Open AccessEnergy efficiency optimisation of large‐scale multiple‐input–multiple‐output system with transmit antenna selection
Author(s) -
Hei Yongqiang,
Liu Yongli,
Li Wentao,
Liu Jiao,
Li Xiaohui
Publication year - 2017
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2016.1092
Subject(s) - mathematical optimization , computer science , transmitter power output , convergence (economics) , base station , selection (genetic algorithm) , energy consumption , mathematics , telecommunications , channel (broadcasting) , electrical engineering , artificial intelligence , economics , economic growth , transmitter , engineering
The rapid development of wireless communication comes at the cost of dramatically increasing energy consumption, which makes the optimisation of energy efficiency (EE) extremely important. In this study, the authors focus on maximising EE of large‐scale multiple‐input–multiple‐output system by optimising the transmit power and the number of selected base station antennas. First, the EE optimisation problem, i.e. finding the optimal EE‐based values of each parameter, when the other one is fixed, is investigated. Then, the optimisation problem jointly considering these two parameters to maximise EE is studied. Moreover, the EE optimisation problem is extended to multi‐user (MU) system. Owing to the formulation of EE, the EE optimisation problem is reformulated as the fractional programming problem, and the Dinkelbach method is proposed to deal with this problem instead of the binary search algorithm (BSA) by switching the objective function to a weighted sum of rate and power. Simulation results show that the EE can be improved with the proposed Dinkelbach method, and it has a faster convergence speed than the BSA without any performance loss for both single‐user system and MU system.