Effective Energy Efficiency under Delay-Outage Probability Constraints and F-Composite Fading.

Area of Science:

• Wireless Communications
• Information Theory
• Network Engineering

Background:

• Next Generation cellular networks (6G) and beyond rely on machine-type communications (MTCs) with numerous autonomous Internet of Things (IoT) devices.
• Effective energy efficiency (EEE) is a critical key performance indicator (KPI) for 6G due to IoT's autonomous and energy-intensive nature.
• Existing research lacks investigation into the EEE of random arrival traffic, a fundamental aspect of MTCs.

Purpose of the Study:

• To explore and evaluate the Effective Energy Efficiency (EEE) over F-composite fading channels, considering random arrival traffic for IoT applications.
• To analyze EEE under a finite blocklength regime and Quality of Service (QoS) constraints for both constant and sporadic traffic patterns.
• To derive optimal power and rate allocation strategies to maximize EEE under QoS constraints.

Main Methods:

• Developed a point-to-point buffer-aided communication system model for uplink transmission under a finite blocklength regime.
• Characterized the communication channel using the F-composite fading model, assuming perfect channel state information (CSI) at the receiver.
• Utilized Markovian source models for average arrival rate and applied effective bandwidth and capacity theories to determine QoS-satisfying rates.
• Formulated and solved individual and joint power allocation (PA) and rate allocation (RA) optimization problems numerically using a particle swarm optimization (PSO) algorithm.

Main Results:

• Derived exact closed-form expressions for outage probability and effective rate, providing accurate approximations for analysis.
• Demonstrated that EEE exhibits a quasi-concave behavior, revealing a trade-off between transmit power and rate for EEE maximization.
• Quantified the impact of line-of-sight and shadowing parameters on EEE performance.

Conclusions:

• The study provides a comprehensive analysis of EEE for IoT communications in complex fading environments, crucial for 6G.
• Optimal power and rate allocation strategies are essential for maximizing EEE while adhering to QoS requirements.
• The findings offer valuable insights for designing energy-efficient 6G wireless systems supporting massive IoT deployments.