One of the biggest problems facing future mobile systems beyond 5G (B5G) is the energy dissipation of mobile devices at high data rates. The heat generated by these devices can impact the performance as a result of a new type of outage called power-consumption outage. In this article, we propose a general definition of the power-consumption outage and describe its three features. Based on the heat transfer model in smartphones, the power-consumption outage probability is analyzed. Specifically, we derive the joint outage probability of channel and power-consumption outages in relation to the signal-to-noise ratio (SNR), communication duration, and initial temperature of the smartphone-back-plate. The joint outage probability is then used to obtain the upper bound of the maximum receiving rate of a typical smartphone. Furthermore, we propose and analyze the impact on the capacity of the power-consumption outage. Simulation results show that the power-consumption outage probability increases with an increase of SNR and with extension of the communication duration. The upper bound of the maximum receiving rate of a smartphone decreases with an extension of communication duration. Considering the joint outage probability, simulation results show that the outage capacities, i.e., channel and power-consumption outages, decrease with an increase of SNR after reaching a given capacity threshold.

With the growing interest in the deployment of massive multiple-input-multiple-output (MIMO) systems and millimeter wave technology for fifth generation (5G) wireless systems, the computation power to the total power consumption ratio is expected to increase rapidly due to high data traffic processing at the baseband unit. Therefore in this paper, a joint optimization problem of computation and communication power is formulated for multi-user massive MIMO systems with partially-connected structures of radio frequency (RF) transmission systems. When the computation power is considered for massiv MIMO systems, the results of this paper reveal that the energy efficiency of massive MIMO systems decreases with increasing the number of antennas and RF chains, which is contrary with the conventional energy efficiency analysis results of massive MIMO systems, i.e., only communication power is considered. To optimize the energy efficiency of multi-user massive MIMO systems, an upper bound on energy efficiency is derived. Considering the constraints on partially-connected structures, a suboptimal solution consisting of baseband and RF precoding matrices is proposed to approach the upper bound on energy efficiency of multi-user massive MIMO systems. Furthermore, an oPtimized Hybrid precOding with computation and commuNication powEr (PHONE) algorithm is developed to realize the joint optimization of computation and communication power. Simulation results indicate that the proposed algorithm improves energy and cost efficiencies and the maximum power saving is achieved by 76.59% for multi-user massive MIMO systems with partially-connected structures.