scholarly journals Proposta de arcabouço experimental para rede de sensoriamento espectral usando rádio definido por software

2019 ◽  
Vol 1 (44) ◽  
pp. 88
Author(s):  
Yngrid Keila Silva Cabral ◽  
Paulo Ribeiro Lins Júnior ◽  
Jerônimo Silva Rocha
Keyword(s):  
Spectrum Sensing ◽  
Low Cost ◽  
Probability Of Detection ◽  
Free Software ◽  
Gnu Radio ◽  
Frequency Bands ◽  
Software Defined Radios

<p>This paper presents an architecture proposal for a spectrum sensing network using software defined radios. The radios responsible for the sensing are implemented with SDR-RTL, a low-cost radio, capable of receiving signals from several frequency bands, such as those used in FM, DAB and DVB-T. Sensing functions are implemented using GNU Radio, the most commonly used free software for configuring software-defined radios installed in Raspberry Pi’s, which makes the sensing structure significantly compact and inexpensive when compared to other solutions. Experiments are performed to measure the probability of detection in relation to the signal noiseratio, as a metric of the efficiency of the system proposed in this work</p>

scholarly journals New Omnidirectional Sensor Based on Open-Source Software and Hardware for Tracking and Backtracking of Dual-Axis Solar Trackers in Photovoltaic Plants

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 726
Author(s):  
Francisco J. Gómez-Uceda ◽  
José Ramirez-Faz ◽  
Marta Varo-Martinez ◽  
Luis Manuel Fernández-Ahumada
Keyword(s):  
Open Source Software ◽  
Energy Production ◽  
Scientific Community ◽  
Radiative Capture ◽  
Low Cost ◽  
Free Software ◽  
Solar Tracking ◽  
Software And Hardware ◽  
Celestial Sphere ◽  
Photovoltaic Plants

In this work, an omnidirectional sensor that enables identification of the direction of the celestial sphere with maximum solar irradiance is presented. The sensor, based on instantaneous measurements, functions as a position server for dual-axis solar trackers in photovoltaic plants. The proposed device has been developed with free software and hardware, which makes it a pioneering solution because it is open and accessible as well as capable of being improved by the scientific community, thereby contributing to the rapid advancement of technology. In addition, the device includes an algorithm developed ex professo that makes it possible to predetermine the regions of the celestial sphere for which, according to the geometric characteristics of the PV plant, there would be shading between the panels. In this way, solar trackers do not have to locate the Sun’s position at all times according to astronomical models, while taking into account factors such as shadows or cloudiness that also affect levels of incident irradiance on solar collectors. Therefore, with this device, it is possible to provide photovoltaic plants with dual-axis solar tracking with a low-cost device that helps to optimise the trajectory of the trackers and, consequently, their radiative capture and energy production.

scholarly journals Costs and Cost-Effectiveness of User-Testing of Health Professionals’ Guidelines to Reduce the Frequency of Intravenous Medicines Administration Errors by Nurses in the United Kingdom: A Probabilistic Model Based on Voriconazole Administration

2021 ◽  
Author(s):  
Matthew D. Jones ◽  
Bryony Dean Franklin ◽  
D. K. Raynor ◽  
Howard Thom ◽  
Margaret C. Watson ◽  
...  
Keyword(s):  
Cost Effectiveness ◽  
Medication Error ◽  
Low Cost ◽  
Cost Savings ◽  
Credible Interval ◽  
Probability Of Detection ◽  
Sensitivity Analyses ◽  
Decision Analytic Model ◽  
Published Data ◽  
User Testing

Abstract Aim In the UK, injectable medicines are often prepared and administered by nurses following the Injectable Medicines Guide (IMG). Our earlier study confirmed a higher frequency of correct administration with user-tested versus standard IMG guidelines. This current study aimed to model the cost-effectiveness of user-testing. Methods The costs and cost-effectiveness of user-testing were explored by modifying an existing probabilistic decision-analytic model. The adapted model considered administration of intravenous voriconazole to hospital inpatients by nurses. It included 11 error types, their probability of detection and level of harm. Model inputs (including costs) were derived from our previous study and other published data. Monte Carlo simulation using 20,000 samples (sufficient for convergence) was performed with a 5-year time horizon from the perspective of the 121 NHS trusts and health boards that use the IMG. Sensitivity analyses were undertaken for the risk of a medication error and other sources of uncertainty. Results The net monetary benefit at £20,000/quality-adjusted life year was £3,190,064 (95% credible interval (CrI): −346,709 to 8,480,665), favouring user-testing with a 96% chance of cost-effectiveness. Incremental cost-savings were £240,943 (95% CrI 43,527–491,576), also favouring user-tested guidelines with a 99% chance of cost-saving. The total user testing cost was £6317 (95% CrI 6012–6627). These findings were robust to assumptions about a range of input parameters, but greater uncertainty was seen with a lower medication error risk. Conclusions User-testing of injectable medicines guidelines is a low-cost intervention that is highly likely to be cost-effective, especially for high-risk medicines.

scholarly journals Optimization of spectrum sensing in cognitive radio using genetic algorithm

2012 ◽  
Vol 25 (3) ◽  
pp. 235-243 ◽  
Author(s):  
Rashmi Deka ◽  
Soma Chakraborty ◽  
Sekhar Roy
Keyword(s):  
Genetic Algorithm ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Rapid Development ◽  
Probability Of Detection ◽  
Radio System ◽  
Probability Of False Alarm ◽  
Space Allocation ◽  
Wireless Environment ◽  
Better Than

Spectrum availability is becoming scarce due to the rise of number of users and rapid development in wireless environment. Cognitive radio (CR) is an intelligent radio system which uses its in-built technology to use the vacant spectrum holes for the use of another service provider. In this paper, genetic algorithm (GA) is used for the best possible space allocation to cognitive radio in the spectrum available. For spectrum reuse, two criteria have to be fulfilled - 1) probability of detection has to be maximized, and 2) probability of false alarm should be minimized. It is found that with the help of genetic algorithm the optimized result is better than without using genetic algorithm. It is necessary that the secondary user should vacate the spectrum in use when licensed users are demanding and detecting the primary users accurately by the cognitive radio. Here, bit error rate (BER) is minimized for better spectrum sensing purpose using GA.

Efficient Wideband Spectrum Sensing Using Mems Acoustic Resonators

2022 ◽  
Vol 25 (3) ◽  
pp. 23-27
Author(s):  
Junfeng Junfeng Guan ◽  
Jitian Zhang ◽  
Ruochen Lu ◽  
Hyungjoo Seo ◽  
Jin Zhou ◽  
...  
Keyword(s):  
Spectrum Sensing ◽  
Spectrum Sharing ◽  
Dynamic Spectrum ◽  
Frequency Bands ◽  
Acoustic Resonators ◽  
Wireless Applications ◽  
Dynamic Spectrum Sharing ◽  
Wideband Spectrum Sensing ◽  
Broadband Radio ◽  
Increasing Demand

The ever-increasing demand for wireless applications has resulted in an unprecedented radio frequency (RF) spectrum shortage. Ironically, at the same time, actual utilization of the spectrum is sparse in practice [1]. To exploit previously underutilized frequency bands to accommodate new unlicensed applications and achieve highly efficient usage of the spectrum, the Federal Communications Committee (FCC) has repurposed many frequency bands for dynamic spectrum sharing. This includes the 6 GHz band to be shared between Wi-Fi 6 and the incumbent users [2] as well as the 3.5 GHz Citizens Broadband Radio Service (CBRS) band [3].

Multistage Spectrum Sensing for Cognitive Radio Using Energy and Maximum Eigenvalues Detection

2020 ◽  
Vol 11 (4) ◽  
pp. 41-59
Author(s):  
Faten Mashta ◽  
Mohieddin Wainakh ◽  
Wissam Altabban
Keyword(s):  
Cognitive Radio ◽  
Computational Complexity ◽  
Spectrum Sensing ◽  
Energy Detection ◽  
Probability Of Detection ◽  
Smoothing Factor ◽  
Third Stage ◽  
Simulation Results ◽  
Good Detection ◽  
High Computational Complexity

Spectrum sensing in cognitive radio has difficult and complex requirements such as requiring speed and sensing accuracy at very low SNRs. In this paper, the authors propose a novel fully blind sequential multistage spectrum sensing detector to overcome the limitations of single stage detector and make use of the advantages of each detector in each stage. In first stage, energy detection is used because of its simplicity. However, its performance decreases at low SNRs. In second and third stage, the maximum eigenvalues detector is adopted with different smoothing factor in each stage. Maximum eigenvalues detection technique provide good detection performance at low SNRs, but it requires a high computational complexity. In this technique, the probability of detection improves as the smoothing factor raises at the expense of increasing the computational complexity. The simulation results illustrate that the proposed detector has better sensing accuracy than the three individual detectors and a computational complexity lies in between the three individual complexities.

Distributed Spectrum Sensing Using Low Cost Hardware

2015 ◽  
Vol 83 (1) ◽  
pp. 5-17 ◽  
Author(s):  
Stefan Grönroos ◽  
Kristian Nybom ◽  
Jerker Björkqvist ◽  
Juhani Hallio ◽  
Jani Auranen ◽  
...  
Keyword(s):  
Spectrum Sensing ◽  
Low Cost ◽  
Distributed Spectrum Sensing

scholarly journals Reliable Machine Learning Based Spectrum Sensing in Cognitive Radio Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Hurmat Ali Shah ◽  
Insoo Koo
Keyword(s):  
Machine Learning ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Posterior Probability ◽  
Nearest Neighbor ◽  
Probability Of Detection ◽  
Fusion Center ◽  
Training Phase ◽  
K Nearest Neighbor ◽  
Combination Scheme

Spectrum sensing is of crucial importance in cognitive radio (CR) networks. In this paper, a reliable spectrum sensing scheme is proposed, which uses K-nearest neighbor, a machine learning algorithm. In the training phase, each CR user produces a sensing report under varying conditions and, based on a global decision, either transmits or stays silent. In the training phase the local decisions of CR users are combined through a majority voting at the fusion center and a global decision is returned to each CR user. A CR user transmits or stays silent according to the global decision and at each CR user the global decision is compared to the actual primary user activity, which is ascertained through an acknowledgment signal. In the training phase enough information about the surrounding environment, i.e., the activity of PU and the behavior of each CR to that activity, is gathered and sensing classes formed. In the classification phase, each CR user compares its current sensing report to existing sensing classes and distance vectors are calculated. Based on quantitative variables, the posterior probability of each sensing class is calculated and the sensing report is classified into either representing presence or absence of PU. The quantitative variables used for calculating the posterior probability are calculated through K-nearest neighbor algorithm. These local decisions are then combined at the fusion center using a novel decision combination scheme, which takes into account the reliability of each CR user. The CR users then transmit or stay silent according to the global decision. Simulation results show that our proposed scheme outperforms conventional spectrum sensing schemes, both in fading and in nonfading environments, where performance is evaluated using metrics such as the probability of detection, total probability of error, and the ability to exploit data transmission opportunities.

Mockup Investigation of Lightweight Timber Floor

2014 ◽  
Vol 899 ◽  
pp. 499-504
Author(s):  
Juraj Medveď ◽  
Bart Ingeleare ◽  
Lieven de Geetere
Keyword(s):  
Low Cost ◽  
Low Frequency ◽  
Sound Insulation ◽  
Light Weight ◽  
Test Results ◽  
Lightweight Construction ◽  
Frequency Bands ◽  
Timber Frame ◽  
Measurement And Analysis ◽  
The Impact

This paper dealt with measurement and analysis of different floor structures and their acoustic optimization towards the improvement of the impact sound insulation. Special attention goes to light weight timber frame constructions with taking in account the low frequency bands. The aim of the research is to create or design acoustic optimized lightweight floor constructions and mainly to find a good solution to achieve the best possible impact sound insulation for lightweight floors with the lowest possible thickness and low cost. Following contribution is first part of mentioned investigation and deal about test results on mockup lightweight construction.

scholarly journals DSP-based Mitigation of RF Front-end Non-linearity in Cognitive Wideband Receivers

Frequenz ◽  
2012 ◽  
Vol 66 (9-10) ◽  
Author(s):  
Michael Grimm ◽  
Rajesh K. Sharma ◽  
Matthias A. Hein ◽  
Reiner S. Thomä
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Communication Systems ◽  
Measurement Data ◽  
Digital Signal ◽  
Software Defined Radios ◽  
Front End ◽  
Non Linear ◽  
Rf Performance ◽  
Processing Techniques

AbstractSoftware defined radios are increasingly used in modern communication systems, especially in cognitive radio. Since this technology has been commercially available, more and more practical deployments are emerging and its challenges and realistic limitations are being revealed. One of the main problems is the RF performance of the front-end over a wide bandwidth.This paper presents an analysis and mitigation of RF impairments in wideband front-ends for software defined radios, focussing on non-linear distortions in the receiver. We discuss the effects of non-linear distortions upon spectrum sensing in cognitive radio and analyse the performance of a typical wideband software-defined receiver. Digital signal processing techniques are used to alleviate non-linear distortions in the baseband signal. A feed-forward mitigation algorithm with an adaptive filter is implemented and applied to real measurement data. The results obtained show that distortions can be suppressed significantly and thus increasing the reliability of spectrum sensing.

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