Cache-aided multiuser UAV-MEC networks for smart grid networks: A DDPG approach

Abstract

Mobile edge computing (MEC) is an important research topic in the field of wireless communication and mobile computing, as it can effectively decrease the latency and energy consumption due to the trade-off between the communication and computing, where some intensive computing tasks can be offloaded to computational access points (CAPs), especially when the wireless transmission channel is in good condition. This article studies how to intelligently allocate the computing capability and wireless bandwidth among users for a cache-aided multi-terminal multi-CAP MEC network with non-ideal channel estimation, where there are $N$ mobile terminals and $M$ CAPs in the network. Each terminal has some tasks that need to be computed in a fast and efficient way. For such a system, we first design the system by jointly considering the computing capability and wireless bandwidth allocation, where the computing and communication delay is used as the performance of metric. To optimize the system performance, we then employ deep deterministic policy gradient to learn an effective strategy on the allocation of computing capability and wireless bandwidth, in order to decrease the system delay as much as possible. Simulations are finally conducted to show the superiority of the proposed studies in this article, especially about the advantages from cache.