Energy efficiency is one of the main challenges to be faced by mobile communications in the near future. The growth of the mobile communications market which is boosted by the increasing penetration of smartphones and laptops requires an increase of the network capacity and, consequently, a great leap forward also for the infrastructures. In this scenario, in order to reduce the operative expenditures, the network operators pay attention to energy saving strategies that may also contribute to the reduction of greenhouse emissions. In this paper the exponential smoothing technique is applied to forecast traffic in a given area considering daily and weekly variations. The availability of a reliable prediction of the future traffic values allows the adaptation of macro base station transmission power and the introduction of a sleep mode for micro base stations and permits to guarantee the requested network capacity while saving energy consumption. Results show the effectiveness of traffic forecast technique for capacity prediction and the usefulness of the proposed algorithms for energy efficiency maximization, affording very good performance, very close to the optimum one.