New Method of Energy Efficient Subcarrier Allocation Based on Evolutionary Game Theory

• Published in: Mobile networks and applications 2021-04, Vol.26 (2), p.523-536
• Main Authors: Zhang, De-gan, Chen, Chen, Cui, Yu-ya, Zhang, Ting
• Format: Article
• Language: English
• Subjects: Communications Engineering; Competition; Computer Communication Networks; Data transmission; Electrical Engineering; Energy efficiency; Energy transmission; Engineering; Evolution; Evolutionary design method; Filter banks; Game theory; IT in Business; Mathematical programming; Networks; Operators (mathematics); Optimization; Power consumption; Power efficiency; Resource allocation; Subcarriers; Transmission rate (communications); Utility functions
• ISSN: 1383-469X; 1572-8153
• DOI: 10.1007/s11036-018-1123-y

Since there is a competition between subcarriers because FBMC (Filter Bank Multicarrier) modulation technology does not need subcarriers to be orthogonal to each other, we consider the evolutionary game method to optimize subcarrier allocation. Because the adjacent subcarriers do not need to be orthogonal to each other in FBMC, there is conflict and competition, thus the evolutionary game theory is used to optimize the subcarrier allocation problem. We innovatively introduced the channel state matrix to show the quality of subcarriers. Considering the height of secondary user and base station’s antenna, the total data transmission rate limit, total power consumption constraint and power consumption constraint on a single subcarrier, a nonlinear fractional programming problem is established where maximum energy efficiency is the objective function, total data transmission rate limit, total power consumption constraint and power consumption constraint on a single subcarrier are constraint conditions. The utility function for each secondary user is established when the evolutionary game operator is designed. When the utility function becomes optimal, the evolutionary game reaches Nash equilibrium, and the strategy combination is considered to be the energy efficient resource allocation scheme. Through experimental simulation, EESA-EG proposed in this paper gives the most reasonable subcarrier allocation scheme, allocates more subcarriers for the subcarriers with better channel state and the energy efficiency in EESA-EG is optimal.