How to Implement Network Pilot Contamination in NS2

To Implement Network Pilot Contamination in NS2 has a series of steps to follow that contain to mimic a scenario in which multiple cells or nodes use the same pilot sequences, that cause to interference during channel estimation and in the neighbouring cells caused to interference, so it corrupting the performance of the communication system. The below is a step-by step procedure to implement the Network Pilot Contamination in NS2:

Step-by-Step Implementation:

  1. Understand Pilot Contamination

In massive MIMO systems, pilot signals are used for channel estimation. Nevertheless, when pilot signals are reused in neighbouring cells because of a limited number of available orthogonal pilot sequences, the channel estimates become inaccurate. This problem is known as pilot contamination. The main goal of executing pilot contamination in NS2 is to mimic the interference triggered by these reused pilot sequences.

  1. Modify NS2 for Massive MIMO Simulation

Meanwhile NS2 does not natively support massive MIMO or pilot contamination, we will need to execute or modify some core components of the simulator:

  • MIMO Support: Initially we need to expand the physical layer to help MIMO communication and this contain to adjust the signal propagation model and antenna model to mimic multiple input/output antennas.
  • Pilot Signal Definition: describe the pilot signals in the simulation. These can be denoted as the particular sequences sent during the channel estimation phase. We will need to mimic the reuse of these sequences in diverse cells or nodes.
  1. Implement Pilot Signal Reuse

To replicate pilot contamination, we need to design the reuse of pilot sequences through different cells or base stations.

  1. Define Pilots: Allocate each base station or access point a set of pilot sequences.
    • In NS2, we can generate pilot signal sequences as part of the node or PHY layer configuration. For example, allocate the particular nodes the same pilot sequence to replicate pilot reuse.
  2. Pilot Reuse across Cells: make sure that neighbouring cells or nodes use the same pilot sequence. This step generates the conditions for pilot contamination, in which one node’s pilot interferes with the neighbouring cell’s communication.
    • For example, two adjacent base stations could be allocated the same pilot sequence to mimic the interference.

Example in TCL script:

set baseStation1 [new BaseStation]

set baseStation2 [new BaseStation]

# Assign same pilot sequence to both base stations to simulate contamination

$baseStation1 setPilotSequence “pilot_seq_1”

$baseStation2 setPilotSequence “pilot_seq_1”

  1. Modify the Channel Estimation Mechanism

Pilot contamination impacts the accuracy of channel estimation. To mimic this, we will need to adapt the channel estimation process in NS2.

  1. Channel Estimation with Pilots: In the PHY layer, adjust the channel estimation function to use the pilot sequences. The interference from reused pilots should destroy the channel estimation.
  2. Incorporate Contamination in SINR Calculation: SINR (Signal-to-Interference-plus-Noise Ratio) is vital in wireless communication. When pilot contamination happens, the interference from neighbouring cells using the same pilot sequence must be accounted for in SINR calculations.

Adjust the SINR calculation in phy.cc to contain interference from contaminated pilots:

double pilotInterference = calcPilotInterference();  // Interference from reused pilots

double sinr = receivedPower / (noise + interference + pilotInterference);

  1. Channel Estimation Errors: we can mimic the degradation in channel estimation by adding an error term that relay on the level of pilot contamination:

double estimationError = pilotInterference / totalPower;

estimatedChannel = trueChannel * (1 – estimationError);  // Imprecise channel estimation

  1. Simulate Multi-Cell Massive MIMO Network

To fully mimic pilot contamination, we need to configure a multi-cell network with massive MIMO base stations.

  1. Multi-Cell Setup: In TCL script, describe several base stations (or cells) with overlapping coverage areas. Allocate each base station its own users, and make sure that some base stations reuse the same pilot sequences.

Example setup:

# Create a multi-cell network

set baseStation1 [$ns node]

set baseStation2 [$ns node]

# Assign pilots to base stations (reusing pilots between cells)

$baseStation1 setPilotSequence “pilot_1”

$baseStation2 setPilotSequence “pilot_1”  # Same pilot as baseStation1

  1. User Assignment: Allocate users (or mobile nodes) to each base station. The users will send pilot signals during the uplink to support their respective base stations estimate the channel. But, due to pilot contamination, the base station’s channel estimates will be impacted by users in neighbouring cells using the same pilot sequence.
  1. Simulate Pilot Contamination Effects

Once pilot contamination is established, simulate its impacts on network performance:

  • Decreased SINR: The reuse of pilot sequences leads to interference that lowers the SINR that should reflect in the simulation results.
  • Impaired Channel Estimation: Channel estimation errors because of pilot contamination should effect in poor communication quality, lower data rates, and more packet losses.
  1. Running the Simulation

After configuring the environment with pilot contamination in TCL script, execute the simulation:

ns pilot_contamination_simulation.tcl

  1. Analyse Results

Inspect the trace files to evaluate the impacts of pilot contamination on network performance. The parameters to analyse that contain:

  • SINR: validate on how pilot contamination impacts the SINR in contaminated cells.
  • Throughput: measure the throughput and compare it with a scenario without pilot contamination.
  • Packet Delivery Ratio: See how the contamination affects packet delivery and overall network reliability.
  1. Possible Enhancements

We can further improve the simulation by executing the mitigation strategies for pilot contamination, such as:

  • Pilot Allocation Optimization: Execute a technique to enhance pilot allocation across cells to reduce contamination.
  • Channel Estimation Refinement: Establish advanced technique for channel estimation that prevents the impacts of pilot contamination such as blind channel estimation.

Example of TCL Script Setup

# Setup simulation

set ns [new Simulator]

# Create base stations with pilot reuse

set bs1 [$ns node]

set bs2 [$ns node]

# Assign the same pilot sequence to simulate contamination

$bs1 setPilotSequence “pilot_seq_1”

$bs2 setPilotSequence “pilot_seq_1”

# Create mobile nodes and assign to base stations

set mn1 [$ns node]

set mn2 [$ns node]

# Define communication links and setup scenario

$ns_ at 1.0 “$mn1 send-pilot $bs1”

$ns_ at 1.0 “$mn2 send-pilot $bs2”

In the presented manual will demonstrated the implementation process that supports to implement the Network Pilot Contamination and measure their performance NS2 tool. If you’re looking for the greatest implementation advice, contact ns2project.com; we can provide the best outcomes. We aid you in algorithm tailored to your needs.