TY - GEN
T1 - A renewable energy cooperation scheme for OFDM systems using evolutionary many-objective optimization algorithm
AU - Wang, Qiang
AU - Liu, Hai Lin
AU - Cheung, Yiu Ming
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/1/17
Y1 - 2017/1/17
N2 - Energy harvesting has drawn more and more attention because of the requirement of the green communication. It is well known that energy harvesting is one of the most important technologies of the green communication. Due to the intermittency of the renewable energy and the different space of the Base stations (BSS), the renewable energy cooperation is necessary to improve the renewable energy efficiency. In this paper, we propose a renewable energy cooperation scheme among different BSS, in which one BS can collect (share) energy from (to) another BSS. It is obvious that the energy cooperation efficiency will be improved when the number of the BSS that join the cooperation scheme is large. In this paper, our objective is to minimize the networks delay of each BS. To minimize the networks delay, it is reasonable that each BS hopes to transfer its energy to another BSS as little as possible, and collects energy from another BSS as much as possible. Thus, the objective of each BS are conflicting. We formulate the joint optimization problem into a many-objective mixed integer optimization problem which is difficult to optimize. We adopt the evolutionary many-objective algorithm based on decomposition and reference distance to optimize the problem. Simulation results show that the effectiveness of the algorithm.
AB - Energy harvesting has drawn more and more attention because of the requirement of the green communication. It is well known that energy harvesting is one of the most important technologies of the green communication. Due to the intermittency of the renewable energy and the different space of the Base stations (BSS), the renewable energy cooperation is necessary to improve the renewable energy efficiency. In this paper, we propose a renewable energy cooperation scheme among different BSS, in which one BS can collect (share) energy from (to) another BSS. It is obvious that the energy cooperation efficiency will be improved when the number of the BSS that join the cooperation scheme is large. In this paper, our objective is to minimize the networks delay of each BS. To minimize the networks delay, it is reasonable that each BS hopes to transfer its energy to another BSS as little as possible, and collects energy from another BSS as much as possible. Thus, the objective of each BS are conflicting. We formulate the joint optimization problem into a many-objective mixed integer optimization problem which is difficult to optimize. We adopt the evolutionary many-objective algorithm based on decomposition and reference distance to optimize the problem. Simulation results show that the effectiveness of the algorithm.
KW - Energy cooperation
KW - Green communication
KW - Many objective optimization problem
KW - Resource allocation
UR - https://ieeexplore.ieee.org/document/7820444
UR - http://www.scopus.com/inward/record.url?scp=85015204909&partnerID=8YFLogxK
U2 - 10.1109/CIS.2016.0053
DO - 10.1109/CIS.2016.0053
M3 - Conference proceeding
AN - SCOPUS:85015204909
SN - 9781509048410
T3 - Proceedings - 12th International Conference on Computational Intelligence and Security, CIS 2016
SP - 194
EP - 197
BT - Proceedings - 12th International Conference on Computational Intelligence and Security, CIS 2016
PB - IEEE
T2 - 12th International Conference on Computational Intelligence and Security, CIS 2016
Y2 - 16 December 2016 through 19 December 2016
ER -