Cache-Aided MEC With the Assistance of Intelligent Reflecting Surface

To address the large concerns of energy consumption caused by the rapid growth of online data traffic and network services such as the applications of the Internet of Things, many technologies have been developed to help wireless communication. Mobile edge computing (MEC) can develop the efficiency and reduce the energy consumption of the network through edge-cloud benefits. Intelligent reflecting surface (IRS) can improve spectrum efficiency and decrease power costs by changing the transmission environment. Considering that IRS also has some good physical characteristics, it can be integrated into MEC as auxiliary equipment and yield marked performance improvement. In this study, we design an IRS-assisted cache-aided MEC system by optimizing the beamformer of base station (BS) and the phase-shift vector of IRS jointly. We develop two algorithms based on the block coordinate descent (BCD) method to achieve this goal. First, we propose a branch-and-bound (BB)-based algorithm. By the algorithm, an approximately optimal solution of the IRS element optimization problem can be obtained under constant modulus constraints. Then, we develop a Lagrange multiplier method-based algorithm that has less complexity. The performance of IRS-assisted cache-aided MEC with the proposed algorithms is demonstrated by simulation results.