scholarly journals Energy-Efficient UAV Trajectory Design with Information Freshness Constraint via Deep Reinforcement Learning

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xinmin Li ◽  
Jiahui Li ◽  
Dandan Liu
Keyword(s):  
Energy Efficiency ◽  
Optimization Problem ◽  
Dynamic Environment ◽  
Training Data ◽  
Base Stations ◽  
Trajectory Design ◽  
Rest Energy ◽  
Reward Function ◽  
Experience Replay ◽  
The Individual

Unmanned aerial vehicle (UAV) technique with flexible deployment has enabled the development of Internet of Things (IoT) applications. However, it is difficult to guarantee the freshness of information delivery for the energy-limited UAV. Thus, we study the trajectory design in the multiple-UAV communication system, in which the massive ground devices send the individual information to mobile UAV base stations under the demand of information freshness. First, an energy-efficiency (EE) maximization optimization problem is formulated under the rest energy, safety distance, and age of information (AoI) constraints. However, it is difficult to solve the optimization problem due to the nonconvex objective function and unknown dynamic environment. Second, a trajectory design based on the deep Q-network method is proposed, in which the state space considering energy efficiency, rest energy, and AoI and the efficient reward function related with EE performance are constructed, respectively. Furthermore, to avoid the dependency of training data for the neural network, the experience replay and random sampling for batch are adopted. Finally, we validate the system performance of the proposed scheme. Simulation results show that the proposed scheme can achieve a better EE performance compared with the benchmark scheme.

scholarly journals Clustering and Auction-Based Power Allocation Algorithm for Energy Efficiency Maximization in Multi-Cell Multi-Carrier NOMA Networks

2019 ◽  
Vol 9 (23) ◽  
pp. 5034 ◽  
Author(s):  
Abuzar B. M. Adam ◽  
Xiaoyu Wan ◽  
Zhengqiang Wang
Keyword(s):  
Energy Efficiency ◽  
Power Allocation ◽  
Cooperative Game ◽  
Multiple Access ◽  
Optimization Problem ◽  
Interference Mitigation ◽  
Base Stations ◽  
Frequency Division ◽  
Simulation Results ◽  
Inter Cell Interference

In this paper, we investigate the energy efficiency (EE) maximization in multi-cell multi-carrier non-orthogonal multiple access (MCMC-NOMA) networks. To achieve this goal, an optimization problem is formulated then the solution is divided into two parts. First, we investigate the inter-cell interference mitigation and then we propose an auction-based non-cooperative game for power allocation for base stations. Finally, to guarantee the rate requirements for users, power is allocated fairly to users. The simulation results show that the proposed scheme has the best performance compared with the existing NOMA-based fractional transmit power allocation (FTPA) and the conventional orthogonal frequency division multiple access (OFDMA).

scholarly journals An Optimal Joint User Association and Power Allocation Algorithm for Secrecy Information Transmission in Heterogeneous Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Rong Chai ◽  
Mingxue Chen ◽  
Qianbin Chen ◽  
Yuanpeng Gao
Keyword(s):  
Energy Efficiency ◽  
Information Transmission ◽  
Power Allocation ◽  
Heterogeneous Networks ◽  
Optimization Problem ◽  
Transmission Rate ◽  
Rapid Development ◽  
Base Stations ◽  
User Association ◽  
Efficient Manner

In recent years, heterogeneous radio access technologies have experienced rapid development and gradually achieved effective coordination and integration, resulting in heterogeneous networks (HetNets). In this paper, we consider the downlink secure transmission of HetNets where the information transmission from base stations (BSs) to legitimate users is subject to the interception of eavesdroppers. In particular, we stress the problem of joint user association and power allocation of the BSs. To achieve data transmission in a secure and energy efficient manner, we introduce the concept of secrecy energy efficiency which is defined as the ratio of the secrecy transmission rate and power consumption of the BSs and formulate the problem of joint user association and power allocation as an optimization problem which maximizes the joint secrecy energy efficiency of all the BSs under the power constraint of the BSs and the minimum data rate constraint of user equipment (UE). By equivalently transforming the optimization problem into two subproblems, that is, power allocation subproblem and user association subproblem of the BSs, and applying iterative method and Kuhn-Munkres (K-M) algorithm to solve the two subproblems, respectively, the optimal user association and power allocation strategies can be obtained. Numerical results demonstrate that the proposed algorithm outperforms previously proposed algorithms.

An Efficient Distributed Single-hop Relay Supporting (EDSRS) MAC Protocol for Wireless Sensor Networks

2019 ◽  
Vol 9 (2) ◽  
pp. 153-164
Author(s):  
Arvind Kakria ◽  
Trilok Chand Aseri
Keyword(s):  
Energy Efficiency ◽  
Cooperative Communication ◽  
Mimo Systems ◽  
Mac Protocol ◽  
Multiple Input Multiple Output ◽  
Relay Node ◽  
Base Stations ◽  
Destination Node ◽  
Distributed Coordination ◽  
Hardware Complexity

Background & Objective: Wireless communication has immensely grown during the past few decades due to significant demand for mobile access. Although cost-effective as compared to their wired counterpart, maintaining good quality-of-service (QoS) in these networks has always remained a challenge. Multiple-input Multiple-output (MIMO) systems, which consists of multiple transmitter and receiver antennas, have been widely acknowledged for their QoS and transmit diversity. Though suited for cellular base stations, MIMO systems are not suited for small-sized wireless nodes due to their hardware complexity, cost, and increased power requirements. Cooperative communication that allows relays, i.e. mobile or fixed nodes in a communication network, to share their resources and forward other node’s data to the destination node has substituted the MIMO systems nowadays. To harness the full benefit of cooperative communication, appropriate relay node selection is very important. This paper presents an efficient single-hop distributed relay supporting medium access control (MAC) protocol (EDSRS) that works in the single-hop environment and improves the energy efficiency and the life of relay nodes without compensating the throughput of the network. Methods: The protocol has been simulated using NS2 simulator. The proposed protocol is compared with energy efficient cooperative MAC protocol (EECOMAC) and legacy distributed coordination function (DCF) on the basis of throughput, energy efficiency, transmission delay and an end to end delay with various payload sizes. Result and Conclusion: The result of the comparison indicates that the proposed protocol (EDSRS) outperforms the other two protocols.

scholarly journals Inverse reinforcement learning in contextual MDPs

2021 ◽  
Author(s):  
Stav Belogolovsky ◽  
Philip Korsunsky ◽  
Shie Mannor ◽  
Chen Tessler ◽  
Tom Zahavy
Keyword(s):  
Reinforcement Learning ◽  
Optimization Problem ◽  
Decision Processes ◽  
Inverse Reinforcement Learning ◽  
Convex Optimization Problem ◽  
Reward Function ◽  
Dynamic Treatment Regime ◽  
Markov Decision ◽  
Dynamic Treatment ◽  
Recorded Data

AbstractWe consider the task of Inverse Reinforcement Learning in Contextual Markov Decision Processes (MDPs). In this setting, contexts, which define the reward and transition kernel, are sampled from a distribution. In addition, although the reward is a function of the context, it is not provided to the agent. Instead, the agent observes demonstrations from an optimal policy. The goal is to learn the reward mapping, such that the agent will act optimally even when encountering previously unseen contexts, also known as zero-shot transfer. We formulate this problem as a non-differential convex optimization problem and propose a novel algorithm to compute its subgradients. Based on this scheme, we analyze several methods both theoretically, where we compare the sample complexity and scalability, and empirically. Most importantly, we show both theoretically and empirically that our algorithms perform zero-shot transfer (generalize to new and unseen contexts). Specifically, we present empirical experiments in a dynamic treatment regime, where the goal is to learn a reward function which explains the behavior of expert physicians based on recorded data of them treating patients diagnosed with sepsis.

Powder Spheroidization Using Induction Plasma Technology

2000 ◽  
Author(s):  
N.M. Dignard ◽  
M.I. Boulos
Keyword(s):  
Energy Efficiency ◽  
Maximum Energy ◽  
Operating Conditions ◽  
Side Reactions ◽  
Induction Plasma ◽  
Silica Alumina ◽  
Change In The Mean ◽  
The Individual ◽  
Semi Empirical ◽  
Objective Being

Abstract An experimental study of the spheroidization efficiency of induction plasma processes was completed. The main objective being to obtain models which could be subsequently used for the prediction of the spheroidization efficiency for various powders and plasma operating conditions. Silica, alumina, chromium oxide and zirconia powders were treated during the experimentation. For the plasma treatment of the powders the installation used had a maximum available power of 50 kW with an operating frequency of 3 MHz. Operating conditions were varied such to minimize side reactions and the evaporation of powders. The resulting powders did show the presence of cavities and a slight change in the mean diameters. The maximum energy efficiency based semi-empirical model did predict the spheroidization efficiency of the particles beyond a defined critical point known as the maximum energy efficiency point. For the model, the maximum energy efficiency is distinct for the individual powders but remain within a defined range which is reflected in the small variations in the Z constant.

scholarly journals Renewable Energy Sharing Among Base Stations as a Min-Cost-Max-Flow Optimization Problem

2019 ◽  
Vol 3 (1) ◽  
pp. 67-78 ◽  
Author(s):  
Doris Benda ◽  
Xiaoli Chu ◽  
Sumei Sun ◽  
Tony Q. S. Quek ◽  
Alastair Buckley
Keyword(s):  
Renewable Energy ◽  
Optimization Problem ◽  
Base Stations ◽  
Flow Optimization ◽  
Energy Sharing

scholarly journals Holdout-Based Empirical Assessment of Mixed-Type Synthetic Data

2021 ◽  
Vol 4 ◽  
Author(s):  
Michael Platzer ◽  
Thomas Reutterer
Keyword(s):  
Mixed Type ◽  
Synthetic Data ◽  
Training Data ◽  
Privacy Risk ◽  
Individual Level ◽  
Empirical Assessment ◽  
Model Free ◽  
Private Data ◽  
Synthetic Datasets ◽  
The Individual

AI-based data synthesis has seen rapid progress over the last several years and is increasingly recognized for its promise to enable privacy-respecting high-fidelity data sharing. This is reflected by the growing availability of both commercial and open-sourced software solutions for synthesizing private data. However, despite these recent advances, adequately evaluating the quality of generated synthetic datasets is still an open challenge. We aim to close this gap and introduce a novel holdout-based empirical assessment framework for quantifying the fidelity as well as the privacy risk of synthetic data solutions for mixed-type tabular data. Measuring fidelity is based on statistical distances of lower-dimensional marginal distributions, which provide a model-free and easy-to-communicate empirical metric for the representativeness of a synthetic dataset. Privacy risk is assessed by calculating the individual-level distances to closest record with respect to the training data. By showing that the synthetic samples are just as close to the training as to the holdout data, we yield strong evidence that the synthesizer indeed learned to generalize patterns and is independent of individual training records. We empirically demonstrate the presented framework for seven distinct synthetic data solutions across four mixed-type datasets and compare these then to traditional data perturbation techniques. Both a Python-based implementation of the proposed metrics and the demonstration study setup is made available open-source. The results highlight the need to systematically assess the fidelity just as well as the privacy of these emerging class of synthetic data generators.

scholarly journals On development of a technique for estimating structural dynamics and strength of modular phased array

2017 ◽  
pp. 75-82
Author(s):  
V. G. Lisovskiy ◽  
E. N. Khmelnitskiy ◽  
A. V. Kuzmicheva
Keyword(s):  
Structural Dynamics ◽  
Phased Array ◽  
Phased Arrays ◽  
Dynamic Environment ◽  
Vibration Acceleration ◽  
Transmission Coefficients ◽  
Mechanical Factors ◽  
Strain Stress ◽  
The Individual ◽  
Stiffening Effect

The purpose of the study was to develop a method of computational and experimental analysis to reduce the dimension of the problem, which makes it possible to simplify and accelerate the strength calculations. When using the method, one can take into account the stiffening effect of the carrier object, where the product will be installed, determine the transmission coefficients of vibration acceleration from the base of the structure to the individual units of the equipment to assess their strength and stability under the influence of mechanical factors. Moreover, the method allows for the strain-stress state analysis using the dynamic environment coefficients. Currently, the developed method is used in the design of several promising projects using modular phased arrays, both sea and land-based

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