Energy Efficiency and System Capacity Based Multi-Objective Radio Resource Management in M2M Communications

Shaoyi XU; Shuai GAO

doi:10.11999/JEIT181168

Volume 41 Issue 12

Dec. 2019

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Article Navigation > Journal of Electronics & Information Technology > 2019 > 41(12): 2817-2825

Shaoyi XU, Shuai GAO. Energy Efficiency and System Capacity Based Multi-Objective Radio Resource Management in M2M Communications[J]. Journal of Electronics & Information Technology, 2019, 41(12): 2817-2825. doi: 10.11999/JEIT181168

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Shaoyi XU, Shuai GAO. Energy Efficiency and System Capacity Based Multi-Objective Radio Resource Management in M2M Communications[J]. Journal of Electronics & Information Technology, 2019, 41(12): 2817-2825. doi: 10.11999/JEIT181168

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Energy Efficiency and System Capacity Based Multi-Objective Radio Resource Management in M2M Communications

doi: 10.11999/JEIT181168

Shaoyi XU^,,
Shuai GAO

School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing 100044, China

Funds: The National Natural Science Foundation of China(61571038), The Important National Science & Technology Specific Projects of China(2016ZX03001011-004), The Fundamental Research Funds for the Central Universities (2016JBZ003)

Received Date: 2018-12-19
Rev Recd Date: 2019-07-24

Available Online: 2019-08-22

Publish Date: 2019-12-01

Abstract

Abstract

Machine-to-Machine (M2M) and Device-to-Device (D2D) communications are both key technologies in the Fifth Generation (5G) mobile communication systems. In M2M communications, the Energy Efficiency (EE) especially needs to be improved to extend the life cycle of the M2M equipment. In this paper, the M2M and D2D technologies are combined and the D2D technology is used to realize M2M transmission. At the same time, M2M users are allowed to reuse spectrum resources with Human-to-Human (H2H) devices in the cellular networks. To guarantee the Quality of Service (QoS) of these two systems simultaneously, a Multi-Objective Optimization Problem (MOOP) is then formulated to maximize the sum throughput of H2H systems, and the sum EE of M2M systems and to minimize the interference from M2M communications to H2H networks. To solve this MOOP, the penalty function method is firstly adopted to relax the original binary variables, and then the ConCave-Convex Procedure (CCCP) method is used to convert the non-convex single-objective problems into convex problems. Finally, the weighted Tchebyshev algorithm is utilized to obtain the Pareto solution of the original MOOP. By comparing with the traditional weighted sum method, the effectiveness of the proposed method is proved by simulation results.
- Machine-to-Machine (M2M),
- Human-to-Human (H2H),
- Multi-Objective Optimization Problem (MOOP),
- ConCave-Convex Procedure (CCCP),
- Weighted Tchebyshev

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References

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