Comparison of D-Model and Wall-Attenuation Model for Signal Strength Estimations in Indoor Environment

2012 ◽  
Author(s):  
Shiraz Latif ◽  
Muhammad Ghazanfar ◽  
Aftab Memon ◽  
Bhawani Shankar Chowdhry ◽  
Javed Ahmed
Keyword(s):  
Indoor Environment ◽  
Signal Strength ◽  
Attenuation Model ◽  
D Model

scholarly journals A Research Cluster based Scheme for Node Positioning in Indoor Environment

2019 ◽  
Vol 8 (6S) ◽  
pp. 79-83
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Indoor Environment ◽  
Cluster Head ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Location Estimation ◽  
Wireless Sensor ◽  
Localization Error ◽  
Network Efficiency

Location estimation in Wireless Sensor Network (WSN) is mandatory to achieve high network efficiency. Identifying the positions of sensors is an uphill task as monitoring nodes are involved in estimation and localization. Clustered Positioning for Indoor Environment (CPIE) is proposed for estimating the position of the sensors using a Cluster Head (CH) based mechanism. The CH estimates the number of neighbor nodes in each floor of the indoor environment. It sends the requests to the cluster members and the positions are estimated based on the Received Signal Strength Indicators (RSSIs) from the members of the cluster. The performance of the proposed scheme is analyzed for both stable and mobile conditions by varying the number of floors. Experimental results show that the propounded scheme offers better network efficiency and reduces delay and localization error

Evaluation of Power Receiving Signal of 5G Small Cells for Outdoor/Indoor Environment at Millimeterwave Bands

2021 ◽  
Vol 36 (2) ◽  
pp. 184-189
Author(s):  
Nagham Hamid
Keyword(s):  
Indoor Environment ◽  
Angular Spectrum ◽  
Signal Strength ◽  
Base Station ◽  
Small Cells ◽  
International Telecommunication Union ◽  
International Telecommunication ◽  
3D Ray Tracing ◽  
Fixed Base ◽  
Building Characteristics

This paper presents a simulation study of the outdoor and indoor propagation losses utilizing 5G small cells at suggested millimeter-wave frequencies of 26 GHz, 28 GHz, and 38 GHz. The environment of this study is conducted with penetration loss of new and old building characteristics. The simulation is performed with help of 3D ray tracing model NVIDIA OptiX engine and MATLAB. The targeted frequencies are 26 GHz, 28 GHz, and 38 GHz that specified by International Telecommunication Union ITU-R organization. The simulation routes are investigated in term of signal strength at multiple receiving points. The strength angular spectrum are represented for fixed points and the power receiving delay is presented by their attributes. The simulated responses showed an efficient and sufficient outdoor and indoor service might be provisioned at 26 GHz and 28 GHz. The received signals at 28 GHz and 38 GHz are found around 4.5 dB and 11 dB with comparison with signal received level at 26 GHz. However, at 38 GHz the indoor signal strength and power receiving delays demonstrate a weak signal reception which offers a poor solution to indoor user by outside fixed base station.

A Method of Calculating Attenuation Factor Based on RFID

2013 ◽  
Vol 718-720 ◽  
pp. 1711-1716
Author(s):  
Ning Yang ◽  
Shao Shan Zhong ◽  
Hai Ting Zhu
Keyword(s):  
Indoor Environment ◽  
Attenuation Factor ◽  
Distance Measurement ◽  
Wireless Location ◽  
Attenuation Model ◽  
Location System ◽  
Measurement Mode ◽  
Reference Distance

As the indoor environment is complex,the attenuation model is imprecise.and the wireless location system is inaccurate.It is a effective method calculating attenuation factor with different distance RSSI data and selecting proper reference distance for solving single reference distance defect. The experiment verified that it can modify distance measurement mode and improve the accuracy and reliability of indoor distance measurement based on RFID.

scholarly journals Development of Attenuation Model for Saturated Water and Sedimentary Deposits for Underwater Acoustic Signal Communication

2019 ◽  
Vol 8 (6) ◽  
pp. 4374-4378
Keyword(s):  
Sodium Chloride ◽  
Acoustic Signal ◽  
Pure Water ◽  
Signal Strength ◽  
Raw Water ◽  
Underwater Acoustic ◽  
Attenuation Model ◽  
Sedimentary Deposits ◽  
Water Saturated ◽  
Underwater Acoustic Signal

In this paper, the model for absorption co-efficient for underwater tank is proposed for medium of raw water concentrated with sodium chloride. With course of time, sediments gets deposited at the bottom of tank. The attenuation model for underwater tank deposited with sediments is also developed. The attenuation models for pure water and sodium chloride are developed separately. The overall model for raw water saturated sodium chloride suitable for bounded shallow underwater medium like tanks. The resultant absorption co-efficient for pure water saturated with sodium chloride can be obtained by summation of the respective models and their percentage concentration. Similarly attenuation model for underwater tank having sedimentary deposits is also developed for various types of sedimentary deposits. For particular operating frequency of communicating devices placed in underwater tank, the absorption of underwater acoustic signal increases. The model reflects the change in attenuation loss as the length of sedimentary deposit increases. The underwater acoustic signal strength gets affected while its transmission in such mediums which can affect received signal strength. Also the length of sedimentary deposits can be related using attenuation model. These models helps to identify the increases concentration of sodium chloride and increases sedimentary deposits by analyzing the received signal strength

scholarly journals MOBILE ROBOT LOCALIZATION USING WLAN, ODOMETRY AND GYROSCOPE DATA

2010 ◽  
pp. 22-30
Author(s):  
Julian Lategahn ◽  
Frank Kuenemund ◽  
Christof Roehrig
Keyword(s):  
Kalman Filter ◽  
Mobile Robot ◽  
Sensor Fusion ◽  
Indoor Environment ◽  
Signal Strength ◽  
Office Building ◽  
Robot Localization ◽  
Mobile Robot Localization ◽  
Radio Map ◽  
Made In

In this paper a method for estimation of position and motion of a mobile robot in an indoor environment is introduced. The proposed method uses WLAN signal strength to estimate the global position of a mobile robot in an office building. Thus signal strengths of the received access points are stored in the radio map in calibration phase. In localization phase the stored values are compared with actually measured one’s. Therefore a fingerprinting algorithm, that was introduced before, is used. The improvement of the presented work is the multi sensor fusion using Kalman filter, which enhances the accuracy of fingerprinting algorithms and tracking of the robot. For this reason odometric and gyroscopic sensors of the robot are fused with the estimated position of the fingerprinting algorithm. The paper presents the experimental results of measurements made in an office building.

Improved Weighted Centroid Localization with Quadratic Means for Indoor Mobile Robot Tracking

2015 ◽  
Vol 781 ◽  
pp. 441-444
Author(s):  
Jirapat Sangthong ◽  
Kantaphon Torat ◽  
Sathaporn Promwong
Keyword(s):  
Mobile Robot ◽  
Indoor Environment ◽  
Signal Strength ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Indoor Mobile Robot ◽  
Robot Tracking ◽  
Weighted Centroid Localization ◽  
The One ◽  
Range Free

Nowadays, mobile robot tracking is the one of application in wireless sensor networks (WSNs). A one of promising localization algorithm in range-free algorithm is the weighted centroid localization (WCL) algorithm. This work proposed the improved WCL algorithm with quadratic means based on received signal strength (RSS). The ZigBee operated at 2.4 GHz frequency is used to measure in the indoor environment. The final results will be discuss about the comparison of the typically WCL algorithm and the improved WCL algorithm. From the results, the 1-meter-precision of improved WCL is 91.67% and WCL is 83.33%. Moreover, the improved WCL obtained the 16.67% no error of estimated position.

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