scholarly journals Throughput of Wireless-Powered Based Multiuser System with Large-Scale Distributed Antennas

Information ◽  
2018 ◽  
Vol 10 (1) ◽  
pp. 13
Author(s):  
Qing Wang ◽  
Jingbo Wei ◽  
Weidong Guo
Keyword(s):  
Information Transmission ◽  
Large Scale ◽  
Minimum Mean Square Error ◽  
Transmission Protocol ◽  
Wireless Energy Transfer ◽  
Zero Forcing ◽  
Multiuser System ◽  
Shortest Distance ◽  
Simulation Results ◽  
Distributed Antennas

This paper investigates energy harvesting based multiuser system with large-scale distributed antennas, where a large number of remote antenna units (RAUs) are evenly separated across multiple circles. An efficient wireless energy and information transmission protocol is proposed. To save the signaling and the radio frequency chains overheads, the RAU with the shortest distance towards a user equipment (UE) is employed for the downlink wireless energy transfer (WET). In the uplink phase, we analyze the probability of wireless information transmission (WIT) of UEs. Then, linear zero-forcing detection and minimum-mean-square error are used to separate the data information among all the UEs that satisfy the requirement of WIT. The asymptotic throughput for an arbitrary UE is derived in closed-form. The time fraction used for the WET is optimized through maximizing the asymptotic throughput. Numerical and simulation results are given to verify the theoretical analysis, and bring to light the time fraction planning and the RAUs deployment for the system.

scholarly journals Low-complexity sparse-aware multiuser detection for large-scale MIMO systems

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Rong Ran ◽  
Hayoung Oh
Keyword(s):  
Large Scale ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Low Complexity ◽  
Finite Alphabet ◽  
Multiuser Detectors ◽  
Input Multiple Output ◽  
Error Detector ◽  
Significant Performance

AbstractSparse-aware (SA) detectors have attracted a lot attention due to its significant performance and low-complexity, in particular for large-scale multiple-input multiple-output (MIMO) systems. Similar to the conventional multiuser detectors, the nonlinear or compressive sensing based SA detectors provide the better performance but are not appropriate for the overdetermined multiuser MIMO systems in sense of power and time consumption. The linear SA detector provides a more elegant tradeoff between performance and complexity compared to the nonlinear ones. However, the major limitation of the linear SA detector is that, as the zero-forcing or minimum mean square error detector, it was derived by relaxing the finite-alphabet constraints, and therefore its performance is still sub-optimal. In this paper, we propose a novel SA detector, named single-dimensional search-based SA (SDSB-SA) detector, for overdetermined uplink MIMO systems. The proposed SDSB-SA detector adheres to the finite-alphabet constraints so that it outperforms the conventional linear SA detector, in particular, in high SNR regime. Meanwhile, the proposed detector follows a single-dimensional search manner, so it has a very low computational complexity which is feasible for light-ware Internet of Thing devices for ultra-reliable low-latency communication. Numerical results show that the the proposed SDSB-SA detector provides a relatively better tradeoff between the performance and complexity compared with several existing detectors.

scholarly journals Design and Evaluation of Large-Scale IoT-Enabled Healthcare Architecture

2021 ◽  
Vol 11 (8) ◽  
pp. 3623
Author(s):  
Omar Said ◽  
Amr Tolba
Keyword(s):  
Packet Loss ◽  
Large Scale ◽  
Performance Metrics ◽  
Medical System ◽  
Healthcare Data ◽  
High Altitude Platforms ◽  
Wide Range ◽  
Simulation Results ◽  
Healthcare Architecture ◽  
The Internet Of Things

Employment of the Internet of Things (IoT) technology in the healthcare field can contribute to recruiting heterogeneous medical devices and creating smart cooperation between them. This cooperation leads to an increase in the efficiency of the entire medical system, thus accelerating the diagnosis and curing of patients, in general, and rescuing critical cases in particular. In this paper, a large-scale IoT-enabled healthcare architecture is proposed. To achieve a wide range of communication between healthcare devices, not only are Internet coverage tools utilized but also satellites and high-altitude platforms (HAPs). In addition, the clustering idea is applied in the proposed architecture to facilitate its management. Moreover, healthcare data are prioritized into several levels of importance. Finally, NS3 is used to measure the performance of the proposed IoT-enabled healthcare architecture. The performance metrics are delay, energy consumption, packet loss, coverage tool usage, throughput, percentage of served users, and percentage of each exchanged data type. The simulation results demonstrate that the proposed IoT-enabled healthcare architecture outperforms the traditional healthcare architecture.

scholarly journals The Flexible Operation of Coal Power and Its Renewable Integration Potential in China

2019 ◽  
Vol 11 (16) ◽  
pp. 4424 ◽  
Author(s):  
Chunning Na ◽  
Huan Pan ◽  
Yuhong Zhu ◽  
Jiahai Yuan ◽  
Lixia Ding ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
Power System ◽  
Large Scale ◽  
Renewable Integration ◽  
Flexible Resources ◽  
Feasible Option ◽  
Coal Power ◽  
Simulation Results ◽  
Flexible Operation

At present time, China’s power systems face significant challenges in integrating large-scale renewable energy and reducing the curtailed renewable energy. In order to avoid the curtailment of renewable energy, the power systems need significant flexibility requirements in China. In regions where coal is still heavily relied upon for generating electricity, the flexible operations of coal power units will be the most feasible option to face these challenges. The study first focused on the reasons why the flexible operation of existing coal power units would potentially promote the integration of renewable energy in China and then reviewed the impacts on the performance levels of the units. A simple flexibility operation model was constructed to estimate the integration potential with the existing coal power units under several different scenarios. This study’s simulation results revealed that the existing retrofitted coal power units could provide flexibility in the promotion of the integration of renewable energy in a certain extent. However, the integration potential increment of 20% of the rated power for the coal power units was found to be lower than that of 30% of the rated power. Therefore, by considering the performance impacts of the coal power units with low performances in load operations, it was considered to not be economical for those units to operate at lower than 30% of the rated power. It was believed that once the capacity share of the renewable energy had achieved a continuously growing trend, the existing coal power units would fail to meet the flexibility requirements. Therefore, it was recommended in this study that other flexible resources should be deployed in the power systems for the purpose of reducing the curtailment of renewable energy. Furthermore, based on this study’s obtained evidence, in order to realize a power system with high proportions of renewable energy, China should strive to establish a power system with adequate flexible resources in the future.

scholarly journals Control method for the stable operation of distributed inverters following the introduction of large-scale renewable energy to a remote island grid

Clean Energy ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 196-207
Author(s):  
Shoichi Sato ◽  
Yasuhiro Noro
Keyword(s):  
Renewable Energy ◽  
Large Scale ◽  
Control Method ◽  
Synchronous Generator ◽  
Stable Operation ◽  
Battery Energy Storage Systems ◽  
Simulation Results ◽  
Battery Energy ◽  
Systems Simulation ◽  
Different Characteristics

Abstract The introduction of large-scale renewable energy requires a control system that can operate multiple distributed inverters in a stable way. This study proposes an inverter control method that uses information corresponding to the inertia of the synchronous generator to coordinate the operation of battery energy storage systems. Simulation results for a system with multiple inverters applying the control method are presented. Various faults such as line-to-line short circuits and three-phase line-to-ground faults were simulated. Two fault points with different characteristics were compared. The voltage, frequency and active power quickly returned to their steady-state values after the fault was eliminated. From the obtained simulation results, it was verified that our control method can be operated stably against various faults.

Large-scale Structure and Turbulence Transport in the Young Solar Wind – Comparison of Parker Solar Probe Observations with a Global 3D Reynolds-averaged MHD Model

2021 ◽  
Author(s):  
Rohit Chhiber ◽  
Arcadi Usmanov ◽  
William Matthaeus ◽  
Melvyn Goldstein ◽  
Riddhi Bandyopadhyay
Keyword(s):  
Solar Wind ◽  
Large Scale ◽  
Transport Equations ◽  
Turbulence Energy ◽  
Reynolds Stresses ◽  
Mean Flow ◽  
Coulomb Collisions ◽  
Flow Equations ◽  
Simulation Results ◽  
Turbulence Transport

<div>Simulation results from a global <span>magnetohydrodynamic</span> model of the solar corona and the solar wind are compared with Parker Solar <span>Probe's</span> (<span>PSP</span>) observations during its first several orbits. The fully three-dimensional model (<span>Usmanov</span> <span>et</span> <span>al</span>., 2018, <span>ApJ</span>, 865, 25) is based on Reynolds-averaged mean-flow equations coupled with turbulence transport equations. The model accounts for effects of electron heat conduction, Coulomb collisions, Reynolds stresses, and heating of protons and electrons via nonlinear turbulent cascade. Turbulence transport equations for turbulence energy, cross <span>helicity</span>, and correlation length are solved concurrently with the mean-flow equations. We specify boundary conditions at the coronal base using solar synoptic <span>magnetograms</span> and calculate plasma, magnetic field, and turbulence parameters along the <span>PSP</span> trajectory. We also accumulate data from all orbits considered, to obtain the trends observed as a function of heliocentric distance. Comparison of simulation results with <span>PSP</span> data show general agreement. Finally, we generate synthetic fluctuations constrained by the local rms turbulence amplitude given by the model, and compare properties of this synthetic turbulence with PSP observations.</div>

scholarly journals Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods

2017 ◽  
Author(s):  
Cherry May R. Mateo ◽  
Dai Yamazaki ◽  
Hyungjun Kim ◽  
Adisorn Champathong ◽  
Jai Vaze ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Large Scale ◽  
Flood Hazard ◽  
Regional Scale ◽  
Global Scale ◽  
Test Case ◽  
Efficiency Coefficient ◽  
Computational Power ◽  
Extreme Flood ◽  
Simulation Results

Abstract. Global-scale River Models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representation of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash–Sutcliffe Efficiency coefficient decreased by more than 35 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions in finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings are universal and can be extended to global-scale simulations. These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

scholarly journals Improving COVID-19 Testing Efficiency using Guided Agglomerative Sampling

2020 ◽  
Author(s):  
Fayyaz Minhas ◽  
Dimitris Grammatopoulos ◽  
Lawrence Young ◽  
Imran Amin ◽  
David Snead ◽  
...  
Keyword(s):  
Large Scale ◽  
Resource Constraints ◽  
Large Population ◽  
Sampling Strategy ◽  
Population Surveillance ◽  
Large Scale Testing ◽  
Scale Population ◽  
Simulation Results ◽  
The Given ◽  
Test Outcomes

AbstractOne of the challenges in the current COVID-19 crisis is the time and cost of performing tests especially for large-scale population surveillance. Since, the probability of testing positive in large population studies is expected to be small (<15%), therefore, most of the test outcomes will be negative. Here, we propose the use of agglomerative sampling which can prune out multiple negative cases in a single test by intelligently combining samples from different individuals. The proposed scheme builds on the assumption that samples from the population may not be independent of each other. Our simulation results show that the proposed sampling strategy can significantly increase testing capacity under resource constraints: on average, a saving of ~40% tests can be expected assuming a positive test probability of 10% across the given samples. The proposed scheme can also be used in conjunction with heuristic or Machine Learning guided clustering for improving the efficiency of large-scale testing further. The code for generating the simulation results for this work is available here: https://github.com/foxtrotmike/AS.

scholarly journals Maximizing Energy Efficiency for Consumption Circuit Power in Downlink Massive MIMO Wireless Networks

2017 ◽  
Vol 7 (6) ◽  
pp. 2977 ◽  
Author(s):  
Adeeb Salh ◽  
Lukman Audah ◽  
Nor Shahida M. Shah ◽  
Shipun A. Hamzah
Keyword(s):  
Energy Efficiency ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Minimum Mean Square Error ◽  
Data Rate ◽  
Optimal Number ◽  
Zero Forcing ◽  
High Data ◽  
Circuit Power

<span>Massive multi-input–multi-output (MIMO) systems are crucial to maximizing energy efficiency (EE) and battery-saving technology. Achieving EE without sacrificing the quality of service (QoS) is increasingly important for mobile devices. We first derive the data rate through zero forcing (ZF) and three linear precodings: maximum ratio transmission (MRT), zero forcing (ZF), and minimum mean square error (MMSE). Performance EE can be achieved when all available antennas are used and when taking account of the consumption circuit power ignored because of high transmit power. The aim of this work is to demonstrate how to obtain maximum EE while minimizing power consumed, which achieves a high data rate by deriving the optimal number of antennas in the downlink massive MIMO system. This system includes not only the transmitted power but also the fundamental operation circuit power at the transmitter signal. Maximized EE depends on the optimal number of antennas and determines the number of active users that should be scheduled in each cell. We conclude that the linear precoding technique MMSE achieves the maximum EE more than ZF and MRT</span><em></em><span>because the MMSE is able to make the massive MIMO system less sensitive to SNR at an increased number of antennas</span><span>.</span>

Traffic Fuzzy Controller's Improvement Based on Self-Adaptive Optimal Algorithm

2012 ◽  
Vol 562-564 ◽  
pp. 1414-1417
Author(s):  
Zhi Yi Xu ◽  
Da Lu Guan ◽  
Ai Long Fan
Keyword(s):  
Mathematical Model ◽  
Large Scale ◽  
Fuzzy Controller ◽  
Optimal Algorithm ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Time Varying ◽  
Large Scale Systems ◽  
Simulation Results ◽  
Self Adaptive

The transport system is a nonlinear, time-varying, lagging large-scale systems. Fuzzy control does not need to build a precise mathematical model, can be easily integrated people's thinking and experience, and is suitable for applications in the traffic signal control system. Here,a self-adaptive optimal algorithm was used to improve the traditional fuzzy controller. Simulation results show that the improved system has higher availability.

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