Edge intelligent service system

Abstract

The invention discloses an edge intelligent service system. According to the invention, the local radio signal processing capability is utilized, the radio resource management capability and the distributed storage capability in the edge equipment are combined, and an edge intelligent service system architecture is formed through appropriate transmission mode selection, so that the effect of reducing the front-end load is achieved, and higher system capacity and higher processing rate are obtained. Specifically, four clouds are defined in a wireless access network of an edge intelligent service system: a global centralized communication and storage cloud, a centralized control cloud, a distributed logic communication cloud and a distributed logic storage cloud which are respectively responsible for communication, storage, control and signal processing. When the user equipment is accessed to the fog computing system Internet of Things, according to the moving speed, the communication distance, the position, the quality of service (QoS) requirements, the processing and caching capabilities of the user equipment, four transmission modes are selected: namely a D2D and relay mode, a local distributed coordination mode and a global C-RAN mode and a HPN mode, so higher efficiency is achieved.

Description

technical field [0001] The invention relates to an edge intelligent service system, which is mainly applied to the fifth generation mobile communication system (5G), and belongs to the field of Internet of Things and cloud computing. Background technique [0002] Compared with the fourth-generation wireless communication system (4G), the system capacity of the fifth-generation wireless communication system (5G) will increase by at least 1000 times, and the energy transmission efficiency will increase by at least 10 times. In order to achieve these goals, the edge intelligent service system must centrally process a large amount of data in distributed base stations, which requires this architecture to have two prerequisites: high bandwidth and low latency interconnected front-end. However, the existing front-end transmission is often constrained by capacity and time delay, and its performance in terms of spectral efficiency and energy efficiency is far from what is required by...

AI Technical Summary

Problems solved by technology

However, the existing front-end transmission is often limited by capacity and time delay, and its performance in terms of spectral efficiency and energy efficiency is far from what is required by the standard

As location-based social applications become more and more popular, front-end business data surges, resulting in a large amount of redundant information; at the same time, in order to meet the peak capacity requirements, operators need to deploy a large number of base stations to meet the peak capacity requirements, however Serious waste is caused when the business delivery volume is not large enough

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