scholarly journals Factorial Design Analysis for Localization Algorithms

2018 ◽  
Vol 8 (12) ◽  
pp. 2654
Author(s):  
Joaquin Mass-Sanchez ◽  
Erica Ruiz-Ibarra ◽  
Ana Gonzalez-Sanchez ◽  
Adolfo Espinoza-Ruiz ◽  
Joaquin Cortez-Gonzalez

Localization is a fundamental problem in Wireless Sensor Networks, as it provides useful information regarding the detection of an event. There are different localization algorithms applied in single-hop or multi-hop networks; in both cases their performance depends on several factors involved in the evaluation scenario such as node density, the number of reference nodes and the log-normal shadowing propagation model, determined by the path-loss exponent (η) and the noise level (σdB) which impact on the accuracy and precision performance metrics of localization techniques. In this paper, we present a statistical analysis based on the 2k factorial methodology to determine the key factors affecting the performance metrics of localization techniques in a single-hop network to concentrate on such parameters, thus reducing the amount of simulation time required. For this proposal, MATLAB simulations are carried out in different scenarios, i.e., extreme values are used for each of the factors of interest and the impact of the interaction among them in the performance metrics is observed. The simulation results show that the path-loss exponent (η) and noise level (σdB) factors have the greatest impact on the accuracy and precision metrics evaluated in this study. Based on this statistical analysis, we recommend estimating the propagation model as close to reality as possible to consider it in the design of new localization techniques and thus improve their accuracy and precision metrics.

2021 ◽  
Vol 9 (03) ◽  
pp. 72-79
Author(s):  
Akohoule Alex ◽  
◽  
Bamba Aliou ◽  
Kamagate Aladji ◽  
Konate Adama ◽  
...  

In wireless networks, propagation models are used to assess the received power signal and estimate the propagation channel. These models depend on the pathloss exponent (PLE) which is one of the main parameters to characterize the propagation environment. Indeed, in the wireless channel, the path loss exponent has a strong impact on the quality of the links and must therefore be estimated with precision for an efficient design and operation of the wireless network. This paper addresses the issue of path loss exponents estimation for mobile networks in four outdoor environments. This study is based on measurements carried out in four outdoor environments at the frequency of 2600 MHz within a bandwidth of 70 MHz. It evaluates the path loss exponent, and the impact of obstacles present in the environments. The parameters of the propagation model determined from the measurements show that the average power of the received signal decreases logarithmically with the distance. We obtained path loss exponents values of 4.8, 3.53, 3.6 and 3.99 for the site 1, site 2, site 3 and site 4, respectively. Clearly the density of the obstacles has an impact on the path loss exponents and our study shows that the received signal decrease faster as the transmitter and receiver separation in the dense environments.


Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6582
Author(s):  
SeYoung Kang ◽  
TaeHyun Kim ◽  
WonZoo Chung

We present a novel hybrid localization algorithm for wireless sensor networks in the absence of knowledge regarding the transmit power and path-loss exponent. Transmit power and the path-loss exponent are critical parameters for target localization algorithms in wireless sensor networks, which help extract target position information from the received signal strength. In the absence of information on transmit power and path-loss exponent, it is critical to estimate them for reliable deployment of conventional target localization algorithms. In this paper, we propose a simultaneous estimation of transmit power and path-loss exponent based on Kalman filter. The unknown transmit power and path-loss exponent are estimated using a Kalman filter with the tentatively estimated target position based solely on angle information. Subsequently, the target position is refined using a hybrid method incorporating received signal strength measurements based on the estimated transmit power and path-loss exponent. Our proposed algorithm accurately estimates transmit power and path-loss exponent and yields almost the same target position accuracy as the simulation results confirm, as the hybrid target localization algorithms with known transmit power and path-loss exponent. Simulation results confirm the proposed algorithm achieves 99.7% accuracy of the target localization performance with known transmit power and path-loss exponent, even in the presence of severe received signal strength measurement noise.


2011 ◽  
Vol 474-476 ◽  
pp. 2161-2166 ◽  
Author(s):  
Jia Zhang ◽  
Hai Yan Zhang ◽  
Jin Na Lv ◽  
Li Qiang Yin

Localization is a vital foundation work in Wireless Sensor Network (WSN). Almost all of location algorithms at present need the position information of reference nodes to locate the unknown nodes. But most of algorithms assume an idealistic radio propagation model that is far from the reality. This will lead to obvious difference compared with real localization of WSN. In this paper we investigate the impact of radio irregularity on the localization algorithms performance in WSN. We introduce the Radio Irregularity Model (RIM) which is established upon empirical data. With this model, this paper analyzes the impact of radio irregularity on localization algorithms. We compare three typical coarse-grained localization algorithms: APIT, Centroid and DV-HOP in simulated realistic settings. Our experimental results show that radio irregularity has a significant impact on some main evaluation aspects of localization algorithms. Some interesting phenomena is worthy of further study.


Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1934
Author(s):  
Piotr Wojcicki ◽  
Tomasz Zientarski ◽  
Malgorzata Charytanowicz ◽  
Edyta Lukasik

Regarding wireless sensor network parameter estimation of the propagation model is a most important issue. Variations of the received signal strength indicator (RSSI) parameter are a fundamental problem of a system based on signal strength. In the present paper, we propose an algorithm based on Bayesian filtering techniques for estimating the path-loss exponent of the log-normal shadowing propagation model for outdoor RSSI measurements. Furthermore, in a series of experiments, we will demonstrate the usefulness of the particle filter for estimating the RSSI data. The stability of this algorithm and the differences in determined path-loss exponent for both method were also analysed. The proposed method of dynamic estimation results in significant improvements of the accuracy of RSSI values when compared with the experimental measurements. It should be emphasised that the path-loss exponent mainly depends on the RSSI data. Our results also indicate that increasing the number of inserted particles does not significantly raise the quality of the estimated parameters.


2020 ◽  
Vol 9 (1) ◽  
pp. 12 ◽  
Author(s):  
José Vallet García

Using the classical received signal strength (RSS)-distance log-normal model in wireless sensor network (WSN) applications poses a series of characteristic challenges derived from (a) the model’s structural limitations when it comes to explaining real observations, (b) the inherent hardware (HW) variability typically encountered in the low-cost nodes of WSNs, and (c) the inhomogeneity of the deployment environment. The main goal of this article is to better characterize how these factors impact the model parameters, an issue that has received little attention in the literature. For that matter, I qualitatively elaborate on their effects and interplay, and present the results of two quantitative empirical studies showing how much the parameters can vary depending on (a) the nodes used in the model identification and their position in the environment, and (b) the antenna directionality. I further show that the path loss exponent and the reference power can be highly correlated. In view of all this, I argue that real WSN deployments are better represented by random model parameters jointly accounting for HW and local environmental characteristics, rather than by deterministic independent ones. I further argue that taking this variability into account results in more realistic models and plausible results derived from their usage. The article contains example values of the mean and standard deviation of the model parameters, and of the correlation between the path loss exponent and the reference power. These can be used as a guideline in other studies. Given the sensitivity of localization algorithms to the proper model selection and identification demonstrated in the literature, the structural limitations of the log-normal model, the variability of its parameters and their interrelation are all relevant aspects that practitioners need to be aware of when devising optimal localization algorithms for real WSNs that rely on this popular model.


Author(s):  
Altaf Hussain ◽  
Tariq Hussain ◽  
Iqtidar Ali ◽  
Muhammad Rafiq Khan

Mobile Ad-hoc Network (MANET) is the most emerging and fast-expanding technology in the last two decades. One of the major issues and challenging areas in MANET is the process of routing due to dynamic topologies and high mobility of mobile nodes. The efficiency and accuracy of a protocol depend on many parameters in these networks. In addition to other parameters node velocity and propagation models are among them. Calculating signal strength at the receiver is the responsibility of a propagation model while the mobility of nodes is responsible for the topology of the network. A huge amount of loss in performance is occurred due to the variation of signal strength at the receiver and obstacles between transmissions. In this paper,it has been analyzed to check the impact of different propagation models on the performance of Optimized Link State Routing (OLSR) in Sparse and Dense scenarios in MANET. The simulation has been carried out in NS-2 by using performance metrics as average packet drop average latency and average Throughput. The results predicted that propagation models and mobility have a strong impact on the performance of OLSR in considered scenarios. 


2021 ◽  
Vol 18 (4(Suppl.)) ◽  
pp. 1378
Author(s):  
Azita Laily Yusof ◽  
Hafizi Halim ◽  
Norsuzila Ya'acob ◽  
Nur Haidah Mohd Hanapiah

The main challenge of military tactical communication systems is the accessibility of relevant information on the particular operating environment required for the determination of the waveform's ideal use. The existing propagation model focuses mainly on broadcasting and commercial wireless communication with a highs transceiver antenna that is not suitable for numerous military tactical communication systems. This paper presents a study of the path loss model related to radio propagation profile within the suburban in Kuala Lumpur. The experimental path loss modeling for VHF propagation was collected from various suburban settings for the 30-88 MHz frequency range. This experiment was highly affected by ecological factors and existing wave propagation effects such as reflection, diffraction, scattering, and Doppler effect. Radio propagation performance is evaluated by collecting received power at the allocated substation and comparing it against existing propagation models. The existing propagation model also will be tuned close to the measurement value by identifying the best path loss exponent to perform a suitable model for a suburban area. Theoretical assessments and analysis of the initial measurement stage for radio propagation show the extensive contribution of radio field from potential obstacles at lower VHF frequencies for both short and medium ranges around there. The explanation indicates the standard radio propagation prediction models that are generally reasonable for the suburban area. From the general error analysis, it is seen that, the performance of the LDPL with adjusting path loss exponent is the suitable model since it has least value of error metrics.


Ekonomika ◽  
2015 ◽  
Vol 94 (1) ◽  
pp. 143-156
Author(s):  
Ewelina Sokołowska ◽  
Jerzy Wiśniewski

The financial viability of small companies depends on their ability to meet sales demands and collect receivables from the sales of goods and provision of services. The efficiency of debt recovery plays the fundamental role in determining the liquidity of a small business. Shortages of cash in the company are rarely subsidised not from external sources but most often from the owner’s own funds that such shortages are made up, including the amounts previously accumulated as a result of the so-called excess liquidity. The main purpose of the article is the hypothesis that application of statistical analysis in liquidity management can be a useful tool in effective debt collection in an enterprise.We looked at the monthly or short-term liquidity of a small business and its impact on the defined performance metrics of debt collection. The analytical tool is a dynamic econometric model that describes the impact of the efficiency of recovery for liquidity in small business.


Author(s):  
Igor Ponomarenko ◽  
Kateryna Volovnenko

The subject of the research is a set of approaches to the statistical analysis ofthe activities of small business entities in Ukraine, including micro-enterprises. The purpose of writing this article is to study of the features of functioningof small business entities in Ukraine. Methodology. The research methodology isto use a system-structural and comparative analysis (to study the change in thenumber of small enterprises by major components); monographic (when studyingmethods of statistical analysis of small businesses); economic analysis (when assessing the impact of small business entities on socio-economic phenomena andprocesses in Ukraine). The scientific novelty consists to determine the features ofthe functioning of small businesses in Ukraine in modern conditions. The influenceof the activities of the main socio-economic and political indicators on the activities of small enterprises in recent periods of time has been identified. It has beenestablished that there is flexibility in the development of strategies by small businesses in conditions of significant competition, which makes it possible to quicklyrespond to changing situations in specific markets. Conclusions. The use of acomprehensive statistical analysis of small businesses functioning in Ukraine willallow government agencies to develop a set of measures to optimize the activitiesof these enterprises, which ultimately will positively affect the strengthening oftheir competitiveness and will contribute to the growth of the national economicsystem.


2020 ◽  
Vol 60 (2) ◽  
pp. 182-193
Author(s):  
Kacem Abdelhadi ◽  
Houar Abdelatif ◽  
Zerf Mohamed ◽  
Bengoua Ali

SummaryThis study tests the impact of COVID-19 on sleep of Algerian population before and during the COVID-19 quarantine by an estimated online survey, adapted from the PSQI Italian version. Including 1210 participants (age between 18-60 years old). The statistical analysis was carried out using SPSS version 22.0 software. Our results showed a significant change in sleeping quality during quarantine, the sleep timing markedly changed, we also noticed additional use of sleeping medications. Algerian scientists recommend to build public awareness and to provide necessary information regarding Algerian sleep quality, especially for Algerian adults.


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