SAMPLE CLOCK OFFSET COMPENSATION IN THE FIFTH-GENERATION NEW RADIO UPLINK

Author(s):  
О.Г. ПОНОМАРЕВ ◽  
М. АСАФ

Рассмотрена проблема коррекции искажений OFDM-сигнала, вызванных смещением частоты дискретизации сигнала в приемном и передающем устройствах системы сотовой связи пятого поколения. Предлагаемый метод компенсации смещения частоты дискретизации основывается на прямой коррекции искажений, вносимых в передаваемый сигнал наличием смещения, и не предполагает какой-либо оценки величины смещения. Метод предназначен для коррекции сигналов в восходящем канале системы сотовой связи пятого поколения и основывается на использовании референсных сигналов, рекомендованных стандартами 3GPP. Результаты численного моделирования показали, что использование предлагаемого метода позволяет повысить эффективность передачи данных по многолучевому радиоканалу более чем на 15% в широком диапазоне значений отношения сигнал/шум. 5G-NR, CP-OFDM, synchronization, sample clock offset, PUSCH. О The paper investigates the issue of sampling clock offset ( SCO) in the fifth generation new radio systems. Due to the imperfect SCO estimation methods, the correction methods relying on the SCO estimation are not perfect, so the proposed method directly corrects the effect of SCO without using any kind of estimation method. Our method is designed to correct the signals in the physical uplink shared channel (PUSCH). The method uses reference signals as recommended by the 3rd generation partnership project (3GPP) standards. The results of the numerical simulation show that the use of the proposed method increases the efficiency of data transmission over the multipath radio channel by more than 15% in a wide range of signal-to-noise ratio values.

2021 ◽  
Author(s):  
Di Zhao ◽  
Weijie Tan ◽  
Zhongliang Deng ◽  
Gang Li

Abstract In this paper, we present a low complexity beamspace direction-of-arrival (DOA) estimation method for uniform circular array (UCA), which is based on the single measurement vectors (SMVs) via vectorization of sparse covariance matrix. In the proposed method, we rstly transform the signal model of UCA to that of virtual uniform linear array (ULA) in beamspace domain using the beamspace transformation (BT). Subsequently, by applying the vectorization operator on the virtual ULA-like array signal model, a new dimension-reduction array signal model consists of SMVs based on Khatri-Rao (KR) product is derived. And then, the DOA estimation is converted to the convex optimization problem. Finally, simulations are carried out to verify the eectiveness of the proposed method, the results show that without knowledge of the signal number, the proposed method not only has higher DOA resolution than subspace-based methods in low signal-to-noise ratio (SNR), but also has much lower computational complexity comparing other sparse-like DOA estimation methods.


2017 ◽  
Vol 13 (2) ◽  
pp. 155014771668968 ◽  
Author(s):  
Sunyong Kim ◽  
Sun Young Park ◽  
Daehoon Kwon ◽  
Jaehyun Ham ◽  
Young-Bae Ko ◽  
...  

In wireless sensor networks, the accurate estimation of distances between sensor nodes is essential. In addition to the distance information available for immediate neighbors within a sensing range, the distance estimation of two-hop neighbors can be exploited in various wireless sensor network applications such as sensor localization, robust data transfer against hidden terminals, and geographic greedy routing. In this article, we propose a two-hop distance estimation method, which first obtains the region in which the two-hop neighbor nodes possibly exist and then takes the average of the distances to the points in that region. The improvement in the estimation accuracy achieved by the proposed method is analyzed in comparison with a simple summation method that adds two single-hop distances as an estimate of a two-hop distance. Numerical simulation results show that in comparison with other existing distance estimation methods, the proposed method significantly reduces the distance estimation error over a wide range of node densities.


2019 ◽  
Vol 491 (2) ◽  
pp. 2688-2705 ◽  
Author(s):  
Denis Vida ◽  
Peter S Gural ◽  
Peter G Brown ◽  
Margaret Campbell-Brown ◽  
Paul Wiegert

ABSTRACT It has recently been shown by Egal et al. that some types of existing meteor in-atmosphere trajectory estimation methods may be less accurate than others, particularly when applied to high-precision optical measurements. The comparative performance of trajectory solution methods has previously only been examined for a small number of cases. Besides the radiant, orbital accuracy depends on the estimation of pre-atmosphere velocities, which have both random and systematic biases. Thus, it is critical to understand the uncertainty in velocity measurement inherent to each trajectory estimation method. In this first of a series of two papers, we introduce a novel meteor trajectory estimation method that uses the observed dynamics of meteors across stations as a global optimization function and that does not require either a theoretical or an empirical flight model to solve for velocity. We also develop a 3D observational meteor trajectory simulator that uses a meteor ablation model to replicate the dynamics of meteoroid flight, as a means to validate different trajectory solvers. We both test this new method and compare it to other methods, using synthetic meteors from three major showers spanning a wide range of velocities and geometries (Draconids, Geminids, and Perseids). We determine which meteor trajectory solving algorithm performs better for all-sky, moderate field-of-view, and high-precision narrow-field optical meteor detection systems. The results are presented in the second paper in this series. Finally, we give detailed equations for estimating meteor trajectories and analytically computing meteoroid orbits, and provide the python code of the methodology as open-source software.


Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8296
Author(s):  
Cezary Ziółkowski ◽  
Jan M. Kelner ◽  
Jarosław Krygier ◽  
Aniruddha Chandra ◽  
Aleš Prokeš

The basic technology that will determine the expansion of the technical capabilities of fifth generation cellular systems is a massive multiple-input-multiple-output. Therefore, assessing the influence of the antenna beam orientations on the radio channel capacity is very significant. In this case, the effects of mismatching the antenna beam directions are crucial. In this paper, the methodology for evaluating changes in the received signal power level due to beam misalignment for the transmitting and receiving antenna systems is presented. The quantitative assessment of this issue is presented based on simulation studies carried out for an exemplary propagation scenario. For non-line-of-sight (NLOS) conditions, it is shown that the optimal selection of the transmitting and receiving beam directions may ensure an increase in the level of the received signal by several decibels in relation to the coaxial position of the beams. The developed methodology makes it possible to analyze changes in the radio channel capacity versus the signal-to-noise ratio and distance between the transmitter and receiver at optimal and coaxial orientations of antenna beams for various propagation scenarios, considering NLOS conditions. In the paper, the influence of the directional antenna use and their direction choices on the channel capacity versus SNR and the distance between the transmitter and receiver is shown.


2000 ◽  
Vol 57 (1) ◽  
pp. 181-191 ◽  
Author(s):  
Randall M Peterman ◽  
Brian J Pyper ◽  
Jeff A Grout

Pacific salmon (Oncorhynchus spp.) populations can experience persistent changes in productivity, possibly due to climatic shifts. Management agencies need to rapidly and reliably detect such changes to avoid costly suboptimal harvests or depletion of stocks. However, given the inherent variability of salmon populations, it is difficult to detect changes quickly, let alone forecast them. We therefore compared three methods of annually updating estimates of stock-recruitment parameters: standard linear regression, Walters' bias-corrected regression, and a Kalman filter. We used Monte Carlo simulations that hypothesized a wide range of future climate-induced changes in the Ricker a parameter of a salmon stock. We then used each parameter estimation method on the simulated stock and recruitment data and set escapement targets and harvest goals accordingly. In these situations with a time-varying true Ricker a parameter, Kalman filter estimation resulted in greater mean cumulative catch than was produced by the standard linear regression approach, Walters' bias correction method, or a fixed harvest rate policy. This benefit of the Kalman filter resulted from its better ability to track changing parameter values, thereby producing escapements closer to the optimal escapement each year. However, errors in implementing desired management actions can significantly reduce benefits from all parameter estimation techniques.


Author(s):  
Mats-Olof Mattsson ◽  
Myrtill Simkó ◽  
Kenneth R. Foster

The development and establishment of mobile communication technologies has necessitated assessments of possible risks to human health from exposures to radio-frequency electromagnetic fields (RF EMF). A number of expert committees have concluded that there is no evidence for such risks as long as exposures are at or below levels that do not allow tissue heating. These assessments have been based primarily on studies investigating frequencies up to 6 GHz including frequencies similar to those used by two of three major bands of fifth generation (more accurately 5G New Radio or 5G NR) of mobile communication. Bioeffects studies in so-called high-band at 25–39 GHz are particularly sparse. Future assessments relevant for these frequencies will need to rely on still unperformed studies. Due to few available studies at 5G NR “high band” frequencies, and questions raised by some existing studies, a recent review recommended a wide range of RF biostudies be done at 5G NR “high band” frequencies. It is of importance that such studies be done using the best possible science. Here we suggest factors to consider when performing future studies in this area. The present focus is on laboratory studies to clarify biological effects of radiofrequency (RF) energy at 5G “high band” frequencies and, more generally at millimeter wave (mm-wave) frequencies (30-300 GHz) which will be increasingly used by communications technologies in the future. Similar comments would apply to epidemiology and exposure assessment studies, but those are not the focus of the present Perspective.


Author(s):  
Di Zhao ◽  
Weijie Tan ◽  
Zhongliang Deng ◽  
Gang Li

AbstractIn this paper, we present a low complexity sparse beamspace direction-of-arrival (DOA) estimation method for uniform circular array (UCA). In the proposed method, we firstly use the beamspace transformation (BT) to transform the signal model of UCA in element-space domain to that of virtual uniform linear array (ULA) in beamspace domain. Subsequently, by applying the vectoring operator on the virtual ULA-like array signal model, a novel dimension-reduction sparse beamspace signal model is derived based on Khatri-Rao (KR) product, the observation data of which is represented by the single measurement vectors (SMVs) via vectorization of sparse covariance matrix. And then, the DOA estimation is formulated as a convex optimization problem by following the concept of a sparse-signal-representation (SSR) of the SMVs. Finally, simulations are carried out to validate the effectiveness of the proposed method. The results show that without knowledge of the number of signals, the proposed method not only has higher DOA resolution than the subspace-based methods in low signal-to-noise ratio (SNR), but also has far lower computational complexity than other sparse-like DOA estimation methods.


2020 ◽  
Vol 2020 (66) ◽  
pp. 101-110
Author(s):  
. Azhar Kadhim Jbarah ◽  
Prof Dr. Ahmed Shaker Mohammed

The research is concerned with estimating the effect of the cultivated area of barley crop on the production of that crop by estimating the regression model representing the relationship of these two variables. The results of the tests indicated that the time series of the response variable values is stationary and the series of values of the explanatory variable were nonstationary and that they were integrated of order one ( I(1) ), these tests also indicate that the random error terms are auto correlated and can be modeled according to the mixed autoregressive-moving average models ARMA(p,q), for these results we cannot use the classical estimation method to estimate our regression model, therefore, a fully modified M method was adopted, which is a robust estimation methods, The estimated results indicate a positive significant relation between the production of barley crop and cultivated area.


2018 ◽  
Vol 10 (10) ◽  
pp. 3626 ◽  
Author(s):  
Yousaf Zikria ◽  
Sung Kim ◽  
Muhammad Afzal ◽  
Haoxiang Wang ◽  
Mubashir Rehmani

The Fifth generation (5G) network is projected to support large amount of data traffic and massive number of wireless connections. Different data traffic has different Quality of Service (QoS) requirements. 5G mobile network aims to address the limitations of previous cellular standards (i.e., 2G/3G/4G) and be a prospective key enabler for future Internet of Things (IoT). 5G networks support a wide range of applications such as smart home, autonomous driving, drone operations, health and mission critical applications, Industrial IoT (IIoT), and entertainment and multimedia. Based on end users’ experience, several 5G services are categorized into immersive 5G services, intelligent 5G services, omnipresent 5G services, autonomous 5G services, and public 5G services. In this paper, we present a brief overview of 5G technical scenarios. We then provide a brief overview of accepted papers in our Special Issue on 5G mobile services and scenarios. Finally, we conclude this paper.


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