文献类型：期刊文献

英文题名：Resource Allocation and Power Control for D2D Communications to Prolong the overall System Survival Time of Mobile Cells

作者：Zhang, Zitian[1];Wu, Yue[1];Chu, Xiaoli[1,2];Zhang, Jie[1,2]

机构：[1]East China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China;[2]Univ Sheffield, Dept Elect & Elect Engn, Sheffield S1 4ET, S Yorkshire, England

年份：2019

卷号：7

起止页码：17111

外文期刊名：IEEE ACCESS

收录：;EI(收录号：20190806530165);WOS:【SCI-EXPANDED(收录号:WOS:000459199000001)】；

基金：This work was supported in part by the EU's H2020 Research and Innovation Programme under Grant Agreement No 778305, and in part by the Shanghai Sailing Program under Grant 18YF1405300.

语种：英文

外文关键词：D2D communication; resource allocation and power control; overall system survival time; game theory

摘要：Device-to-device (D2D) communications as an underlay to cellular networks can potentially improve the system throughput and reduce transmission delays between users, which, however, are largely limited by the battery lifetime of user equipment (UE). In this paper, we define the overall system survival time of a mobile cell and maximize it by jointly optimizing the resource allocation and power control (RAPC) for D2D and conventional cellular links. Considering that the UEs may have different levels of residual battery energy, we define the overall system survival time as the minimally expected battery lifetime among all transmitting UEs in a cell. Subject to the transmission rate requirement of each link, we formulate the joint optimization of RAPC as a non-linear programming problem, which is NP-hard. To solve it, we devise a game theory based distributed approach, where the links are considered as non-cooperative players with the overall system survival time as their utility function. We prove the existence of the Nash equilibrium in our RAPC game and propose a low-complexity algorithm to calculate each individual player's best response, given the strategies of other players. Numerical results show that our game theory based approach can significantly prolong the overall system survival time as compared with existing RAPC schemes.