scholarly journals SIR Meta Distribution in the Heterogeneous and Hybrid Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Yuhong Sun ◽  
Qinghai Liu ◽  
Hua Wang
Keyword(s):  
Process Model ◽  
Network Performance ◽  
Success Probability ◽  
Path Loss ◽  
Wireless Systems ◽  
Hybrid Networks ◽  
Fine Grained ◽  
Link Rate ◽  
Significant Attention ◽  
Typical User

With the development of the technology, the wireless systems are becoming more heterogeneous with the introduction of various power nodes including femtocells, relays, or distributed antennas. Among the research of wireless network performance, the meta distribution of the signal-to-interference ratio (SIR) has attracted significant attention. Compared to the standard success (coverage) probability, the meta distribution provides much more fine-grained information about the network performance. In this paper, we analyze the meta distribution of the SIR in the multi-tier heterogeneous and hybrid networks, where each tier is based on a homogeneous independent Poisson point process model. For the open tiers (the users can associate with any tier) and the closed tiers (the users can only associate with a certain tier), we study the b th moment of the conditional success probability for the typical user and give the beta approximation of the meta distribution from analysis and simulations. Furthermore, we analyze the per-link rate control for open tiers and closed tiers, which answers the question: “how to set the SIR threshold to meet a target reliability?”. We give the approximate value of the SIR threshold to meet a target reliability and show how the value is related to the path loss exponent and densities.

scholarly journals LVD-NMPC: A learning-based vision dynamics approach to nonlinear model predictive control for autonomous vehicles

2021 ◽  
Vol 18 (3) ◽  
pp. 172988142110195
Author(s):  
Sorin Grigorescu ◽  
Cosmin Ginerica ◽  
Mihai Zaha ◽  
Gigel Macesanu ◽  
Bogdan Trasnea
Keyword(s):  
Neural Network ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Nonlinear Model ◽  
Autonomous Vehicles ◽  
Process Model ◽  
Network Performance ◽  
Vision System ◽  
Nonlinear Model Predictive Control ◽  
Scaled Model

In this article, we introduce a learning-based vision dynamics approach to nonlinear model predictive control (NMPC) for autonomous vehicles, coined learning-based vision dynamics (LVD) NMPC. LVD-NMPC uses an a-priori process model and a learned vision dynamics model used to calculate the dynamics of the driving scene, the controlled system’s desired state trajectory, and the weighting gains of the quadratic cost function optimized by a constrained predictive controller. The vision system is defined as a deep neural network designed to estimate the dynamics of the image scene. The input is based on historic sequences of sensory observations and vehicle states, integrated by an augmented memory component. Deep Q-learning is used to train the deep network, which once trained can also be used to calculate the desired trajectory of the vehicle. We evaluate LVD-NMPC against a baseline dynamic window approach (DWA) path planning executed using standard NMPC and against the PilotNet neural network. Performance is measured in our simulation environment GridSim, on a real-world 1:8 scaled model car as well as on a real size autonomous test vehicle and the nuScenes computer vision dataset.

scholarly journals Optimization of Wireless Communication Coverage in Underground Tunnels Based on Zone Division

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Yu Huo ◽  
Qingsong Hu ◽  
Yanjing Sun ◽  
Xiwang Guo ◽  
Liang Qi ◽  
...  
Keyword(s):  
Wireless Communication ◽  
Fresnel Zone ◽  
Path Loss ◽  
Wireless Systems ◽  
Real Data ◽  
Communication Signal ◽  
Transmitting Antenna ◽  
Antenna Polarization ◽  
Zone Division ◽  
Multimodal Method

In order to reduce the path loss of the wireless communication signal in the underground tunnel, a scheme for configuring the antenna polarization of wireless systems based on a zone-division method is proposed. A multimodal method is used to estimate the effect of antenna polarization on the wireless propagation. When the optimal polarization of the antenna leading to low path loss is different in the zones near and far from the transmitting antenna, a dividing point is used to separate the zones. Experiments are conducted in an underground mine. It shows that the results by the multimodal method are consistent with the real data. Compared with the existing coverage schemes, the proposed scheme can obtain better coverage. Meanwhile, zone division has an important influence on the optimized performance of the wireless coverage. The zones divided based on Fresnel zone clearance and system identification are too small or too large, which result in incorrect polarization switching and high path loss.

scholarly journals A Genetic Algorithm-based Framework for Soft Handoff Optimization in Wireless Networks

2017 ◽  
Vol 5 (1) ◽  
pp. 1
Author(s):  
Daniel E. Asuquo ◽  
Samuel A. Robinson
Keyword(s):  
Genetic Algorithm ◽  
Wireless Networks ◽  
Network Performance ◽  
Heterogeneous Wireless Networks ◽  
Success Probability ◽  
Mobile Terminal ◽  
Soft Handoff ◽  
Global Optima ◽  
Promising Solution ◽  
The One

In this paper, a genetic algorithm (GA)-based approach is used to evaluate the probability of successful handoff in heterogeneous wireless networks (HWNs) so as to increase capacity and network performance. The traditional handoff schemes are prone to ping pong and corner effects and developing an optimized handoff scheme for seamless, faster, and less power consuming handoff decision is challenging. The GA scheme can effectively optimize soft handoff decision by selecting the best fit network for the mobile terminal (MT) considering quality of service (QoS) requirements, network parameters and user’s preference in terms of cost of different attachment points for the MT. The robustness and ability to determine global optima for any function using crossover and mutation operations makes GA a promising solution. The developed optimization framework was simulated in Matrix Laboratory (MATLAB) software using MATLAB’s optima tool and results show that an optimal MT attachment point is the one with the highest handoff success probability value which determines direction for successful handoff in HWN environment. The system maintained a 90%  with 4 channels and more while a 75% was obtained even at high traffic intensity.

scholarly journals The Effective Radiation Pattern Concept for Realistic Performance Estimation of LTE Wireless Systems

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Dimitra Zarbouti ◽  
George Tsoulos ◽  
Georgia Athanasiadou ◽  
Constantinos Valagiannopoulos
Keyword(s):  
Radiation Pattern ◽  
Network Performance ◽  
Wireless Systems ◽  
Performance Estimation ◽  
Reference Scenario ◽  
The Real ◽  
4G Lte ◽  
Performance Results ◽  
Effective Radiation ◽  
Identical Performance

Radio channels induce distortions to the radiation pattern of beamforming systems such as beam broadening as well as sidelobe level and null rising. If these effects are ignored, the system performance is overestimated. This paper proposes the simple concept of an effective radiation pattern (ERP) calculated by optimally fitting the “real-world” radiation pattern to the ERP. The proposed ERP method is incorporated into a multicell bad urban 4G LTE operational scenario which employs beamforming for both the BSs and the RNs. The performed simulations provide evidence that the ideal instead of the real radiation pattern overestimates the SIR and capacity by almost 3 dB and 13 Mbps, respectively, for the reference scenario without RNs. It also proves that the ERP method produces almost identical performance results with the real radiation pattern, and hence it is a simple and viable option for realistic performance analysis. Finally, the network performance is studied as a function of the number of RNs with the help of the ERP method. Results show that a beamforming LTE network with RNs that also employ beamforming provides 3 dB SIR gain with the addition of 1 RN per cell and 15 dB gain with 4 RNs per cell.

Supporting the Development of Personalized E-Health

2010 ◽  
pp. 353-367
Author(s):  
Ulrika Josefsson
Keyword(s):  
Health Informatics ◽  
Technology Development ◽  
Qualitative Approach ◽  
Patient Centeredness ◽  
Patient Centered ◽  
Patient Role ◽  
Fine Grained ◽  
Introductory Discussion ◽  
Depth Interviews ◽  
Significant Attention

The area of E-health development for patient-healthcare interaction has lately received significant attention by the health informatics community. Increasingly healthcare and information technology (IT) developers are proposed to take seriously the needs and preferences of the patients. This chapter explores the multifaceted E-patient context, in an effort to contribute to an increased patient-centeredness of this form of technology development. Patient-centeredness is captured in terms of personalization as an attempt to depart from patients’ specific context to contribute to technology design and use. Using a qualitative approach, the chapter reports from 25 in-depth interviews performed with Swedish patients and representatives of patient associations. Six themes of the E-patient context derive from the findings (diagnosis, demographics, access, preferences, coping, and patient role). The results present a fine-grained picture of the E-patient context adding to previous approaches of personalization. The introductory discussion reflects on the themes in relation to their tentative implications for the development of patient-centered personalized E-health for patient-healthcare interaction.

Creating Pathways to Personal Resilience Through Classroom Simulations

2019 ◽  
Vol 50 (2) ◽  
pp. 214-242 ◽  
Author(s):  
Lorin Walker ◽  
Ray Luechtefeld ◽  
Jo Anne Long Walker
Keyword(s):  
Student Outcomes ◽  
Process Model ◽  
Faculty Support ◽  
Traditional Course ◽  
Student Management ◽  
Resilience Scale ◽  
Adverse Experiences ◽  
Personal Resilience ◽  
Bounce Back ◽  
Significant Attention

Background. College or university classroom simulations have the potential to create valuable educational outcomes that are difficult to achieve by other means. Personal resilience is one outcome that has achieved significant attention in the literature. Personal resilience is the ability to bounce back, learn from, and move forward after adverse experiences. Aim. This study posits that student personal resilience will increase following participation in university undergraduate management courses that use simulations that are grounded in a proposed teleological process model that includes six causal relationships. Method. Eighty-four students participated in either a Capstone strategy course using the Capsim simulation or a semester-long classroom as organization open simulation called XB that involved student management of all course aspects. The Connor-Davidson Resilience Scale (CD-RISC 10) survey instrument was used to measure personal resilience at both the beginning and end of each course. Results. In several cases, student personal resilience was significantly increased after courses utilizing simulations involving specific features. Conclusions. Participation in these kinds of experiences (with faculty support) may significantly increase levels of personal resilience among students. Recommendations. Simulations with the specified causal attributes might be used to foster student outcomes such as personal resilience, which typically are not a part of traditional course objectives.

scholarly journals An environmental channel throughput and radio propagation modeling for vehicle-to-vehicle communication

2018 ◽  
Vol 14 (4) ◽  
pp. 155014771877253 ◽  
Author(s):  
Mohammed Abdulhakim Al-Absi ◽  
Ahmed Abdulhakim Al-Absi ◽  
TaeYong Kim ◽  
Hoon Jae Lee
Keyword(s):  
Network Performance ◽  
Path Loss ◽  
Packet Delivery Ratio ◽  
Propagation Model ◽  
Radio Propagation ◽  
Propagation Path ◽  
Line Of Sight ◽  
Delivery Ratio ◽  
Intelligent Transport System ◽  
Packet Delivery

Developing a secure and smart intelligent transport system for both safety and non-safety application services requires a certain guarantee of network performance, especially in terms of throughput and packet collision performance. The vehicular ad hoc network propagation is strongly affected due to varying nature of the environment. The existing radio propagation path loss models are designed by using mean additional attenuation sophisticated fading models. However, these models do not consider the obstacle caused due to the obstacle of the vehicle in line of sight of the transmitting and receiving vehicle. Thus, the attenuation signal at the receiving vehicles/devices is affected. To address this issue, we present an obstacle-based radio propagation model that considers the effect caused due to the presence of obstructing vehicle in line of sight. This model is evaluated under different environmental conditions (i.e. city, highway, and rural) by varying the speed of vehicles and vehicles’ density. The performance of the model is evaluated in terms of throughput, collision, transmission efficiency, and packet delivery ratio. The overall result shows that the proposed obstacle-based throughput model is efficient considering varied speed and density. For instance, in the city environment, the model achieves an average improvement of 9.98% and 25.02% for throughput performance over other environments by varying the speed and density of devices respectively and an improvement of 15.04% for packet delivery ratio performance over other environments considering varied speed of devices.

scholarly journals Extracting Valuable Information from Big Data for Machine Learning Control: An Application for a Gas Lift Process

Processes ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 252
Author(s):  
Ana Carolina Spindola Rangel Dias ◽  
Felipo Rojas Soares ◽  
Johannes Jäschke ◽  
Maurício Bezerra de Souza ◽  
José Carlos Pinto
Keyword(s):  
Process Model ◽  
Network Performance ◽  
Oil Well ◽  
Data Sets ◽  
Training Set ◽  
Model Mismatch ◽  
The Neural Network ◽  
Control Scheme ◽  
Noisy Measurements ◽  
Gas Lift

The present work investigated the use of an echo state network for a gas lift oil well. The main contribution is the evaluation of the network performance under conditions normally faced in a real production system: noisy measurements, unmeasurable disturbances, sluggish behavior and model mismatch. The main pursued objective was to verify if this tool is suitable to compose a predictive control scheme for the analyzed operation. A simpler model was used to train the neural network and a more accurate process model was used to generate time series for validation. The system performance was investigated with distinct sample sizes for training, test and validation procedures and prediction horizons. The performance of the designed ESN was characterized in terms of slugging, setpoint changes and unmeasurable disturbances. It was observed that the size and the dynamic content of the training set tightly affected the network performance. However, for data sets with reasonable information contents, the obtained ESN performance could be regarded as very good, even when longer prediction horizons were proposed.

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