Future wireless networks will be characterized by heterogeneous traffic requirements. Such requirements can be low-latency or minimum-throughput. Therefore, the network has to adjust to different needs. Usually, users with low-latency requirements have to deliver their demand within a specific time frame, i.e., before a deadline, and they co-exist with throughput oriented users. In addition, the users are mobile and they share the same wireless channel. Therefore, they have to adjust their power transmission to achieve reliable communication. However, due to the limited power budget of wireless mobile devices, a power-efficient scheduling scheme is required by the network. In this work, we cast a stochastic network optimization problem for minimizing the packet drop rate while guaranteeing a minimum throughput and taking into account the limited-power capabilities of the users. We apply tools from Lyapunov optimization theory in order to provide an algorithm, named Dynamic Power Control (DPC) algorithm, that solves the formulated problem in realtime. It is proved that the DPC algorithm gives a solution arbitrarily close to the optimal one. Simulation results show that our algorithm outperforms the baseline Largest-Debt-First (LDF) algorithm for short deadlines and multiple users.
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