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Computer Science > Information Theory

arXiv:1802.06759 (cs)
[Submitted on 19 Feb 2018]

Title:Network Lifetime Maximization for Cellular-Based M2M Networks

Authors:Amin Azari, Guowang Miao
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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
Comments: IEEE Access 2017
Subjects: Information Theory (cs.IT)
Cite as: arXiv:1802.06759 [cs.IT]
  (or arXiv:1802.06759v1 [cs.IT] for this version)
  https://doi.org/10.48550/arXiv.1802.06759
Related DOI: https://doi.org/10.1109/ACCESS.2017.2753283

Submission history

From: Amin Azari MS [view email]
[v1] Mon, 19 Feb 2018 18:51:07 UTC (1,107 KB)
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