3D Poisson-Based Neighborhood Capacity Analysis for Millimeter Wave Communications

Area of Science:

• Wireless Communications
• Stochastic Geometry
• Telecommunications Engineering

Background:

• Millimeter wave (mmWave) communication is crucial for high-bandwidth wireless systems.
• Existing models often assume fixed node distributions and simplified propagation.
• Understanding link capacity in dense, 3D deployments is essential for future networks.

Purpose of the Study:

• To develop a theoretical model for evaluating mmWave source-destination link capacity.
• To analyze link performance for arbitrary destination locations in a 3D homogeneous Poisson point process network.
• To investigate the impact of various parameters on link capacity in realistic propagation environments.

Main Methods:

• A theoretical framework based on a 3D homogeneous Poisson point process for node distribution.
• Inclusion of realistic propagation effects: path loss, shadowing, and link states (LoS, nLoS, outage).
• Derivation of closed-form capacity formulas validated by Monte Carlo simulations.

Main Results:

• The model provides accurate, closed-form expressions for mmWave link capacity.
• Analysis reveals the influence of node intensity, antenna gain, and frequency band on capacity.
• Performance evaluation is possible for any neighbor order, accommodating arbitrary destination placements.

Conclusions:

• The proposed model offers a comprehensive approach to mmWave link capacity analysis in 3D stochastic networks.
• It provides valuable insights for designing and optimizing future wireless systems operating in mmWave frequencies.
• The model's flexibility in handling arbitrary node distributions and realistic propagation enhances its practical applicability.