Massive Multiple-Input Multiple-Output (mMIMO) is emerging as a cornerstone technology for 5G communications. It promises to scale up the performance of the conventional communication systems by growing the number of antennas at the base station side. This paper proposes a decentralized, scalable, and energy efficient radio resource allocation method tailored for the uplink of the upcoming 5G air interface, based on the mMIMO physical layer. The proposed solution elaborates on a game-theoretical approach, which aims at maximizing the energy efficiency of mobile terminals, while guaranteeing the respect of average data rates and power consumptions constraints. This formulation leads to a low-complexity, iterative, and distributed algorithm, which considers (just to mention few relevant issues) the impact of channel time selectivity, delayed feedback from the base station, and physical-layer details of the selected communication technology. An extensive simulation campaign, considering a LTE-A-based multicellular system based on mMIMO, is used to evaluate the benefits of the proposed technique. By calculating energy efficiency, user and peak data rates, spectral efficiency, outage probability, and other minor performance indexes, the reported results clearly demonstrate the performance gain that the designed solution offers with respect to baseline strategies.