Energy efficient cooperative multicast beamforming in ultra dense networks

Energy efficiency is one of the main requirements for future 5G wireless networks to allow a sustainable network development. Toward this goal, this paper proposes a novel iterative algorithm to maximize the energy efficiency of multicast services in ultra dense networks. Macrocell and small cells cooperate using a multicast beamforming strategy to efficiently radiate the power in the considered area. Moreover, small cells are activated opportunistically, and their power levels are adjusted suitably. Due to the high complexity of the optimization problem, the proposed algorithm works calculating iteratively beamforming weights and power adjustments, thus reducing the set of possible solutions. Then, an exhaustive search is performed among the elements of this restricted set. This solution has reduced computational complexity, and the achieved energy efficiency is higher than benchmark alternatives. Performance in terms of energy efficiency and complexity are provided together with a solution feasibility evaluatio