Search Results

In MATLAB you can use the two functions chi2pdf() and chi2cdf() for numerical brute force solution for $\sigma^2$. …

Nevertheless, be careful taking into account fft/ifft normalization in calculating EbNo (assuming you are using MATLAB implementations). …

q = integral(g,xmin,xmax) For example $g(t) = e^{-t}$ $$q = \int_0^{\infty}e^{-t}\mathrm{d}t = 1$$ g = @(t) exp(-t); q = integral(g,0,Inf) More information Matlab numerical integration …

MATLAB/Octave code octave:6> N = 65536; octave:7> x=randn(1,N); octave:8> u=2*(randn(1,N)>0) - 1; octave:9> var(x) ans = 1.0020 octave:10> var(u) ans = 1.0000 The case of OP question $x$ is (0,1)- … $\mathrm{var}(u) = \mathbb{E}[(u - 0.5)^2] = (1 - 0.5)^2 \times \mathrm{Pr}(x >= 0.5) + (0 - 0.5)^2 \times \mathrm{Pr}(x < 0.5) = 0.25$ MATLAB/Octave code octave:13> N = 65536; octave:14> x=rand(1,N) …

A discrete-time baseband model of a multi-propagation channel can be written as $$y[m] = \sum_l h_l[m] x[m-l] + w[m]$$ where $l$ is the index of channel taps if the channel is modeled as a FIR $\{h_ …

This is impossible for the second constraint. As $63=3\times3\times7$, the difference of any two $r_i$ must not be a multiple of $3$. This is equivalent to the remainders of the division of any two $r …

Assuming one antenna transmits one symbol per time unit, then 16 symbols require 4 time units to be out. Then it is simply that r_1 = H_1 * x_1(1:4) r_2 = H_2 * x_1(5:8) r_3 = H_3 * x_1(9:12) r_4 = H …

For each sample, we note $1$ if error and $0$ otherwise. Then, for bit error rate $q$, the tests are independent Bernoulli random variables $\{X_i\}$ with probability $q$. The estimate is $\hat{p} = \ …

As specified in documentation, using 'ParityCheckMatrix' you can configure the Parity Check Matrix (PCM) during the constructions of the encoder/decoder objects. The syntax is encoder = comm.LDPCEncod …

What you are doing with matlab is playing with Equation (4) and you don't need to care about symbol duration and delay spread anymore. …

More details can be found at AWGN channel MATLAB. And by description of awgn() function: y = awgn(x,snr) adds white Gaussian noise to the vector signal x. …

Short answer 10*log(bw/fs) to take into account the oversampling operation because the awgn() function specifies the signal-to-noise ratio per sample, in dB. Longer answer The discrete time AWGN mo …