Hi Michael,
To visualize the impact of jamming or noise on a coverage map using MATLAB, we can adopt a simplified yet insightful approach. This method involves adjusting the signal-to-noise ratio (SNR) or signal-to-interference-plus-noise ratio (SINR) to reflect the degradation caused by interference across your coverage area. It's a practical way to simulate the challenges faced in real-world communication systems due to unwanted signals.
Here is a simplified MATLAB example to illustrate this approach:
% Example parameters
txLocation = [0, 0]; % Transmitter location
txPower = 10; % dBm
jammerLocation = [100, 100]; % Jammer location
jammerPower = -20; % dBm, representing the disruptive power of the jammer
frequency = 2.4e9; % Frequency in Hz
% Grid setup
[x, y] = meshgrid(-200:20:200, -200:20:200);
% Calculate distances
distTx = sqrt((x - txLocation(1)).^2 + (y - txLocation(2)).^2);
distJammer = sqrt((x - jammerLocation(1)).^2 + (y - jammerLocation(2)).^2);
% Pathloss calculation (simplified free-space model)
c = 3e8; % Speed of light
pathLossTx = 20*log10(distTx) + 20*log10(frequency) + 20*log10(4*pi/c);
pathLossJammer = 20*log10(distJammer) + 20*log10(frequency) + 20*log10(4*pi/c);
% Adjust for jamming impact
snrAdjusted = txPower - pathLossTx + jammerPower - pathLossJammer;
% Visualization
figure;
contourf(x, y, reshape(snrAdjusted, size(x)), 20);
colorbar;
title('Coverage Map with Jamming Impact');
xlabel('X Position');
ylabel('Y Position');
This example is a basic starting point that shows how jamming can change signal coverage, using the simple idea of pathloss. It is a straightforward and basic way to see the effects of interference. For real-world projects, you will likely need to dive deeper into the specifics and complexities of your situation.
I hope this helps!
