active elements. In this paper, we tackle these challenges by employing generative adversarial networks (GANs) to estimate the channel’s cascade matrix between the base station (BS) and mobile users. To leverage the high correlation among adjacent elements in the IRS, we propose turning off a majority of these elements during the estimation phase, effectively creating a low-resolution channel. We then introduce the semi-super resolution GAN (SSRGAN) model, capable of inferring channel values for the deactivated elements based on existing correlations. Our new SSRGAN-based channel estimation method transforms low-resolution channel data into high-resolution channel data. Through a comprehensive comparative analysis, our study showcases the superior performance of our SSRGAN channel estimation method compared to established benchmark schemes.

The New Small Wheel Trigger for the ATLAS experiment

The ATLAS New Small Wheel (NSW) Muon spectrometer upgrade, completed in 2022, was the largest Phase I detector upgrade among LHC experiments. The NSW enhances triggering in the endcap region (1.3<|η|<2.4) by confirming muons from the Interaction Point (IP) and rejecting fake contributions. It also improves muon tracking with 2.5 million high-resolution channels across 16 layers. The NSW Trigger, based on small-strip Thin Gap Chambers (sTGC) and Micromegas (MM) technologies, provides Level-1 triggers at every Bunch Crossing (BC) with a fixed low latency (44 BC). Integrated into ATLAS in 2023, the NSW Trigger significantly reduces fake rates and overall readout deadtime. The custom electronics of the NSW Trigger system efficiently collect, process, and trigger on IP muons, focusing on the fully operational sTGC pad-only path based on the Pad Trigger (PT) and Trigger Processor (TP) FPGA based boards. Performance studies using 13.6TeV pp collisions are presented, demonstrating NSW’s readiness for the High Luminocity LHC (HL-LHC) era and outlining Phase II upgrade perspectives.

Implications of digital elevation models on habitat analysis of Golden Mahseer in the Upper Ganga Basin, India

Aquatic habitat analysis is crucial in determining the relationship between river flow and habitat availability for aquatic species. This helps in identifying the environmental flow requirements of rivers. However, conducting habitat analysis in Indian rivers is challenging because of the unavailability of reliable and high-resolution terrain data. To address this challenge, a study was conducted to explore the possibilities of using Digital Elevation Models (DEMs) to extract required hydraulic data and to evaluate their accuracies. The extracted data were coupled with ecological data of a keystone fish species, namely Golden Mahseer (Tor putitora), to develop habitat analysis models for the Upper Ganga Basin (UGB) in India. The study adopted a hierarchical three-step approach for evaluating the accuracy and performance of DEMs as surrogate data sources. Firstly, cross sections at selected sites in the UGB were extracted from three different DEMs (SRTM, ASTER, and CARTOSAT) and evaluated against surveyed cross-section data with turning point tests and correlation coefficients. These data were then used to establish hydraulic and habitat analysis models. Four parameters (top width, flow cross-sectional area, hydraulic mean depth, and wetted perimeter) were evaluated using five error estimators to determine the accuracy and performance of hydraulic modelling. Finally, the hydraulic parameters were coupled with ecological requirements to develop a habitat model for different life stages of Golden Mahseer, namely fingerling, juvenile, and adult stages.We found that the SRTM predictions were better than those of the other DEMs, indicating its suitability to replicate channel geometry with higher accuracy, thus better predicting hydraulic parameters at all flow ranges. In habitat area estimation for adult Golden Mahseer, all the DEMs performed reasonably well (within ±20%) within the flow range of 100 ​m3/s, which covers the low to average flow season. Beyond this flow range, ASTER and CARTOSAT resulted in considerable underestimations, averaging 22% and 54%, respectively. It is important to note that DEM-based cross sections lack high-resolution channel information, resulting in unstable habitat predictions for younger life stages like fingerling. However, overall, the study established that DEM-based data can be relied upon for habitat modelling-based assessment of environmental flows with some precautions for sensitive cases. Remote sensing presents a promising avenue for habitat analysis studies of Indian species, offering the potential to unlock significant progress in environmental flows (E-Flows) assessments and thus providing ecological benefits.

Urbanization enhances channel and surface runoff: A quantitative analysis using both physical and empirical models over the Yangtze River basin

Urbanization has become an irreversible trend and is even more rapid in flood-prone area. However, the responses of both channel runoff and surface runoff to the urbanization and the underlying mechanisms still deserve more in-depth exploration within urban extents with limited data availability. Accordingly, we conducted a comprehensive quantitative analysis of the urbanization effects on channel and surface runoff from both statistical and model-based perspectives over three major urban agglomerations (i.e., Chengyu (CY), middle region of Yangtze River (MRYR), Yangtze River Delta (YRD)) in the Yangtze River Basin. The long-term high-resolution channel and surface runoff under different urbanization scenarios were simulated using both WRF-Hydro and SCS-CN models by integrating multiple remotely sensed, reanalysis, and in-situ datasets. Results demonstrated that the channel runoff increased by 4.4%, 5%, and 12.08% in CY, MRYR, and YRD urban agglomerations, respectively. Meanwhile, the urbanization also contributed to 30%, 21.4%, and 17.7% of the surface runoff changes in three urban agglomerations. Based on the high-resolution local climate zone (LCZ), our results highlighted that the high-rise and middle-rise buildings and compact-arranged regions were more prone to accumulating surface runoff and trigger flooding events due to the weaker infiltration capacity of land surface with the densely distribution of impervious surface. Further machine learning based investigation and case analysis also explored the potential influencing factors and mechanisms of the impact of urbanization on channel and surface runoff. Results in the current research show further evidence that policy makers of urban planning and management need to consider and ensure societal preparedness for extreme runoff and flooding events.

The impact of post-cutoff bend curvature on channel kinematics in meandering rivers: an example from the Trinity River, Texas, USA

Abstract Neck and chute cutoffs along meandering rivers are near-instantaneous morphodynamic perturbations that drive modification of planform channel geometry and kinematics at the cutoff site and in adjacent bends. Despite their ubiquity, quantitative and predictive linkages between post-cutoff planform bend geometry and subsequent bend kinematics remain limited. Here, using a 37-year record of Landsat-derived river channel centrelines from a meandering reach of the Trinity River in Texas (USA) and a newly developed directed graph-based approach for high-resolution channel tracking, we identify a linkage between post-cutoff bend curvature and the magnitude, spatial extent, and temporal duration of cutoff influence on local and non-local channel bend kinematics. We further explore this relationship using a kinematic model of meandering applied to synthetically generated river reaches and the Landsat-derived Trinity River centrelines. While the model captures the observed linkages between post-cutoff bend curvature and resultant bend kinematics, it underpredicts the magnitude of cutoff influence observed in the real centreline data – particularly at the cutoff site – by up to one order of magnitude. Our results provide a promising advance in the characterization and prediction of the spatiotemporal impact of cutoffs on local and non-local post-cutoff channel bend kinematics.

Channel state information-based wireless localization by signal reconstruction

Wireless localization technology has been widely used in indoor and outdoor fields. Channel estimation based on channel state information is a hot research topic in recent years. However, due to the interference of acquisition bandwidth, noise and Doppler effect, high-resolution channel estimation is a difficult problem. In this paper, the least squares estimate the amplitude of the signal subspace projection and estimate the time delay, using wireless channel state information to delay obey exponential distribution and magnitude obey normal distribution features, and reconstruction after the signal space and sampling to the Euclidean distance between the signal space, common as gradient optimization parameters, estimate the arrival time delay of high precision. The algorithm proposed in this paper filters out the noise interference in wireless communication and improves the accuracy of channel estimation through the method of least square and gradient optimization, which provides a feasible scheme for indoor wireless localization.

Spektr–UF Mission Spectrograph Space Qualified CCD Detector Subsystem

Spektr–UF (World Space Observatory Ultraviolet, WSO-UV) is a Russian-led international collaboration aiming to develop a large space-borne 1.7 m Ritchey–Chretién telescope with science instruments to study the Universe in ultraviolet wavelengths. The WSO-UV spectrograph (WUVS) consists of three channels: two high-resolution channels (R = 50,000) with spectral ranges of 115–176 nm and 174–310 nm, and a low-resolution (R = 1000) channel with a spectral range of 115–305 nm. Each of the three channels has an almost identical custom detector consisting of a CCD inside a vacuum enclosure, and drive electronics. The main challenges of the WUVS detectors are to achieve high quantum efficiency in the FUV-NUV range, to provide low readout noise (3 e− at 50 kHz) and low dark current (&lt;12 e−/pixel/hour), to operate with integral exposures of up to 10 h and to provide good photometric accuracy. A custom vacuum enclosure and three variants of a custom CCD272-64 sensor with different UV AR coatings optimised for each WUVS channel were designed. The enclosure prevents contamination and maintains the CCD at the operating temperature of −100 ∘C, while the temperature of the WUVS optical bench is +20 ∘C. A camera electronics box (CEB) that houses the CCD drive electronics was developed. Digital correlated double sampling technology allows for extremely low readout noise and flexible frequency for normal and binned pixel readout modes. This paper presents the WUVS detector design drivers, methods for extending the service life of the CCD sensors working with low signals in a space radiation environment and the key calculated parameters and results of the engineering qualification model qualification campaign.

Deep learning-driven super-resolution reconstruction of two-dimensional explosion pressure fields

Precise and rapid calculation of explosive loads on structures in specific explosion scenarios is crucial for blast-resistant design, emergency response and safety assessments of structures after disasters. However, available methods such as empirical models and numerical simulations are inadequate in meeting the fast computation demands for diverse explosion scenarios due to limitations in accuracy or computational cost. In order to obtain high-precision explosion pressure fields and overpressure time histories with low computational cost, this study presents a deep learning-based framework for reconstructing two-dimensional explosion pressure fields, which transforms low-resolution numerical simulation results into super-resolution outputs equivalent to high-resolution numerical simulation results. A super-resolution strategy, which concatenates high-resolution channels that record flow field information with the low-resolution channel, is proposed to improve the network performance. Based on the constructed dataset, a comparative study of three different networks is presented to assess their super-resolution applicability. Finally, the performance and generalization ability of the trained model is evaluated with super-resolution evaluation metrics, statistical evaluation metrics, and relative error distribution. The findings indicate that the super-resolution strategy can effectively improve the prediction accuracy of the network. The super-resolution model can not only provide high-credibility super-resolution pressure fields and pressure time histories, but also exhibits excellent generalization capabilities for explosive scenarios beyond the training dataset, therefore providing a new approach for realizing high-precision calculation of explosive flow fields and loads under diverse blast scenarios.

Spitzer IRS Observations of Titan as a Precursor to JWST MIRI Observations

In this work, we present for the first time infrared spectra of Titan from the Spitzer Space Telescope (2004–2009). The data are from both the short wavelength–low resolution (SL; 5.13–14.29 μm, R ∼ 60–127) and short wavelength–high resolution (SH; 9.89–19.51 μm, R ∼ 600) channels showing the emissions of CH4, C2H2, C2H4, C2H6, C3H4, C3H6, C3H8, C4H2, HCN, HC3N, and CO2. We compare the results obtained for Titan from Spitzer to those of the Cassini Composite Infrared Spectrometer (CIRS) for the same time period, focusing on the 16.35–19.35 μm wavelength range observed by the SH channel but impacted by higher noise levels in the CIRS observations. We use the SH data to provide estimated haze extinction cross sections for the 16.67–17.54 μm range that are missing in previous studies. We conclude by identifying spectral features in the 16.35–19.35 μm wavelength range that could be analyzed further through upcoming James Webb Space Telescope Cycle 1 observations with the Mid-Infrared Instrument (5.0–28.3 μm, R ∼ 1500–3500). We also highlight gaps in the current spectroscopic knowledge of molecular bands, including candidate trace species such as C60 and detected trace species such as C3H6, that could be addressed by theoretical and laboratory study.

Detection of Antarctic Surface Meltwater Using Sentinel-2 Remote Sensing Images via U-Net With Attention Blocks: A Case Study Over the Amery Ice Shelf

Surface meltwater critically impacts the Antarctic mass balance and global sea level rise. Quantifying the extent of surface meltwater in Antarctica on a large scale is a challenging task. Traditional methods, such as thresholding, have many limitations. We used a deep learning method, the U-Net with attention blocks, to automatically extract surface meltwater from Sentinel-2 images. We inserted attention mechanism blocks into U-Net to assign different weights to all pixels and channels to utilize the high resolution and multiple channels of Sentinel-2 images. The model was used to map surface water bodies in Sentinel-2 images, and the average accuracy reached 0.9969 on the test dataset. In East Antarctica, the Amery Ice Shelf (AIS) exhibits the largest surface meltwater area. Studying surface meltwater dynamics on the AIS is useful for understanding the East Antarctic mass balance and demonstrating the model performance. We analyzed the classification results for surface water bodies on the AIS from January 2017-2022. Spatially, 96% of surface water bodies are concentrated inland of the AIS from 70-73°S and account for 93% of the region 20 km from the coastline of the AIS. Temporally, the water body area varies considerably in different years, with a maximum in 2017 (932.54 km <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) and a minimum in 2021 (58.34 km <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ). The spatial distribution of surface water body on the AIS is controlled by the firn air content, katabatic winds, bare rocks and blue ice. The interannual variability is associated with complex climate factors, including temperature, surface net solar radiation, snowfall, and snowmelt, among which temperature and snowfall show strong correlation.

Ultra-wideband wireless channel and environment characterization assisted by dual optical frequency comb

In this work, a photonic technique based on dual optical frequency comb is proposed to perform ultra-wideband channel sounding that delivers high-resolution channel characterization and high-speed environment monitoring. The proof-of-concept experiments demonstrate the continuous sounding of non-line-of-sight wireless channels with > TS/s sampling resolution and the revealing of an electric fan rotating at up to 1100 rpm. A wireless channel of 12 GHz bandwidth is covered using electronics with less than 60 MHz bandwidth, showcasing the high practicality of the proposed technique in assisting the evolution towards the integration of communication and sensing essential in the next generation of wireless communication.

Disproportional erosion of the middle-lower Yangtze River following the operation of the Three Gorges Dam

The operation of the Three Gorges Dam (TGD) modifies downstream flow and sediment regimes, triggering disproportional fluvial responses at different distances downstream. However, our understanding of the downstream geomorphic changes in the middle-lower Yangtze River remains incomplete due to the complexity of the river responses across temporal and spatial scales. Here, we leverage data on discharge, suspended sediment concentration (SSC), riverbed grain size, cross-sectional profiles and high-resolution channel bathymetric maps at different locations downstream of the TGD to investigate geomorphic responses. The results show that the magnitude of fluvial erosion decreases downstream, with the Yichang-Luoshan Reach (the first ~500 km downstream) experiencing the most severe erosion in 2003–2020 (~9.05 × 104 t/km/yr). Local changes in riverbed morphology include channel bar erosion, channel incision (~0.43 m/yr in CS1 near the dam site over 2002–2019), riverbank retreat and bed material coarsening (an increase in D50 from 0.175 to 43.1 mm at Yichang station from 2002 to 2017). Such marked erosion is caused by the sharply reduced SSC in the dominant discharge range (10,000–30,000 m3/s) and the extended duration of this dominant discharge range. The sediment erosive magnitude in the Luoshan-Datong Reach is relatively small (3.85 × 104 t/km/yr) in 2002–2020. The Luoshan-Hukou Reach (~500–1000 km downstream) exhibits moderate channel incision, minor bed material coarsening and moderate mid-channel bar lateral erosion. The Hukou-Datong Reach (below 1000 km downstream) experienced minor geomorphic change without significant evidence of bed material coarsening. The relatively small impact of the TGD on the lower reach from Luoshan to Datong can be mainly attributed to the progressive SSC recovery along the river induced by upstream channel erosion providing sediment replenishment. These findings have significant implications for estimating geomorphic changes in response to upstream damming and thus could inform better river management and ecological assessment in other similar alluvial rivers.

Functional and structural characterization of interactions between opposite subunits in HCN pacemaker channels

Hyperpolarization-activated and cyclic nucleotide (HCN) modulated channels are tetrameric cation channels. In each of the four subunits, the intracellular cyclic nucleotide-binding domain (CNBD) is coupled to the transmembrane domain via a helical structure, the C-linker. High-resolution channel structures suggest that the C-linker enables functionally relevant interactions with the opposite subunit, which might be critical for coupling the conformational changes in the CNBD to the channel pore. We combined mutagenesis, patch-clamp technique, confocal patch-clamp fluorometry, and molecular dynamics (MD) simulations to show that residue K464 of the C-linker is relevant for stabilizing the closed state of the mHCN2 channel by forming interactions with the opposite subunit. MD simulations revealed that in the K464E channel, a rotation of the intracellular domain relative to the channel pore is induced, which is similar to the cAMP-induced rotation, weakening the autoinhibitory effect of the unoccupied CL-CNBD region. We suggest that this CL-CNBD rotation is considerably involved in activation-induced affinity increase but only indirectly involved in gate modulation. The adopted poses shown herein are in excellent agreement with previous structural results.

Planetary boundary layer height retrieval from a diode-laser-based high spectral resolution lidar

The planetary boundary layer height (PBLH) is an essential parameter for weather forecasting and climate modeling. The primary methods for obtaining the PBLH include radiosonde measurements of atmospheric parameters and lidar measurements, which track aerosol layers in the lower atmosphere. Radiosondes provide the parameters to determine the PBLH but cannot monitor changes over a diurnal cycle. Lidar instruments can track the temporal variability of the PBLH and account for spatial variability when operated in a network configuration. The networkable micropulse DIAL (MPD) instruments for thermodynamic profiling are based on diode-laser technology that is eye-safe and cost-effective and has demonstrated long-term autonomous operation. We present a retrieval algorithm for determining the PBLH from the quantitative aerosol profiling capability of the high spectral resolution channel of the MPD. The PBLH is determined using a Haar wavelet transform (HWT) method that tracks aerosol layers in the lower atmosphere. The PBLH from the lidar is compared with the PBLH determined from potential temperature profiles from radiosondes. In many cases, good agreement among the PBLH retrievals was seen. However, the radiosonde retrieval often missed the lowest inversion layer when several layers were present, while the HWT could track the lowest layer.

Guest Editorial: Evolution of 5G NR MIMO Standards

The multi-input multi-output (MIMO) technology is proven salient in cellular wireless communications standards for improving end-user experience by increasing the overall spectral efficiency. With the advent of antenna technologies such as active antennas and two-dimensional arrays, deploying base stations with tens or hundreds of antenna elements has become feasible and it is an essential component for successful deployments of 5G New Radio (NR) technologies standardized by the 3rd Generation Partnership Project (3GPP). Also included in 5G NR is the use of mmWave bands where an analog-beam-based transmission and reception paradigm, termed the beam management, poses a new set of challenges and requirements. The initial release of 5G NR, i.e., Rel-15 includes the support of high-resolution channel state information (CSI) to facilitate efficient multi-user MIMO operation, multiple transmit/receive points (multi-TRP) operation, and beam management. Such features are enabled by basic components such as reference signals for facilitating demodulation and CSI measurements, CSI reporting mechanisms for link adaptation and scheduling, transmission schemes for downlink and uplink, and control signaling. 5G NR MIMO has been enhanced in 3GPP Rel-16 and Rel-17 standards. Following the recent completion of Rel-17 standards, 5G NR MIMO would be further enhanced in Rel-18 taking into account various requests to enable new products and more flexible network deployments.

Integrating deep learning with microfluidics for biophysical classification of sickle red blood cells adhered to laminin.

Sickle cell disease, a genetic disorder affecting a sizeable global demographic, manifests in sickle red blood cells (sRBCs) with altered shape and biomechanics. sRBCs show heightened adhesive interactions with inflamed endothelium, triggering painful vascular occlusion events. Numerous studies employ microfluidic-assay-based monitoring tools to quantify characteristics of adhered sRBCs from high resolution channel images. The current image analysis workflow relies on detailed morphological characterization and cell counting by a specially trained worker. This is time and labor intensive, and prone to user bias artifacts. Here we establish a morphology based classification scheme to identify two naturally arising sRBC subpopulations—deformable and non-deformable sRBCs—utilizing novel visual markers that link to underlying cell biomechanical properties and hold promise for clinically relevant insights. We then set up a standardized, reproducible, and fully automated image analysis workflow designed to carry out this classification. This relies on a two part deep neural network architecture that works in tandem for segmentation of channel images and classification of adhered cells into subtypes. Network training utilized an extensive data set of images generated by the SCD BioChip, a microfluidic assay which injects clinical whole blood samples into protein-functionalized microchannels, mimicking physiological conditions in the microvasculature. Here we carried out the assay with the sub-endothelial protein laminin. The machine learning approach segmented the resulting channel images with 99.1±0.3% mean IoU on the validation set across 5 k-folds, classified detected sRBCs with 96.0±0.3% mean accuracy on the validation set across 5 k-folds, and matched trained personnel in overall characterization of whole channel images with R2 = 0.992, 0.987 and 0.834 for total, deformable and non-deformable sRBC counts respectively. Average analysis time per channel image was also improved by two orders of magnitude (∼ 2 minutes vs ∼ 2-3 hours) over manual characterization. Finally, the network results show an order of magnitude less variance in counts on repeat trials than humans. This kind of standardization is a prerequisite for the viability of any diagnostic technology, making our system suitable for affordable and high throughput disease monitoring.

Simulation of Images and Digital Terrain Models for the Mission BepiColombo

BepiColombo mission will provide Digital Terrain Models of the surface of Mercury by means of the stereo channel of the SIMBIO-SYS (Spectrometer and Imaging for MPO BepiColombo Integrated Observatory SYStem) imaging package onboard. The work here described presents a novel approach for the creation of higher resolution stereo products using the high-resolution channel of SIMBIO-SYS. Being the camera rigidly integrated with the spacecraft, this latter must be tilted to acquire stereo pairs necessary for the 3D reconstruction. A new method for image simulation and stereo reconstruction is presented in this work, where the input data are chosen as closely as possible to the real mission parameters. Different simulations are executed changing the illumination conditions and the stereo angles. The Digital Terrain Models obtained are evaluated and an analysis of the best acquisition conditions is performed, helping to improve the image acquisition strategy of BepiColombo mission. In addition, a strategy for the creation of a mosaic from different images acquired with the high-resolution channel of SIMBIO-SYS is explained, giving the possibility to obtain tridimensional products of extended targets.

SEAFLOOR SPREADING AND TECTONICS AT THE CHARLIE GIBBS TRANSFORM SYSTEM (52-53ºN, MID ATLANTIC RIDGE): PRELIMINARY RESULTS FROM R/V A. N. STRAKHOV EXPEDITION S50

The Charlie Gibbs offsetting by ~ 340 km the Mid Atlantic Ridge (MAR) axis at 52°-53° N is one of the main transform systems of the North Atlantic. Located between long mid-ocean ridge segments influenced from the south by the Azores and from the north by the Iceland mantle plumes, this transform system has been active since the early phases of North Atlantic rifting. Object of several surveys in the ’70 and ’80, Charlie Gibbs received great attention for its unique structure characterized by two long-lived right-lateral transform faults linked by a short ~ 40 km-long intra-transform spreading centre (ITR) with parallel fracture zone valleys extending continuously towards the continental margins. In October 2020 expedition S50 of the R/V A.N. Strakhov surveyed an area of 54,552 km2 covering the entire Charlie Gibbs transform system and the adjacent MAR spreading segments. We collected new bathymetric, magnetic and high-resolution single channel seismic data, along with basaltic, gabbroic and mantle rocks from 21 dredges. This work contains preliminary data from cruise S50 and discusses the large-scale architecture of this unique, long-lived transform system.

Оптическая система видеоканала высокого разрешения бинокулярного кольпоскопа

Оптическая система видеоканала высокого разрешения бинокулярного кольпоскопа

Two-Dimensional Channel Parameter Estimation for Millimeter-Wave Systems Using Butler Matrices

In this paper, a novel two-dimensional parameter estimation method is proposed for frequency-selective millimeter-wave (mmWave) channels by probing a limited number of Kronecker products of discrete Fourier transform (DFT) beams, which are efficiently implemented in the analog domain by a novel combination of Butler matrices. The proposed strategy firstly estimates the channel parameters by using a modified parameter estimation via interpolation based on a DFT grid (PREIDG) algorithm. In a second step, high-resolution channel parameter estimation is achieved even in the low signal-to-noise-ratio (SNR) using the space-alternating generalized expectation-maximization (SAGE) algorithm. The proposed modified PREIDG algorithm outperforms state-of-the-art methods, e.g., the auxiliary beam pair (ABP) method while the SAGE algorithm achieves the derived Cramér-Rao lower bound (CRLB). Numerical results demonstrate that excellent estimation performance can be achieved for angle of departure (AoD) azimuth and elevation with addition to delay and complex path gain of each path even in the low SNR regime.