Resource allocation algorithm with energy efficiency priority based on quasi-Newton interior point method in cognitive internet of vehicles

Affiliation of Author(s):电子信息工程学院

Journal:Dongnan Daxue Xuebao

Abstract:To improve the energy efficiency and real-time performance of multi-user resource allocation (RA) in cognitive internet of vehicles (IoV), a resource allocation algorithm maximizing system energy efficiency was proposed with imperfect channel state information (CSI). Considering the constraints of the transmission power budget, the primary users' interference thresholds, the minimum communication rate and the proportional fairness among users, the interference constraints of the primary users were transformed into the probabilistic constraints. Then, the Bernstein approximation was used to deal with the probabilistic constraints and the proportional fairness among users was solved by setting the fair threshold. Finally, high and low complexity subcarrier allocation algorithms were used respectively, and combining with the quasi-Newton interior point method, a power allocation was carried out. The simulation results show that the energy efficiency of the proposed algorithm is about 93% of the upper bound of the optimal solution, which can meet the energy efficiency requirement of the system and reduce the computational complexity. It is suitable for the IoV with high real-time requirements. © 2019, Editorial Department of Journal of Southeast University. All right reserved.

ISSN No.:1001-0505

Translation or Not:no

Date of Publication:2019-03-20

Co-author:Tan, Yazhu,Dong, Li,Wang, Jiankang,Hu, Jin,Song, Tiecheng

Correspondence Author:Song Xiaoqin

Date of Publication:2019-03-20