data = readmatrix('subtowersutm.xlsx');
% Extract latitude, longitude, and RSRP values.
measurement_lat = data(:, 1);
measurement_lon = data(:, 2);
rsrp = data(:, 11); % Adjust the column index for RSRP data.
% Check if the dimensions of Lat and Lon match
if size(measurement_lat) ~= size(measurement_lon)
error('Latitude and Longitude dimensions do not match.');
end
% Define the UTM zone for your area.
utm_zone = 32;
% Step 2: Transform Coordinates using the built-in 'deg2utm' function
[utm_x, utm_y, utm_zone] = deg2utm(measurement_lat, measurement_lon);
Unrecognized function or variable 'deg2utm'.
% Define the pixel size and create the grid
pixel_size = 20; % Adjust as needed
x_grid = min(utm_x):pixel_size:max(utm_x);
y_grid = min(utm_y):pixel_size:max(utm_y);
% Step 3: Calculate average RSRP for each pixel
num_pixels_x = numel(x_grid) - 1;
num_pixels_y = numel(y_grid) - 1;
average_rsrp = zeros(num_pixels_y, num_pixels_x); % Initialize the grid.
for i = 1:num_pixels_x
for j = 1:num_pixels_y
% Define the current pixel polygon.
polygon_x = [x_grid(i), x_grid(i + 1), x_grid(i + 1), x_grid(i)];
polygon_y = [y_grid(j), y_grid(j), y_grid(j + 1), y_grid(j + 1)];
% Check if measurements fall within the current pixel.
in_polygon = inpolygon(utm_x, utm_y, polygon_x, polygon_y);
% Calculate average RSRP for the measurements within the polygon.
if any(in_polygon)
rsrp_values_in_polygon = rsrp(in_polygon); % Replace with your RSRP data.
% Convert dBm to watts, compute average, and convert back to dBm.
rsrp_watts = 10 .^ (rsrp_values_in_polygon / 10);
average_rsrp(j, i) = 10 * log10(mean(rsrp_watts));
end
end
end
% Step 4: Plot the heatmap of average RSRP
% You can use various plotting functions to visualize the heatmap.
heatmap(x_grid(1:end-1), y_grid(1:end-1), average_rsrp);
colorbar;
xlabel('UTM X');
ylabel('UTM Y');
title('Average RSRP Heatmap');