Contents

Generate dataset

%
% Load the provided dataset parameters
%
dataset_params = read_params('NR_example_1_params.m');

%
% Generate the dataset with the loaded parameters
%
[DeepMIMO_dataset, dataset_params] = DeepMIMO_generator(dataset_params);
 DeepMIMO Dataset Generation started
 Reading the channel parameters of the ray-tracing scenario O1_60
 Basestation 1
 Constructing the DeepMIMO Dataset for BS 1 - Percentage completed: 100.0
 DeepMIMO Dataset Generation completed 

Variable inspection

Select a user and basestation pair

Note: These variables will be used later to select a single user.

bs = 1; ue = 1;

% Let's check the size of the dataset
size_of_channel = size(DeepMIMO_dataset{bs}.user{ue}.channel)

% Path parameters
DeepMIMO_dataset{bs}.user{ue}.path_params

% Check velocity and travel direction of the UE
velocity = DeepMIMO_dataset{bs}.user{ue}.path_params.velocity;
travel_dir_sph = DeepMIMO_dataset{bs}.user{ue}.path_params.travel_dir;
[tr_x, tr_y, tr_z] = sph2cart(deg2rad(travel_dir_sph(1)), deg2rad(90-travel_dir_sph(2)), velocity);
travel_dir = [tr_x, tr_y, tr_z];
size_of_channel =

    28     1    32   256


ans = 

  struct with fields:

               DoD_phi: [1×9 single]
             DoD_theta: [1×9 single]
               DoA_phi: [1×9 single]
             DoA_theta: [1×9 single]
                 phase: [1×9 single]
                   ToA: [1×9 single]
                 power: [1×9 single]
             num_paths: 9
            LoS_status: 1
                    DS: [1×9 single]
            travel_dir: [2×1 double]
              velocity: 15.0765
    rxArrayOrientation: [2×1 double]

Plot an example channel

An example channel magnitude response is plotted for OFDM symbols through time.

channel = DeepMIMO_dataset{bs}.user{ue}.channel;

channel_plot = abs(squeeze(channel(:, 1, 1, :)));
subcarriers = 1:dataset_params.OFDM_sampling_factor:dataset_params.OFDM_limit;
OFDM_symbols = 1:1:(14*dataset_params.CDL_5G.num_slots);

figure;

subplot(2 ,1, 1);
surf(OFDM_symbols, subcarriers, channel_plot');
shading('flat');
xlabel('OFDM Symbols');
ylabel('Subcarriers');
zlabel('|H|');
title('Channel Magnitude Response');
view(-75, 35)


subplot(2,1,2);
imagesc(OFDM_symbols, subcarriers, channel_plot');
set(gca,'YDir','normal') % Invert Y axis (subcarriers)
shading('flat');
xlabel('OFDM Symbols');
ylabel('Subcarriers');
zlabel('|H|');
title('Channel Magnitude Response');
view(0, 90)

Plot the position and velocity of a user

Plot the basestation position, user position and velocity of a single user.

bs_loc = DeepMIMO_dataset{bs}.loc;

ue_loc = DeepMIMO_dataset{bs}.user{ue}.loc;
travel_vector = travel_dir / 3.6; % m/s
figure;
scatter3(bs_loc(1), bs_loc(2), bs_loc(3), 'bo');
hold on
scatter3(ue_loc(1), ue_loc(2), ue_loc(3), 'rx');
quiver3(ue_loc(1), ue_loc(2), ue_loc(3), travel_vector(1), travel_vector(2), travel_vector(3), 1, 'k')
xlabel('x (m)');
ylabel('y (m)');
zlabel('z (m)');

Path loss of the users

We combine the positions of the users along with the combined path-loss variables to plot it with the basestation location.

bs_loc = DeepMIMO_dataset{bs}.loc;
num_ue = 362;

ue_locs = zeros(num_ue, 3);
ue_pl = zeros(num_ue, 1);
for ue = 1:362
    ue_locs(ue, :) = DeepMIMO_dataset{bs}.user{ue}.loc;
    ue_pl(ue) = DeepMIMO_dataset{bs}.user{ue}.pathloss;
end

figure;
scatter3(ue_locs(:, 1), ue_locs(:, 2), ue_locs(:, 3), [], ue_pl);
hold on
scatter3(bs_loc(1), bs_loc(2), bs_loc(3), 'bo');
xlabel('x (m)');
ylabel('y (m)');
zlabel('z (m)');
title('Path Loss (dBm)')
colorbar()

Reconstruct the CDL channel object

Can be used with the MATLAB CDL channel visualization tools to check the transmit and receive antennas (shape and orientation), along with the channel paths.

ue = 1;
channel_path_parameters = DeepMIMO_dataset{bs}.user{ue}.path_params;
txSize = dataset_params.CDL_5G.bsAntenna{bs};
txOrientation = dataset_params.CDL_5G.bsOrientation{bs}; % BS Orientation from dataset params
txPolarization = dataset_params.CDL_5G.bsPolarization+1; % BS Polarization for BS-UE channel
rxSize = dataset_params.CDL_5G.ueAntSize;
rxOrientation = channel_path_parameters.rxArrayOrientation; % UE Orientation from path params
rxPolarization = dataset_params.CDL_5G.uePolarization+1; % UE Polarization for BS-UE channel

CDL_channel = construct_DeepMIMO_CDL_channel(txSize, txOrientation, txPolarization, rxSize, rxOrientation, rxPolarization, dataset_params, channel_path_parameters);

% Visualize the RX and TX antennas with MATLAB 5G Toolbox functions:
CDL_channel.displayChannel('LinkEnd','Tx');
CDL_channel.displayChannel('LinkEnd','Rx');