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Energy‐efficient joint power control and resource allocation for cluster‐based NB‐IoT cellular networks
Author(s) -
Zhu Shuqiong,
Wu Wenquan,
Feng Lei,
Zhao Pan,
Zhou Fanqin,
Yu Peng,
Li Wenjing
Publication year - 2019
Publication title -
transactions on emerging telecommunications technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.366
H-Index - 47
ISSN - 2161-3915
DOI - 10.1002/ett.3266
Subject(s) - computer science , efficient energy use , mathematical optimization , resource allocation , power control , channel (broadcasting) , throughput , energy consumption , optimization problem , base station , distributed computing , power (physics) , wireless , computer network , algorithm , telecommunications , mathematics , engineering , electrical engineering , physics , quantum mechanics
Abstract As a new cellular technology introduced in 3rd Generation Partnership Project (3GPP) Release 13, Narrow‐band Internet of Things (NB‐IoT) provides wide‐area coverage for massive IoT devices. In the perspective of NB‐IoT business applications, it is easily known that energy efficiency is of utmost importance. In this paper, we propose an energy‐efficient joint resource allocation and power control for cluster‐based NB‐IoT cellular networks. The scheme mainly consists of 2 parts, ie, the formation of NB‐IoT device clusters and joint optimization of power and channel allocation. Firstly, by considering the geographical distribution density and the communication capability of NB‐IoT devices, we propose a fast cluster formation scheme to categorize a group of devices into multiple clusters. The cluster head is selected based on the strategy of maximal remaining battery energy due to its higher power consumption than that of clustered devices. Then, a joint optimization of resource and power is proposed for the maximization of energy efficiency of cluster‐based NB‐IoT cellular networks. Exploiting the properties of an objective function, we transform the original nonconvex optimization problem into equivalent 2‐step subproblems. In the first step, the optimal power allocation for any feasible channel reuse assignments is solved by finding the Nash equilibrium point based on noncooperative gaming. In the second step, the resource assignment problem is modeled as bipartite graphs matching and a Hungarian algorithm is used to obtain the perfect matching of channel reusing for maximal energy efficiency. Numerical results demonstrate the remarkable improvements in terms of energy efficiency and device access rate during a period by using the proposed scheme.