Interference suppression in spread spectrum system

Interference suppression in spread spectrum system using kalman filter.

please anyone provide the matlab code of this

Answer 1

[Dr. JANAK TRIVEDI]

% Define the system parameters

spreadFactor = 10;

bandwidth = 1;

sigmaNoise = 0.1;

sigmaInterference = 1;

% Define the Kalman filter parameters

A = 1;

B = 1;

C = spreadFactor;

Q = sigmaNoise^2;

R = sigmaInterference^2;

% Initialize the state and covariance matrices

x = [0; 0];

P = [0 0; 0 0];

% Preallocate the arrays for storing the results

xEstimate = zeros(2, 1000);

y = zeros(1, 1000);

% Generate the signals

for k = 1:1000

% Generate the noise and interference

noise = sigmaNoise * randn;

interference = sigmaInterference * randn;

% Generate the spread signal

x(1) = bandwidth * randn;

x(2) = x(1) * spreadFactor + noise + interference;

% Kalman filter prediction step

xEstimate(:, k) = A * x;

P = A * P * A' + Q;

% Kalman filter update step

y(k) = C * x + interference;

K = P * C' / (C * P * C' + R);

xEstimate(:, k) = xEstimate(:, k) + K * (y(k) - C * xEstimate(:, k));

P = (eye(2) - K * C) * P;

end

% Plot the results

figure

subplot(2, 1, 1)

plot(xEstimate(1, :))

title('Estimated Signal')

subplot(2, 1, 2)

plot(y)

title('Observed Signal')