Social-aware energy efficiency optimization for device-to-device communications in 5G networks

• Published in: Computer communications 2018-05, Vol.120, p.102-111
• Main Authors: Huynh, De-Thu, Wang, Xiaofei, Duong, Trung Q., Vo, Nguyen-Son, Chen, Min
• Format: Article
• Language: English
• Subjects: 5G networks; D2D communications; Energy efficiency; Mobile social networks; Spectrum efficiency
• ISSN: 0140-3664; 1873-703X
• DOI: 10.1016/j.comcom.2018.02.008

•The challenges that appear when exploiting the social relationships of mobile users to improve the performance of D2D communications in 5G networks are intensively analyzed.•The energy efficiency optimization (EEO) problem in D2D communications is formulated by carefully considering both the social relationships and physical interference between all mobile users in the 5G networks.•A novel EEO method is proposed to maximize the energy efficiency while ensuring high system throughput and spectrum efficiency for high QoS requirements by applying the Adaptive Genetic Algorithm.•The convergence rate of algorithm is considered to demonstrate the feasibility our proposed solution.•The performance of proposed EEO method is evaluated to show the effectiveness of our method in terms of energy efficiency and system throughput for social-aware D2D communications in 5G networks. Mobile social networks and device-to-device (D2D) communications have emerged as promising techniques to support better local advanced services in 5G networks. Nevertheless, the integration of mobile social networks and D2D communications into 5G networks poses pivotal challenges such as how to exploit the social relationships of mobile users (MUs) and manage the interference and resources (i.e., spectrum and energy) in order to improve the performance of D2D communications. To this end, we propose a social-aware energy efficiency optimization solution for D2D communications in 5G networks. In particular, we first analyze and evaluate the influence of social relationships on the performance of D2D communications, which enable us to formulate the energy efficiency optimization (EEO) problem while carefully considering both the social relationships and physical interference between all the MUs. The EEO problem is then solved for optimal channel mode selection and optimal transmission powers allocated to each MU to maximize the energy efficiency, by utilizing adaptive genetic algorithm. Numerical results show that compared with social-unaware methods, our proposed solution can achieve significant improvement in terms of energy efficiency and system throughput while preserving the quality of service (QoS) for all users by taking into account the spectrum efficiency and transmission power constraints.