Distributed Resource Management in Unlicensed Assisted Mobile Edge Computing

This paper studies joint power, spectrum and computational resource allocation in mobile edge computing (MEC) systems. Considering that the licensed spectrum resources are not sufficient, the computing tasks can also be uploaded to the remote MEC server (MECS) via the unlicensed spectrum. To facilitate fair coexistence with Wi-Fi networks, we adopt the duty-cycle-muting mechanism with adaptive adjustment of the duty cycle on unlicensed channels. We propose a Stackelberg game formulation, where the aim is to minimize the long-term energy consumption of the non-cooperative user terminals (UEs) while guaranteeing the stability of task buffers. In the game, the MECS prices the licensed spectrum to indirectly adjust the proportion of bandwidth for each UE. In particular, we develop a distributed resource management algorithm, which enables the UEs to behave independently and adaptively. Theoretical analysis and simulations demonstrate the effectiveness of our proposed algorithm with respect to energy saving under constrained signaling overheads.