scholarly journals Path Loss Measurement and Channel Modeling with Muscular Tissue Characteristics

2017 ◽  
Vol 11 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Yu-Ping Qin ◽  
Shuang Zhang ◽  
Hai-Yan Liu ◽  
Yi-He Liu ◽  
You-Zhi Li ◽  
...  
Keyword(s):  
Communication Channel ◽  
Path Loss ◽  
Channel Modeling ◽  
Maximum Error ◽  
Sine Wave ◽  
Muscular Fibre ◽  
Muscular Tissue ◽  
Experimental Sample ◽  
Galvanic Coupling ◽  
Communication Distance

Background: The galvanic coupling intra-body communication has low radiation and strong anti-interference ability, so it has many advantages in the wireless communication. Method: In order to analyze the effect of muscle tissue’s characteristics upon the communication channel, we selected the muscle of pig buttock as the experimental sample, and used it to study the attenuation property with the galvanic coupling intra-body communication channel along the parallel direction and the transverse direction relative to the muscular fibre line as well as on the surface of destroyed muscular fibre; the study frequency ranges from 1kHz to 10MHz.In the isotropic experiment, in order to destroy muscle’s fibre characteristics, we grinded the muscle four times, at least five minutes for each time. 0dbm sine-wave signal was input to measure the channel attenuation parameter S21 when the transmitter and the receiver were placed at different positions and different distances d1 and d2 (20mm, 40mm, 60mm), so as to analyze channel loss. Conclusion: Within the same frequency range and at the same communication distance, the maximum error of channel attenuation was 10dB; within the same frequency, as the communication distance was increased, the channel attenuation rose gradually, with 4dB increased every 20mm. The conclusion provides the basis for building the theoretical model in the future.

scholarly journals Mathematical Model of Human Forearm Based Muscle Fiber Tissues’ Anisotropic Characteristics

2016 ◽  
Vol 10 (1) ◽  
pp. 234-238 ◽  
Author(s):  
Yu-Ping Qin ◽  
Shuang Zhang ◽  
Yi-he Liu
Keyword(s):  
Mathematical Model ◽  
Muscle Fiber ◽  
Communication Channel ◽  
Human Muscle ◽  
Transmission Mechanism ◽  
Muscular Tissue ◽  
Electrical Characteristics ◽  
Galvanic Coupling ◽  
Communication Signals ◽  
Human Forearm

On the basis of human muscle fiber tissues' characteristics, it is first proposed to establish the analytical model of galvanic coupling intra-body communication channel. In this model, the parallel and the transverse electrical characteristics of muscular tissue are fully considered, and the model accurately presents the transmission mechanism of galvanic coupling intra-body communication signals in the channel.

scholarly journals Joint UAV channel modeling and power control for 5G IoT networks

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Xiuhua Fu ◽  
Tian Ding ◽  
Rongqun Peng ◽  
Cong Liu ◽  
Mohamed Cheriet
Keyword(s):  
Energy Efficiency ◽  
Power Control ◽  
Channel Model ◽  
Path Loss ◽  
Channel Modeling ◽  
Signal Propagation ◽  
Spectrum Efficiency ◽  
Propagation Path ◽  
Control Factor ◽  
The Impact

AbstractThis paper studies the communication problem between UAVs and cellular base stations in a 5G IoT scenario where multiple UAVs work together. We are dedicated to the uplink channel modeling and the performance analysis of the uplink transmission. In the channel model, we consider the impact of 3D distance and multi-UAVs reflection on wireless signal propagation. The 3D distance is used to calculate the path loss, which can better reflect the actual path loss. The power control factor is used to adjust the UAV's uplink transmit power to compensate for different propagation path losses, so as to achieve precise power control. This paper proposes a binary exponential power control algorithm suitable for 5G networked UAV transmitters and presents the entire power control process including the open-loop phase and the closed-loop phase. The effects of power control factors on coverage probability, spectrum efficiency and energy efficiency under different 3D distances are simulated and analyzed. The results show that the optimal power control factor can be found from the point of view of energy efficiency.

scholarly journals Application of Computational Intelligence Algorithms in Radio Propagation: A Systematic Review and Metadata Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Quadri Ramon Adebowale ◽  
Nasir Faruk ◽  
Kayode S. Adewole ◽  
Abubakar Abdulkarim ◽  
Lukman A. Olawoyin ◽  
...  
Keyword(s):  
Computational Intelligence ◽  
Path Loss ◽  
Channel Modeling ◽  
Radio Propagation ◽  
Future Research ◽  
Computational Techniques ◽  
Research Issues ◽  
Main Research ◽  
Loss Prediction ◽  
Path Loss Prediction

The importance of wireless path loss prediction and interference minimization studies in various environments cannot be over-emphasized. In fact, numerous researchers have done massive work on scrutinizing the effectiveness of existing path loss models for channel modeling. The difficulties experienced by the researchers determining or having the detailed information about the propagating environment prompted for the use of computational intelligence (CI) methods in the prediction of path loss. This paper presents a comprehensive and systematic literature review on the application of nature-inspired computational approaches in radio propagation analysis. In particular, we cover artificial neural networks (ANNs), fuzzy inference systems (FISs), swarm intelligence (SI), and other computational techniques. The main research trends and a general overview of the different research areas, open research issues, and future research directions are also presented in this paper. This review paper will serve as reference material for researchers in the field of channel modeling or radio propagation and in particular for research in path loss prediction.

A Generic Method for the Reliable Calculation of Large-Scale Fading in an Obstacle-Dense Propagation Environment

2013 ◽  
pp. 256-277
Author(s):  
Theofilos Chrysikos ◽  
Stavros Kotsopoulos ◽  
Eduard Babulak
Keyword(s):  
Large Scale ◽  
Path Loss ◽  
Signal Strength ◽  
Channel Modeling ◽  
Wireless Channel ◽  
Mathematical Tool ◽  
Shadow Fading ◽  
Estimation Model ◽  
Statistical Parameters ◽  
Wireless Channel Modeling

The aim of this chapter is to summarize and present recent findings in the field of wireless channel modeling that provide a new method for the reliable calculation of the statistical parameters of large-scale variations of the average received signal (shadow fading). This algorithm is theoretically based on a path loss estimation model that incorporates losses due to walls and floors. This has been confirmed to be the most precise mathematical tool for average signal strength prediction for various frequencies of interest and propagation environments. The total path loss is estimated as a sum of two independent attenuation processes: free space loss and losses due to obstacles. This solution allows for a direct and reliable calculation of the deviation of the fluctuations of the average received signal in an obstacle-dense environment.

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