Cost-efficient edge caching for NOMA-enabled IoT services

Mobile edge computing (MEC) is a promising paradigm by deploying edge servers (nodes) with computation and storage capacity close to IoT devices. Content Providers can cache data in edge servers and provide services for IoT devices, which effectively reduces the delay for acquiring data. With the increasing number of IoT devices requesting for services, the spectrum resources are generally limited. In order to effectively meet the challenge of limited spectrum resources, the Non-Orthogonal Multiple Access (NOMA) is proposed to improve the transmission efficiency. In this paper, we consider the caching scenario in a NOMA-enabled MEC system. All the devices compete for the limited resources and tend to minimize their own cost. We formulate the caching problem, and the goal is to minimize the delay cost for each individual device subject to resource constraints. We reformulate the optimization as a non-cooperative game model. We prove the existence of Nash equilibrium (NE) solution in the game model. Then, we design the Game-based Cost-Efficient Edge Caching Algorithm (GCECA) to solve the problem. The effectiveness of our GCECA algorithm is validated by both parameter analysis and comparison experiments.