NOMA mobile edge computing system construction method with anti-eavesdropping capability

Abstract

The invention discloses an NOMA mobile edge computing system construction method with anti-eavesdropping capability. In the case that there is an eavesdropper and the channel state information of theeavesdropper is unknown, a user introduces a metric independent of the channel state information of the eavesdropper through secret coding to quantify the anti-eavesdropping ability of the user. Two users simultaneously send respective partial tasks to nearby access points equipped with mobile edge computing servers through NOMA uplinks in a resource block sharing manner and perform fast processing, thereby actively assisting the execution of computing tasks of mobile users, and ensuring the fast execution of the computing tasks with low delay tolerance and high complexity of mobile clients. The NOMA mobile edge computing system construction method disclosed by the invention has the advantages of ensuring secure transmission of information through the anti-eavesdropping ability when the channel state information of the eavesdropper is unknown. According to the NOMA mobile edge computing system construction method disclosed by the invention, a class of interrupt events based on probabilistic analysis is also defined to measure the communication performance of the system and to evaluate the impact of transmitting power and unloading tasks on the system performance.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and in particular relates to a construction method of a secure NOMA mobile edge computing system with anti-eavesdropping capabilities. Background technique [0002] Mobile edge computing (Mobile Edge Computing, MEC) and non-orthogonal multiple access (Non-orthogonal Multiple Access, NOMA) are considered to be promising technologies in the next generation of wireless networks. MEC can calculate a large number of tasks in real time, improve the computing power and energy efficiency of wireless devices, and realize various computing-intensive and low-latency IoT applications. Therefore, MEC has attracted more and more industry and academia. research interests. By deploying MEC servers at the edge of the network such as access points, IoT devices offload heavy computing tasks to access points via wireless links, so that they can be efficiently executed remotely in the MEC system. By ...

AI Technical Summary

Problems solved by technology

In fact, in a real eavesdropping scenario, since the eavesdropper is usually passive, it is very difficult to detect the eavesdropper, let alone obtain its channe

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