Average channel capacity in anisotropic atmospheric non-Kolmogorov turbulent medium

2019 ◽  
Vol 451 ◽  
pp. 129-135 ◽  
Author(s):  
Yalçın Ata ◽  
Yahya Baykal ◽  
Muhsin Caner Gökçe
Keyword(s):  
Channel Capacity ◽  
Turbulent Medium ◽  
Average Channel Capacity

scholarly journals Average Channel Capacity of Amplify-and-forward MIMO/FSO Systems Over Atmospheric Turbulence Channels

2018 ◽  
Vol 8 (6) ◽  
pp. 4334
Author(s):  
Duong Huu Ai
Keyword(s):  
Atmospheric Turbulence ◽  
Channel Capacity ◽  
Multiple Input Multiple Output ◽  
Mathematical Expression ◽  
Relay Channel ◽  
Free Space Optical ◽  
Amplify And Forward ◽  
Average Channel Capacity ◽  
Link Distance ◽  
Gamma Distributions

In amplify-and-forward (AF) relay channel, when the direct link between source and destination terminals is deeply faded, the signal from the source terminal to the destination terminal propagates through the relay terminals, each of which relays a signal received from the previous terminal to the next terminal in series. This paper, we theoretically analyze the performance of multiple-input multiple-output (MIMO) AF free-space optical (FSO) systems. The AF-MIMO/FSO average channel capacity (ACC), which is expressed in terms of average spectral efficiency (ASE) is derived taking into account the atmospheric turbulence effects on the MIMO/FSO channel. They are modeled by log-normal and the gamma-gamma distributions for the cases of weak-to-strong turbulence conditions. We extract closed form mathematical expression for the evaluation of the ACC and we quantitatively discuss the influence of turbulence strength, link distance, different number of relay stations and different MIMO configurations on it.

Average channel capacity for Rake receivers

2002 ◽  
Vol 38 (10) ◽  
pp. 475 ◽  
Author(s):  
P. Varzakas ◽  
G.S. Tombras
Keyword(s):  
Channel Capacity ◽  
Rake Receivers ◽  
Average Channel Capacity

scholarly journals An adaptive q-Lognormal model towards the computation of Average Channel Capacity in slow fading channels

2021 ◽  
Author(s):  
Tanmay Mukherjee ◽  
Dilip Senapati
Keyword(s):  
Fading Channels ◽  
Channel Capacity ◽  
Performance Measures ◽  
Lognormal Model ◽  
Average Channel Capacity ◽  
Slow Fading ◽  
Slow Fading Channels ◽  
Log Normal ◽  
Log Normal Distribution

Abstract The characterization of multipath fading and shadowing in wireless communication systems is essential towards the evaluation of various performance measures. It is well known that the statistical characterization of shadowing phenomena is captured by distributions viz., log-normal distribution, gamma distribution and other mixture distributions. However, it is observed that the log-normal distribution fails to characterize the outliers in the fading signal. The extreme fluctuations in the fading signal needs to be characterized efficiently for error free computation of the various performance metrics. In this context, this paper portrays an adaptive generalized Tsallis’ non-extensive q-Lognormal model towards the characterization of various fading channels. This model operates well with the synthesized fading signals and captures the wide range of tail fluctuations to adapt different fading scenarios. The significance and applicability of the proposed novel q- Lognormal model in capturing the slow fading channels is validated using different statistical tests viz., chi-square test and symmetric JS measure. Furthermore, essential performance measures viz., the average channel capacity, closed form expression of cumulative distribution function (CDF) in terms of Gauss-Hypergeometric function 2 F 1 [a ; b ; c; z], higher order moments corresponding to q-Lognormal channel capacity and coefficient of variation is evaluated corresponding to the proposed q-Lognormal model performing extensive Monte-Carlo simulation techniques up to O (10^7).

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