scholarly journals Transmission Optimization Metrics Setup Issues in the Field of Time Constrained Communications

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3104
Author(s):  
Ondřej Vondrouš ◽  
Zbyněk Kocur ◽  
Jaromír Hrad
Keyword(s):  
Resource Allocation ◽  
Traffic Flow ◽  
Network Optimization ◽  
Narrow Band ◽  
Optimization Method ◽  
Data Traffic ◽  
Successful Completion ◽  
Specific Nature ◽  
New Approach ◽  
Proper Setting

This article introduces a new approach in the field of network optimization based on Transmission Optimization Metric (TOM), which is aimed at improving traffic flow continuity and increasing the chances for traffic flow sustainability in a way that helps to minimize inter-packet gaps. The work is mainly focused on harsh transmission conditions in narrow-band networks. Finally, the presented approach has impact on better resource allocation as fewer attempts are necessary for successful completion of a transmission. A significant part of the article deals with parameterization of coefficients used by the TOM optimization method. Examples of analysis for several topologies of narrow-band wireless networks based on CSMA/CA and TDMA protocols are used to demonstrate various issues related to proper setting of parameters. The introduced TOM metric has the potential to become a standard for optimization, for example, in sensor networks that are characterized by the specific nature of data traffic.

scholarly journals Interference Cancellation Based Spectrum Sharing for Massive MIMO Communication Systems

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3584
Author(s):  
Milembolo Miantezila Junior ◽  
Bin Guo ◽  
Chenjie Zhang ◽  
Xuemei Bai
Keyword(s):  
Interference Cancellation ◽  
Communication Systems ◽  
Spectrum Sharing ◽  
Null Space ◽  
Base Station ◽  
Base Stations ◽  
Small Cells ◽  
Data Traffic ◽  
New Approach ◽  
Lte Advanced

Cellular network operators are predicting an increase in space of more than 200 percent to carry the move and tremendous increase of total users in data traffic. The growing of investments in infrastructure such as a large number of small cells, particularly the technologies such as LTE-Advanced and 6G Technology, can assist in mitigating this challenge moderately. In this paper, we suggest a projection study in spectrum sharing of radar multi-input and multi-output, and mobile LTE multi-input multi-output communication systems near m base stations (BS). The radar multi-input multi-output and mobile LTE communication systems split different interference channels. The new approach based on radar projection signal detection has been proposed for free interference disturbance channel with radar multi-input multi-output and mobile LTE multi-input multi-output by using a new proposed interference cancellation algorithm. We chose the channel of interference with the best free channel, and the detected signal of radar was projected to null space. The goal is to remove all interferences from the radar multi-input multi-output and to cancel any disturbance sources from a chosen mobile Communication Base Station. The experimental results showed that the new approach performs very well and can optimize Spectrum Access.

Oosterweel – from an underground and even underwater road infrastructure plan to an urban transformation project

2021 ◽  
Author(s):  
Luc Hellemans
Keyword(s):  
Traffic Flow ◽  
Large Scale ◽  
Good Reason ◽  
Urban Transformation ◽  
Construction Site ◽  
Successful Completion ◽  
Road Infrastructure ◽  
Living Space ◽  
The City ◽  
Made In

<p>For the coming ten years, the heart of Europe will turn into a gigantic construction site for works on one of the largest hubs of the continent: Antwerp. The Oosterweel Link is the project whereby the motorway ring around Antwerp is undergoing a metamorphosis to reinvigorate traffic flow and add living space to the City. The project had come to a standstill for several years as a result of protests by assertive citizens, but was given a second lease of life following a large-scale participation project.</p><p>To ensure its successful completion, unparalleled efforts are being made in the field and in the area of digitization. It is therefore with good reason that in Belgium the project is referred to as “the construction site of the century”.</p>

Probabilistic Optimal Design Using Successive Surrogate Probability Density Functions

1990 ◽  
Author(s):  
R. J. Eggert ◽  
R. W. Mayne
Keyword(s):  
Probability Density ◽  
Optimization Method ◽  
Probability Density Functions ◽  
Density Functions ◽  
Matching Method ◽  
Design Constraint ◽  
New Approach ◽  
Function Formulation ◽  
The Moment ◽  
Theoretical Considerations

Abstract Probabilistic optimization using the moment matching method and the simulation optimization method are discussed and compared to conventional deterministic optimization. A new approach based on successively approximating probability density functions, using recursive quadratic programming for the optimization process, is described. This approach incorporates the speed and robustness of analytical probability density functions and improves accuracy by considering simulation results. Theoretical considerations and an example problem illustrate the features of the approach. The paper closes with a discussion of an objective function formulation which includes the expected cost of design constraint failure.

scholarly journals Wireless network optimization method based on cognitive cycle using machine learning

2018 ◽  
Vol 7 (7) ◽  
pp. 278-283 ◽  
Author(s):  
Koji Oshima ◽  
Takumu Kobayashi ◽  
Yuki Taenaka ◽  
Kaori Kuroda ◽  
Mikio Hasegawa
Keyword(s):  
Machine Learning ◽  
Wireless Network ◽  
Network Optimization ◽  
Optimization Method ◽  
Wireless Network Optimization

scholarly journals A New Approach for Allocating a New Party's Budget during an Election Campaign

PCD Journal ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 23-45
Author(s):  
Irit Talmor ◽  
Osnat Osnat Akirav
Keyword(s):  
Resource Allocation ◽  
Election Campaign ◽  
Pareto Principle ◽  
Election Campaigns ◽  
New Parties ◽  
New Approach ◽  
Confidential Data ◽  
User Friendly ◽  
Campaign Advertising

During pre-election campaigns, parties make great efforts to persuade constituents to vote for them. Usually, new parties have smaller budgets and fewer resources than veteran parties. Generally, the more heterogeneous the party’s electorate, the more critical the issue of resource allocation. This paper presents a method for new parties to efficiently allocate campaign advertising resources and maximise voters. The model developed uses the Pareto principle and multi-criteria approach, integrating the party’s confidential data together with official open-to-all data. We implemented the model on a specific new party during the intensive political period before the April 2019 elections in Israel, finding that the model produced clear and unbiased results, and this made it effective and user-friendly for strategy teams and campaign managers.

scholarly journals A Resource Allocation Algorithm for Ultra-Dense Networks Based on Deep Reinforcement Learning

2021 ◽  
Vol 16 (2) ◽  
Author(s):  
Huashuai Zhang ◽  
Tingmei Wang ◽  
Haiwei Shen
Keyword(s):  
Resource Allocation ◽  
Reinforcement Learning ◽  
Data Traffic ◽  
Wireless Data ◽  
Resource Allocation Algorithm ◽  
Allocation Algorithm ◽  
Q Learning ◽  
Dense Networks ◽  
Target Network ◽  
Wireless Resource Allocation

The resource optimization of ultra-dense networks (UDNs) is critical to meet the huge demand of users for wireless data traffic. But the mainstream optimization algorithms have many problems, such as the poor optimization effect, and high computing load. This paper puts forward a wireless resource allocation algorithm based on deep reinforcement learning (DRL), which aims to maximize the total throughput of the entire network and transform the resource allocation problem into a deep Q-learning process. To effectively allocate resources in UDNs, the DRL algorithm was introduced to improve the allocation efficiency of wireless resources; the authors adopted the resource allocation strategy of the deep Q-network (DQN), and employed empirical repetition and target network to overcome the instability and divergence of the results caused by the previous network state, and to solve the overestimation of the Q value. Simulation results show that the proposed algorithm can maximize the total throughput of the network, while making the network more energy-efficient and stable. Thus, it is very meaningful to introduce the DRL to the research of UDN resource allocation.

Modeling Traffic Flows with Fluid Flow Model

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Paulus Setiawan Suryadjaja ◽  
◽  
Maclaurin Hutagalung ◽  
Herman Yoseph Sutarto ◽  
◽  
...  
Keyword(s):  
Fluid Flow ◽  
Traffic Flow ◽  
Flow Model ◽  
Intelligent Transportation System ◽  
Macroscopic Model ◽  
Chain Process ◽  
Data Traffic ◽  
Flow Data ◽  
Order Markov Chain ◽  
Parameter Values

This Research presents a macroscopic model of traffic flow as the basis for making Intelligent Transportation System (ITS). The data used for modeling is The number of passing vehicles per three minutes. The traffic flow model created in The form of Fluid Flow Model (FFM). The parameters in The model are obtained by mixture Gaussian distribution approach. The distribution consists of two Gaussian distributions, each representing the mode of traffic flow. In The distribution, intermode shifting process is illustrated by the first-order Markov chain process. The parameters values are estimated using The Expectation-maximization (EM) algorithm. After The required parameter values are obtained, traffic flow is estimated using the Observation and transition-basedmost likely estimates Tracking Particle Filter (OTPF). To Examine the accuracy of the model has been made, the model estimation results are compared with the actual traffic flow data. Traffic flow data is collected on Monday 20 September 2017 at 06.00 to 10.00 on DipatiukurRoad, Bandung. The proposed model has accuracy with MAPE value below 10%, or falls into highly accurate categories

Image Enhancement with Improved Global and Local Visual Effects

2021 ◽  
Vol 01 ◽  
Author(s):  
Muhammad Adeel ◽  
Yinglei Song
Keyword(s):  
Objective Function ◽  
Image Enhancement ◽  
Optimization Technique ◽  
Optimization Method ◽  
Original Image ◽  
Visual Effects ◽  
Swarm Optimization ◽  
New Approach ◽  
Visual Contrast ◽  
Global And Local

Background: In many applications of image processing, the enhancement of images is often a step necessary for their preprocessing. In general, for an enhanced image, the visual contrast as a whole and its refined local details are both crucial for achieving accurate results for subsequent classification or analysis. Objective: This paper proposes a new approach for image enhancement such that the global and local visual effects of an enhanced image can both be significantly improved. Methods: The approach utilizes the normalized incomplete Beta transform to map pixel intensities from an original image to its enhanced one. An objective function that consists of two parts is optimized to determine the parameters in the transform. One part of the objective function reflects the global visual effects in the enhanced image and the other one evaluates the enhanced visual effects on the most important local details in the original image. The optimization of the objective function is performed with an optimization technique based on the particle swarm optimization method. Results: Experimental results show that the approach is suitable for the automatic enhancement of images. Conclusion: The proposed approach can significantly improve both the global and visual contrasts of the image.

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