The channel power gain of a wireless
communication channel can be modeled
by an exponential RV with average
(mean) equals 2. Then, what is the
value Pr{ X>3X>2 } is equal to?
Answers
Hello,
If you consider a noise-dominant case, you will use AWGN channel. For modulated scenario, you should use Complex Gaussian model. If you experience and fading channel you have to consider a complex Gaussian channel which the signal envelope is based on the Rayleigh or Rician models. IF you consider the X^2 in your hand, Gaussian model will be changed to exponential.
Cite
Popular Answers (1)
13th Apr, 2015
Ahmet Yılmaz
The Scientific & Technological Research Council of Turkey
Hello,
Simply we can express the received signal as:
Received_Signal = Transmitted_Signal * Fading + Additive_Noise;
In general, additive noise has a Gaussian distribution with a constant power spectral density.
On the other hand, when we consider Fading distribution, we have so many options. If direct path between the transmitter and receiver (i.e., line-of-sight, LOS) is available Rice distribution is a good option. When LOS is not available Rayleigh distribution is better one.
In addition, mathematically tractable and general fading models such as Nakagami-m distribution is also good one.
Rayleigh, Ricean and Nakagami-m distributions are magnitude distributions. If we express a fading random variable as a complex number
h = x + j*y
x and y have Gaussian distribution. abs(h) ~ Rayleigh distribution.
Power of h i.e., (abs(h))^2 ~ Exponential distribution.
You can choose your channel model which is more proper for your problem and mathematically tractable. If you raise your contribution, you can choose more general fading model.
---
Cite
7 Recommendations
All Answers (4)
13th Apr, 2015
Emil Björnson
Linköping University
If the variable h is a scalar channel with a zero-mean complex Gaussian distribution with variance V, then |h|^2 has an exponential distribution with mean V.
I believe that these are the two "different" models that you have seen in papers, but it is really just the same model. I am not aware of any paper that assumes that h is exponentially distributed, but if you've found such a paper, please give the title and I can have a look!
Cite
6 Recommendations
13th Apr, 2015
Ahmet Yılmaz
The Scientific & Technological Research Council of Turkey
Hello,
Simply we can express the received signal as:
Received_Signal = Transmitted_Signal * Fading + Additive_Noise;
In general, additive noise has a Gaussian distribution with a constant power spectral density.
On the other hand, when we consider Fading distribution, we have so many options. If direct path between the transmitter and receiver (i.e., line-of-sight, LOS) is available Rice distribution is a good option. When LOS is not available Rayleigh distribution is better one.
In addition, mathematically tractable and general fading models such as Nakagami-m distribution is also good one.
Rayleigh, Ricean and Nakagami-m distributions are magnitude distributions. If we express a fading random variable as a complex number
h = x + j*y
x and y have Gaussian distribution. abs(h) ~ Rayleigh distribution.
Power of h i.e., (abs(h))^2 ~ Exponential distribution.
You can choose your channel model which is more proper for your problem and mathematically tractable. If you raise your contribution, you can choose more general fading model
Hello,
If you consider a noise-dominant case, you will use AWGN channel. For modulated scenario, you should use Complex Gaussian model. If you experience and fading channel you have to consider a complex Gaussian channel which the signal envelope is based on the Rayleigh or Rician models. IF you consider the X^2 in your hand, Gaussian model will be changed to exponential.
Cite
Popular Answers (1)
13th Apr, 2015
Ahmet Yılmaz
The Scientific & Technological Research Council of Turkey
Hello,
Simply we can express the received signal as:
Received_Signal = Transmitted_Signal * Fading + Additive_Noise;
In general, additive noise has a Gaussian distribution with a constant power spectral density.
On the other hand, when we consider Fading distribution, we have so many options. If direct path between the transmitter and receiver (i.e., line-of-sight, LOS) is available Rice distribution is a good option. When LOS is not available Rayleigh distribution is better one.
In addition, mathematically tractable and general fading models such as Nakagami-m distribution is also good one.
Rayleigh, Ricean and Nakagami-m distributions are magnitude distributions. If we express a fading random variable as a complex number
h = x + j*y
x and y have Gaussian distribution. abs(h) ~ Rayleigh distribution.
Power of h i.e., (abs(h))^2 ~ Exponential distribution.
You can choose your channel model which is more proper for your problem and mathematically tractable. If you raise your contribution, you can choose more general fading model.
---
Cite
7 Recommendations
All Answers (4)
13th Apr, 2015
Emil Björnson
Linköping University
If the variable h is a scalar channel with a zero-mean complex Gaussian distribution with variance V, then |h|^2 has an exponential distribution with mean V.
I believe that these are the two "different" models that you have seen in papers, but it is really just the same model. I am not aware of any paper that assumes that h is exponentially distributed, but if you've found such a paper, please give the title and I can have a look!
Cite
6 Recommendations
13th Apr, 2015
Ahmet Yılmaz
The Scientific & Technological Research Council of Turkey
Hello,
Simply we can express the received signal as:
Received_Signal = Transmitted_Signal * Fading + Additive_Noise;
In general, additive noise has a Gaussian distribution with a constant power spectral density.
On the other hand, when we consider Fading distribution, we have so many options. If direct path between the transmitter and receiver (i.e., line-of-sight, LOS) is available Rice distribution is a good option. When LOS is not available Rayleigh distribution is better one.
In addition, mathematically tractable and general fading models such as Nakagami-m distribution is also good one.
Rayleigh, Ricean and Nakagami-m distributions are magnitude distributions. If we express a fading random variable as a complex number
h = x + j*y
x and y have Gaussian distribution. abs(h) ~ Rayleigh distribution.
Power of h i.e., (abs(h))^2 ~ Exponential distribution.
You can choose your channel model which is more proper for your problem and mathematically tractable. If you raise your contribution, you can choose more general fading model