This work develops power control algorithms for bit/Joule energy efficiency (EE) maximization in wireless networks. Unlike previous related works, minimum-rate constraints are imposed and the signal-to-interference-plus-noise ratio takes a more general expression which encompasses some of the most promising 5G candidate technologies. Both network-centric and user-centric EE maximizations are considered. In the first scenario, the maximization of the global EE and of the minimum EE of the network are performed. Unlike previous contributions, centralized algorithms are developed which are guaranteed to converge with limited computational complexity to Karush-KuhnTucker points of the considered, non-convex optimization problems. Moreover, closed-form feasibility conditions are derived. In the user-centric scenario, game theory is used to study the equilibria of the network and to derive convergent power control algorithms, which can be implemented in a fully decentralized fashion. Both scenarios above are studied under the assumption that single or multiple resource blocks are employed for data transmission. Numerical results are provided to assess the performance of the proposed solutions and to make comparisons in different settings.
Considering rate constraints and signal-to-inference-plus-noise ratio (SINR) expression in 5G technologies, authors in REF proposed a improved power control algorithms for energy efficiency optimization in wireless networks.
Energy-Efficient Power Control: A Look at 5G Wireless Technologies
ArXiv
ArXiv
Computer Science Mathematics