Knowledge review of the Ninth Datang Cup Provincial Competition - 5G+ Vertical Industry Application (20%)

5G+ vertical industry applications (20%)

Master the basic concepts and applications of 5G+ IoV, master the network architecture and mainstream deployment schemes of 5G IoV, master the standards and implementation of vehicle-road collaborative information and communication technology, and master 5G technology-based intelligent networked vehicle scenario solutions.

Master the application of 5G-based artificial intelligence algorithms, and master the innovative methods of applying 5G+artificial intelligence algorithms in vertical industries.

 

1. 5G Internet of Vehicles

  1. Basic Concepts (Frequency Bands), Advantages, Challenges
  2. Two camps:

(1) DSRC - a relatively mature IEEE-led solution, a vehicle-specific short-range communication technology, and end-to-end direct access. (what?)

 

(2) C-V2X (domestic, based on cellular network and V2X)

One is to connect to the vehicle profile communication through the base station; the other is to communicate directly between vehicles, with fewer turning points and lower delay.

 

①LTE-V2X: 3GPP R14 (version agreement content); resource allocation mode - mode3: centralized scheduling of base stations, mode4: terminal autonomy

②NR-V2X: 3GGP R16; resource allocation mode - mode1: under the control of the base station, mode2: the terminal independently selects

3. C-V2X working mode

(1) V2V——Vehicle-to-Vehicle

(2) V2I - vehicle and infrastructure

(3) V2N - between the vehicle and the network

(4) V2P - between cars and pedestrians

4. C-V2X communication interface - correspondence between different working modes and interfaces

(1) Uu——cellular network communication interface (used under network coverage)

(2) PC5 - short-distance interface between vehicles, people and roads (direct communication)

5. C-V2X module

(1) OBU: On-board unit

(2) RSU: road side unit

2. 5G+artificial intelligence - how to unite and what is the significance?

  1. process status
  2. algorithm
  1. linear regression 

①Learning algorithm: least square method; gradient descent method;

② Fitting results: overfitting; underfitting; - regular term, regression model

③ Model effect judgment

(1) neural network

(2) Decision tree

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Origin blog.csdn.net/m0_58547949/article/details/126974977