NR Intercell Interference Modeling

This example uses:

This example shows the impact on network performance due to downlink (DL) intercell interference caused by nearby cells. The example models a 5G New Radio (NR) network of multiple cells operating in the same frequency band. Each cell has a gNB placed at the center of the cell that serves a set of user equipment (UE). The NR stack on the nodes includes radio link control (RLC), medium access control (MAC), and physical layers (PHY).

Introduction

This example models:

Co-channel intercell interference.
Slot-based round robin scheduling of physical downlink shared channel (PDSCH) resources.
Free space path loss (FSPL) model.
Single input single output (SISO) antenna configuration.
Link-to-system-mapping-based abstract PHY.

In this example, you consider the control packets, such as DL assignments, PDSCH feedback, and channel quality indicator (CQI) report, transmitted as out-of-band. Out-of-band refers to the transmission without the need for resources. It also refers to assured error-free reception.

Co-Channel Interference

Co-channel cells are the NR cells operating on the same frequency. They can interfere with each other.

Consider this sample network topology consisting of 3 cells. Cell-1 and Cell-3 operate on the same frequency band. Cell-2 operates on a different frequency band and does not interfere with Cell-1 or Cell-3.

Scenario setup

Check if the Communications Toolbox Wireless Network Simulation Library support package is installed. If the support package is not installed, MATLAB® returns an error with a link to download and install the support package.

wirelessnetworkSupportPackageCheck

Create a wireless network simulator.

rng("default") % Reset the random number generator
numFrameSimulation = 20; % Simulation time in terms of number of 10 ms frames
networkSimulator = wirelessNetworkSimulator.init;

Specify the positions of 3 gNBs and the gNB of interest for visualizing metrics.

gNBPositions = [1700 600 0; 3000 600 0; 2500 2000 0];
gNBOfInterestIdx = 3; % Specify a value between 1 and number of gNBs

Create the gNBs. Specify the position, carrier frequency, channel bandwidth, subcarrier spacing, transmit power, and receive gain of each gNB. Each gNB operates one NR cell.

gNBs = nrGNB(Position=gNBPositions,CarrierFrequency=2.5e9, ...
    ChannelBandwidth=10e6,SubcarrierSpacing=30e3,TransmitPower=32,ReceiveGain=11);

Set the scheduler parameter ResourceAllocationType by using the configureScheduler function.

for gNBIdx = 1:length(gNBs)
    % Resource allocation type value 0 indicate noncontiguous allocation of
    % frequency-domain resources in terms of RBGs
    configureScheduler(gNBs(gNBIdx),ResourceAllocationType=0)
end

Generate the positions of UEs in each cell.

numCells = length(gNBs);
cellRadius = 500; % Radius of each cell (in meters)
numUEsPerCell = 4;
uePositions = generateUEPositions(cellRadius,gNBPositions,numUEsPerCell);

Create the UEs and connect them to a gNB. Configure full buffer traffic in the DL direction.

UEs = cell(numCells,1);
for cellIdx = 1:numCells
    ueNames = "UE-" + (1:size(uePositions{cellIdx},1));
    UEs{cellIdx} = nrUE(Name=ueNames,Position=uePositions{cellIdx},ReceiveGain=11);
    connectUE(gNBs(cellIdx),UEs{cellIdx},FullBufferTraffic="DL")
end

Add gNBs and UEs to the network simulator.

addNodes(networkSimulator,gNBs);
for cellIdx = 1:numCells
    addNodes(networkSimulator,UEs{cellIdx})
end

Get the cell ID for the gNB of interest. All the visualizations and metrics are shown for this cell.

cellOfInterest = gNBs(gNBOfInterestIdx).ID;

Set the enableTraces as true to log the traces. If the enableTraces is set to false, then traces are not logged in the simulation. To speed up the simulation, set the enableTraces to false.

enableTraces = true;

Create objects to log MAC and PHY traces.

linkDir = 0; % Indicates DL
if enableTraces
    simSchedulingLogger = cell(numCells,1);
    simPhyLogger = cell(numCells,1);

    for cellIdx = 1:numCells
        % Create an object for MAC DL scheduling traces logging
        simSchedulingLogger{cellIdx} = helperNRSchedulingLogger(numFrameSimulation, ...
            gNBs(cellOfInterest),UEs{cellOfInterest},LinkDirection=linkDir);

         % Create an object for PHY layer traces logging
        simPhyLogger{cellIdx} = helperNRPhyLogger(numFrameSimulation,gNBs(cellOfInterest), ...
            UEs{cellOfInterest});
    end
end

Update the output metrics plots periodically, specifying numMetricsSteps updates within the simulation. numMetricsSteps must be less than or equal to number of slots in simulation.

numMetricsSteps = numFrameSimulation;

Create an object for MAC and PHY metrics visualization.

metricsVisualizer = helperNRMetricsVisualizer(gNBs(cellOfInterest),UEs{cellOfInterest}, ...
    CellOfInterest=cellOfInterest,NumMetricsSteps=numMetricsSteps, ...
    PlotSchedulerMetrics=true,PlotPhyMetrics=true,LinkDirection=linkDir);

Write the logs to MAT-files. You can use these logs for post-simulation analysis.

simulationLogFile = "simulationLogs"; % For logging the simulation traces

Set up mobility for the UE of interest in the cell of interest.

enableMobility = false;
if enableMobility
    ueSpeedRange = [1 100]; % In meters per second
    ueWithMobility = UEs{cellOfInterest}(2); % Get the UE-2 in the cell of interest
    % Install random waypoint mobility on the selected UE
    addMobility(ueWithMobility,SpeedRange=ueSpeedRange,BoundaryShape="circle",Bounds=[gNBs(cellOfInterest).Position(1:2) cellRadius])
end

Display the network topology.

helperTopologyVisualizer(cellOfInterest,cellRadius,gNBs,UEs)

Run the simulation for the specified numFrameSimulation frames.

% Calculate the simulation duration (in seconds)
simulationTime = numFrameSimulation*1e-2;
% Run the simulation
run(networkSimulator,simulationTime);

Read per-node stats.

gNBStats = statistics(gNBs);
ueStats = cell(numCells, 1);
for cellIdx = 1:numCells
    ueStats{cellIdx} = statistics(UEs{cellIdx});
end

At the end of the simulation, the achieved value for system performance indicators is compared to their theoretical peak values (considering zero overheads). Performance indicators displayed are achieved data rate (DL), achieved spectral efficiency (DL), and BLER observed for UEs (DL). The peak values are calculated as per 3GPP TR 37.910. In the specified cell of interest, UE-1, UE-3, and UE-4 are almost equidistant from their gNB. However, you can observe lower throughput for UE-3 and UE-4 as compared to UE-1. This is because UE-3 and UE-4 experience higher intercell interference.

displayPerformanceIndicators(metricsVisualizer)

Peak DL Throughput: 59.72 Mbps. Achieved Cell DL Throughput: 17.08 Mbps
Achieved DL Throughput for each UE: [4.01        9.16        1.47        2.44]
Peak DL spectral efficiency: 5.97 bits/s/Hz. Achieved DL spectral efficiency for cell: 1.71 bits/s/Hz
Block error rate for each UE in the downlink direction: [0.008           0       0.015       0.008]

Simulation Visualization

The run-time visualization shown are:

Display of Network Topology: The figure shows the configured cell topology. For each cell, it shows the position of the gNB and the connected UEs.
Display of DL scheduling metrics plots: For details, see 'Downlink Scheduler Performance Metrics ' figure description in NR Cell Performance Evaluation with MIMO example.
Display of DL Block Error Rates: The plot displayed in 'Block Error Rate (BLER) Visualization' shows the BLER (for each UE) observed in the downlink direction, as the simulation progresses.

Simulation Logs

The simulation logs are saved in MAT-files for post-simulation analysis and visualization. The per time step logs, scheduling assignment logs, and Phy reception logs are captured for each cell in the simulation and saved in the MAT-file simulationLogFile. After the simulation, open the file to load NCellID, DLTimeStepLogs, SchedulingAssignmentLogs, and PhyReceptionLogs in the workspace.

NCellID: This stores the cell ID and represents cell to which the simulation logs belong.

DL time step logs: Stores the per slot logs of the simulation with each slot as one row in the simulation. For details of log format, see the 'Time step logs' section of the NR Cell Performance Evaluation with MIMO example.

Scheduling assignment logs: Information of all the scheduling assignments and related information is logged in this file. For details of log format, see the 'Scheduling assignment logs' section in the NR Cell Performance Evaluation with MIMO example.

Phy reception logs: This file logs the packet reception information observed in the simulation. For details of log format, see the 'Phy reception logs' section in the NR Cell Performance Evaluation with MIMO example.

if enableTraces
    % Get the logs
    simulationLogs = cell(numCells, 1);
    for cellIdx = 1:numCells
        if gNBs(cellIdx).DuplexMode == "FDD"
            logInfo = struct("NCellID",[],"DLTimeStepLogs",[], ...
                "SchedulingAssignmentLogs",[],"PhyReceptionLogs",[]);
            logInfo.DLTimeStepLogs = getSchedulingLogs(simSchedulingLogger{cellIdx});
        else % TDD
            logInfo = struct("NCellID",[],"TimeStepLogs",[], ...
                "SchedulingAssignmentLogs",[],"PhyReceptionLogs",[]);
            logInfo.TimeStepLogs = getSchedulingLogs(simSchedulingLogger{cellIdx});
        end
        logInfo.NCellID = gNBs(cellIdx).ID;
        % Get the scheduling assignments log
        logInfo.SchedulingAssignmentLogs = getGrantLogs(simSchedulingLogger{cellIdx});
        % Get the Phy reception logs
        logInfo.PhyReceptionLogs = getReceptionLogs(simPhyLogger{cellIdx});
        simulationLogs{cellIdx} = logInfo;
    end
    % Save simulation logs in a MAT-file
    save(simulationLogFile,"simulationLogs")
end

Further Exploration

You can use this example to further explore these options:

Model the uplink interference between the nodes by specifying the uplink-related configuration parameters. For details, see the NR Cell Performance Evaluation with MIMO example.
Model the Aggressor-Victim scenarios: The aggressor is the source of interference and the victim suffers due to the interference. Consider the DL scenario in the following figure. The macro cell UE is far away from the macro base station (BS) and near to the small cell. In DL direction, macro cell UE suffers from interference by the small cell BS. The small cell BS is called the aggressor and macro UE is called the victim.

Model multiple clusters, where each cluster consists of cells operating on different frequencies, and analyze the impact of interference on the cell edge users.
Model the effects of intra-cell mobility on the downlink metrics: The mobility model installed on the UE determines the pattern along which the UE moves within a particular cell. Set the enableMobility to true for enabling mobility on UE-2 in the CellOfInterest. This plot demonstrates the effect of UE mobility on the throughput for a simulation duration of 1000 frames. The throughput decreases gradually as the UE moves away from the gNB. However, in comparison, the static UEs sustain their data rates throughout the simulation.

Throughput plots for the cell of interest with static UEs

Throughput plots for the cell of interest with mobility installed on UE-2

Local functions

function uePositions = generateUEPositions(cellRadius,gNBPositions,numUEsPerCell)
%generateUEPositions Return the position of UEs in each cell

numCells = size(gNBPositions,1);
uePositions = cell(numCells,1);
for cellIdx=1:numCells
    gnbXCo = gNBPositions(cellIdx,1); % gNB X-coordinate
    gnbYCo = gNBPositions(cellIdx,2); % gNB Y-coordinate
    gnbZCo = gNBPositions(cellIdx,3); % gNB Z-coordinate
    theta = rand(numUEsPerCell,1)*(2*pi);
    % Expression to calculate position of UEs with in the cell. By default,
    % it will place the UEs randomly with in the cell
    r = sqrt(rand(numUEsPerCell,1))*cellRadius;
    x = round(gnbXCo + r.*cos(theta));
    y = round(gnbYCo + r.*sin(theta));
    z = ones(numUEsPerCell,1) * gnbZCo;
    uePositions{cellIdx} = [x y z];
end
end

Appendix

The example uses these helper classes:

helperNRMetricsVisualizer.m: Implements metrics visualization functionality
helperNRSchedulingLogger.m: Implements scheduling information logging functionality
helperNRPhyLogger.m: Implements PHY packet reception information logging functionality
helperTopologyVisualizer.m: Implements 5G network topology visualization functionality

References

[1] 3GPP TS 38.104. “NR; Base Station (BS) radio transmission and reception.” 3rd Generation Partnership Project; Technical Specification Group Radio Access Network.

[2] 3GPP TS 38.214. “NR; Physical layer procedures for data.” 3rd Generation Partnership Project; Technical Specification Group Radio Access Network.

[3] 3GPP TS 38.321. “NR; Medium Access Control (MAC) protocol specification.” 3rd Generation Partnership Project; Technical Specification Group Radio Access Network.

[4] 3GPP TS 38.322. “NR; Radio Link Control (RLC) protocol specification.” 3rd Generation Partnership Project; Technical Specification Group Radio Access Network.

[5] 3GPP TS 38.323. “NR; Packet Data Convergence Protocol (PDCP) specification.” 3rd Generation Partnership Project; Technical Specification Group Radio Access Network.

[6] 3GPP TS 38.331. “NR; Radio Resource Control (RRC) protocol specification.” 3rd Generation Partnership Project; Technical Specification Group Radio Access Network.

[7] 3GPP TR 37.910. “Study on self evaluation towards IMT-2020 submission.” 3rd Generation Partnership Project; Technical Specification Group Radio Access Network.