Energy-Efficient Device-to-Device Communications for Green Smart Cities

被引:77
|
作者
Kai, Caihong [1 ]
Li, Hui [1 ]
Xu, Lei [1 ]
Li, Yuzhou [2 ]
Jiang, Tao [2 ]
机构
[1] Hefei Univ Technol, Sch Comp Sci & Informat Engn, Hefei 230009, Anhui, Peoples R China
[2] Huazhong Univ Sci & Technol, Sch Elect Informat & Commun, Wuhan 430074, Hubei, Peoples R China
基金
美国国家科学基金会;
关键词
Convex approximation; device-to-device (D2D) communications; energy consumption; green communications; resource allocation; smart city; RESOURCE-ALLOCATION; POWER ALLOCATION; ASSIGNMENT;
D O I
10.1109/TII.2017.2789304
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
To afford effective service of real-time monitoring and responses for smart cities, it is desired to provide ubiquitous network connections and high data rate services. However, the huge demands for ubiquitous high data rate wireless communications have caused a sharp increase in energy consumption and green house gas emission. In order to realize a sustainable smart city, it is critical to incorporate green communication technique into smart city developments. Device-to-device (D2D) communication has been recognized as one of the key technologies to improve data rate and reduce power consumption, which allows two physically nearby located user equipments to communicate directly with each other. In this paper, with the target of achieving green communications through D2D, we investigate the joint optimization of uplink subcarrier assignment (SA) and power allocation (PA) in D2D underlying cellular networks. Specifically, the problem formulation is to minimize the energy cost of all users in the system while guaranteeing the required data rate of both the D2D user equipments (DUEs) and cellular user equipments. Such an optimization problem is in general a mixed-integer nonlinear programming problem that is NP-hard. To make this problem tractable, we decompose it into the SA and PA subproblems. In particular, we design a heuristic algorithm to assign subcarrier by assuming that the transmit power is evenly allocated over all subcarriers. After that, we solve the PA subproblem by exploiting the difference between the concave function (D.C.) structure of the constraints and transform it into a convex optimization problem. Simulation results demonstrate the remarkable improvement in terms of power consumption by using our algorithms.
引用
收藏
页码:1542 / 1551
页数:10
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