Approximations of the Aggregated Interference Statistics for Outage Analysis in Massive MTC

Area of Science:

• Wireless Communications
• Signal Processing
• Network Performance Analysis

Background:

• Massive machine-type communications (mMTC) involve a large number of devices with random activity, posing challenges for interference analysis.
• Accurate modeling of aggregated interference statistics is crucial for evaluating mMTC system performance.

Purpose of the Study:

• To develop analytic closed-form approximations for aggregated interference statistics in uplink mMTC.
• To derive an expression for outage probability using these approximations.
• To propose and evaluate a resource allocation strategy for mMTC systems.

Main Methods:

• Utilizing Gram-Charlier series expansion for a continuous approximation of discrete interference statistics.
• Deriving closed-form expressions for outage probability based on signal-to-interference-and-noise ratio (SINR).
• Employing a graph-based approach for resource allocation to minimize average outage probability.

Main Results:

• Accurate analytic approximations for aggregated interference statistics were derived.
• A closed-form expression for outage probability was obtained, enabling performance evaluation.
• A graph-based allocation strategy demonstrated effectiveness in minimizing outage probability.

Conclusions:

• The proposed approximations accurately model interference in mMTC systems.
• The developed resource allocation strategy effectively reduces outage probability.
• The findings contribute to the performance optimization of mMTC networks.