Intelligent Mobile Edge Computing With Pricing in Internet of Things

In this paper, we investigate mobile edge computing (MEC) networks for intelligent information services, where there are <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> users equipped with <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> antennas and one access point (AP). The users have some computational tasks, and some of them can be decoupled by the AP, at the cost of a fee charged by the AP. For the considered system, we firstly consider two important metrics of interest: latency and fee. Then, we formulate a stochastic game to model the interaction between users and the AP. In this game, the AP sets prices to maximize its profit, while users devise the offloading strategy to reduce both the latency and charge. We further optimize the system by applying the array signal processing schemes on the users, in order to reduce the transmission latency. Simulation results are finally presented to verify the effectiveness of the stochastic game, and it is shown that the array signal processing scheme can help reduce the transmission latency significantly.