Network Lifetime Maximization for Cellular-Based M2M Networks

TL;DR

This paper develops energy consumption models and proposes scheduling and power control strategies to maximize network lifetime in cellular-based massive MTC, demonstrating significant improvements through simulations.

Contribution

It introduces a realistic energy model and lifetime-aware scheduling/power control methods specifically for massive MTC over cellular networks, including low-complexity solutions.

Findings

Proposed solutions significantly extend network lifetime.

Energy efficiency and spectral efficiency tradeoffs are analyzed.

Simulation results confirm substantial lifetime improvements.

Abstract

High energy efficiency is critical for enabling massive machine-type communications (MTC) over cellular networks. This work is devoted to energy consumption modeling, battery lifetime analysis, lifetime-aware scheduling and transmit power control for massive MTC over cellular networks. We consider a realistic energy consumption model for MTC and model network battery-lifetime. Analytic expressions are derived to demonstrate the impact of scheduling on both the individual and network battery lifetimes. The derived expressions are subsequently employed in the uplink scheduling and transmit power control for mixed-priority MTC traffic in order to maximize the network lifetime. Besides the main solutions, low-complexity solutions with limited feedback requirement are investigated, and the results are extended to existing LTE networks. Also, the energy efficiency, spectral efficiency, and network lifetime tradeoffs in resource provisioning and scheduling for MTC over cellular networks are investigated. The simulation results show that the proposed solutions can provide substantial network lifetime improvement and network maintenance cost reduction