Mobile 4G Network: Signal Power and Quality vs Bandwidth Throughput

2021 ◽  
pp. 341-352
Author(s):  
Luis Oliveira ◽  
Joao Henriques ◽  
Ivan Miguel Pires ◽  
Cristina Wanzeller ◽  
Filipe Caldeira
Keyword(s):  
Author(s):  
D. Van Dyck

An (electron) microscope can be considered as a communication channel that transfers structural information between an object and an observer. In electron microscopy this information is carried by electrons. According to the theory of Shannon the maximal information rate (or capacity) of a communication channel is given by C = B log2 (1 + S/N) bits/sec., where B is the band width, and S and N the average signal power, respectively noise power at the output. We will now apply to study the information transfer in an electron microscope. For simplicity we will assume the object and the image to be onedimensional (the results can straightforwardly be generalized). An imaging device can be characterized by its transfer function, which describes the magnitude with which a spatial frequency g is transferred through the device, n is the noise. Usually, the resolution of the instrument ᑭ is defined from the cut-off 1/ᑭ beyond which no spadal information is transferred.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 222766-222773
Author(s):  
Mingming Tan ◽  
Tu Thanh Nguyen ◽  
Pawel Rosa ◽  
Mohammad Ahmad Zaki Al-Khateeb ◽  
Tingting Zhang ◽  
...  

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Mahmoud M. A. Eid ◽  
Ahmed Nabih Zaki Rashed ◽  
Ehab Salah El-din

AbstractAim and scope of this study is to simulate the performance signature of optical inter satellite links based booster Erbium doped fiber amplifier (EDFA) and receiver preamplifiers. The study is simulated to demonstrated the effect of changing the propagation distances between satellites spacing based on the booster EDFA and receiver preamplifiers. Signal power amplitude, Max. Q factor, and min bit error rate are investigated against the input power variations.


2019 ◽  
Vol 11 (1) ◽  
pp. 542-548
Author(s):  
Wenlong Tang ◽  
Hao Cha ◽  
Min Wei ◽  
Bin Tian ◽  
Xichuang Ren

Abstract This paper proposes a new refractivity profile estimation method based on the use of AIS signal power and quantum-behaved particle swarm optimization (QPSO) algorithm to solve the inverse problem. Automatic identification system (AIS) is a maritime navigation safety communication system that operates in the very high frequency mobile band and was developed primarily for collision avoidance. Since AIS is a one-way communication system which does not need to consider the target echo signal, it can estimate the atmospheric refractivity profile more accurately. Estimating atmospheric refractivity profiles from AIS signal power is a complex nonlinear optimization problem, the QPSO algorithm is adopted to search for the optimal solution from various refractivity parameters, and the inversion results are compared with those of the particle swarm optimization algorithm to validate the superiority of the QPSO algorithm. In order to test the anti-noise ability of the QPSO algorithm, the synthetic AIS signal power with different Gaussian noise levels is utilized to invert the surface-based duct. Simulation results indicate that the QPSO algorithm can invert the surface-based duct using AIS signal power accurately, which verify the feasibility of the new atmospheric refractivity estimation method based on the automatic identification system.


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