A framework for energy-efficient design of 5G technologies

This paper considers the problem of energy efficiency maximization in the uplink of a cluster of multiple-antenna coordinated access points. A framework for energy efficiency optimization is developed in which the signal-to-interference- plus-noise ratio takes a more general expression than existing alternatives so as to encompass most 5G candidate technologies. Two energy efficiency optimization problems are formulated, also considering QoS constraints: 1) network global energy efficiency maximization; 2) worst-case energy-efficient design. These frac- tional, non-convex problems are tackled by means of fractional programming coupled with sequential convex optimization, and two low-complexity resource allocation algorithms are designed, which are guaranteed to converge to Karush-Kuhn-Tucker points of the non-convex problems. Numerical results show that the proposed algorithm can efficiently balance between the goals of maximizing the energy efficiency and meeting the QoS constraints. Moreover, it is shown that a small sum-rate reduction allows large energy savings.