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## How do you calculate channel gain and path loss?

path loss exponent (n) = 3.5 The channel is small scale Rayleigh fading with path loss, and the average power gain over all channels equals to 1. In matlab, i calculate channel gain using g=abs(h)^2/(d)^n, where h is a Rayleigh random variable, and then SNR=(P.g/N0).

How is channel gain calculated?

The channel gain H of a wireless channel (S,R) is defined by: Y= H X + Z, where X is the signal sent by S, Y is the signal received by R and Z ~ N(0,1) is the noise term.

### How is path loss calculated?

To calculate free space path loss for isotropic antennas, follow the given instructions: Take the square of the wavelength of the carrier wave. Multiply the distance between the transmitter and receiver antennas by 4π, and take the square of the result. Divide the value from step 1 with that of step 2.

What is the path loss in dB?

Path loss in dB: where is the path loss in decibels, is the wavelength and is the transmitter-receiver distance in the same units as the wavelength. Note the power density in space has no dependency on ; The variable. exists in the formula to account for the effective capture area of the isotropic receiving antenna.

#### What is channel gain?

The channel gain is a complex number whose magnitude is the attenuation of the signal and angle is the phase shift of the signal at a given time instant. So for your purpose, is same as the pathloss.

What is path gain in wireless communication?

Path gain is defined as the ratio of average receive and transmit powers for omnidirectional, co- polarized transmit/receive antennas.

## What is channel coefficient?

When using a base-band representation of MIMO systems, the channel coefficients are complex Gaussian variables with zero mean and equal variance. These coefficients can be independent identical variables but other MIMO channels models can introduce correlations between these variables, as in. B. Habib, G.

What is the capacity of a channel?

The channel capacity, C, is defined to be the maximum rate at which information can be transmitted through a channel. The fundamental theorem of information theory says that at any rate below channel capacity, an error control code can be designed whose probability of error is arbitrarily small.