Coverage probability analysis of three uplink power control schemes: Stochastic geometry approach

Area of Science:

• Wireless communication networks
• Signal processing
• Stochastic geometry

Background:

• Mobile stations adjust transmit power for desired signal quality and interference management.
• Optimal power levels are influenced by path loss, shadowing, fading, and network configuration.
• Performance analysis of uplink power control is complex due to correlated cell associations and distance-dependent path loss.

Purpose of the Study:

• To analyze and quantify the impact of three uplink transmit power control schemes on network performance.
• To derive performance metrics like coverage probability using stochastic geometry.
• To investigate the influence of various factors including shadowing, path loss, and base station deployment density.

Main Methods:

• Modeling cellular networks with standard power-law path loss and composite Rayleigh-lognormal fading.
• Application of stochastic geometry tools to derive uplink transmit power distributions.
• Derivation of network coverage probability based on signal-to-interference-plus-noise ratio (SINR).

Main Results:

• Coverage probability is highly sensitive to shadowing severity and power control scheme parameters.
• Coverage remains invariant to base station deployment density under mild shadowing and fractional power control.
• At low SINRs, compensating for both path loss and shadowing enhances coverage.
• At high SINRs, compensating only for path loss improves coverage.

Conclusions:

• The choice of power control scheme and its parameters significantly impacts network coverage.
• Shadowing severity is a critical factor determining coverage performance.
• Fractional power control and mild shadowing conditions simplify performance analysis and decouple it from base station density.