Research Article
Energy Efficiency Optimization-Based Joint Resource Allocation and Clustering Algorithm for M2M Communication Networks (Workshop)
@INPROCEEDINGS{10.1007/978-3-030-41117-6_29, author={Changzhu Liu and Ahmad Zubair and Rong Chai and Qianbin Chen}, title={Energy Efficiency Optimization-Based Joint Resource Allocation and Clustering Algorithm for M2M Communication Networks (Workshop)}, proceedings={Communications and Networking. 14th EAI International Conference, ChinaCom 2019, Shanghai, China, November 29 -- December 1, 2019, Proceedings, Part II}, proceedings_a={CHINACOM PART 2}, year={2020}, month={2}, keywords={Machine to machine (M2M) communications Clustering Resource allocation Energy efficiency (EE)}, doi={10.1007/978-3-030-41117-6_29} }- Changzhu Liu
Ahmad Zubair
Rong Chai
Qianbin Chen
Year: 2020
Energy Efficiency Optimization-Based Joint Resource Allocation and Clustering Algorithm for M2M Communication Networks (Workshop)
CHINACOM PART 2
Springer
DOI: 10.1007/978-3-030-41117-6_29
Abstract
In recent years, machine-to-machine (M2M) communications have attracted great attentions from both academia and industry. In M2M communication networks, machine type communication devices (MTCDs) are capable of communicating with each other intelligently under highly reduced human interventions. In this paper, we address the problem of joint resource allocation and clustering for M2M communications. By defining the system energy efficiency (EE) as the sum of the EE of MTCDs, the joint resource allocation and clustering problem is formulated as a system EE maximization problem. As the original optimization problem is a nonlinear fractional programming problem, which cannot be solved conveniently, we transform it into two subproblems, i,e., power allocation subproblem and clustering subproblem, and solve the two subproblems by means of Lagrange dual method and modified K-means algorithm, respectively. Numerical results demonstrate the effectiveness of the proposed algorithm.
