The document discusses work on a thesis about artificial intelligence in wireless networks. It includes introducing network slicing and neural methods, reading documentation on reinforcement learning tools like Gym and Sacred, running simulations with the Nokia wireless suite and observing results with MongoDB, implementing Q-learning in Python and Matlab, and working to optimize resource allocation and improve efficiency. The goal is to apply reinforcement learning techniques to problems in frequency allocation for wireless networks.

1. Politecnico di Milano - AmirhoseinAtaei 1
25/09/2020 (sep)
- Introduce the network slicing in 5g and 6g also neural methods
- Introduce the nokia wireless suite
full thesis
Artificial intelligence in the air

2. Politecnicodi Milano - AmirhoseinAtaei 2
Considering INI
Network slicing
https://ieeexplore.ieee.org/abstract/document/8476595

3. Politecnicodi Milano - AmirhoseinAtaei 3
Nokia
github

4. 09/19/2020 (oct)
- Read the gym and sacred documentation also deep learning
- Run the nokia wireless suite with observer
Politecnico di Milano - AmirhoseinAtaei 4
full thesis
Artificial intelligence in the air

5. GYMENVIRONMENT
SACRED CONFIGURATION
Politecnicodi Milano - AmirhoseinAtaei 5
Wireless-suite develop

6. Politecnicodi Milano - AmirhoseinAtaei 6
REINFORCEMENTLEARNING
Machine learning
https://youtu.be/kopoLzvh5jY

7. ADD TO PATH
Politecnicodi Milano - AmirhoseinAtaei 7
Package should be add to path list

8. IMPORTMONGODB AS OBSERVER
Politecnicodi Milano - AmirhoseinAtaei 8
Should be import mongo observer

9. PORT AND HOST
DATA BASEPATH
Politecnicodi Milano - AmirhoseinAtaei 9
Configuration of mongodb

10. CREATE DB AND USER TO ACCESS
RUN MONGOSHELL
Politecnicodi Milano - AmirhoseinAtaei 10
Running mongodb and it’s shell

11. COMPASSGUI
Politecnicodi Milano - AmirhoseinAtaei 11
See the data in GUI mongodb compass

12. RUN LAUNCH AGENTACCORDINGCONFIGFILES
Politecnicodi Milano - AmirhoseinAtaei 12
Run the simulation

13. REWARD VALUE AS RESULT
Politecnicodi Milano - AmirhoseinAtaei 13
Get the reward number

14. STORED DATA
Politecnicodi Milano - AmirhoseinAtaei 14
Evaluate all the datas that are saved

15. MAKE ENVIRONMENT
Politecnicodi Milano - AmirhoseinAtaei 15
Gym environment

16. GYMENVIRONMENTEXAMPLE
Politecnicodi Milano - AmirhoseinAtaei 16
Test open ai gym

17. Politecnicodi Milano - AmirhoseinAtaei 17
Matlab
reinforcement learning
https://it.mathworks.com/products/reinforcement-learning.html

18. Politecnico di Milano - AmirhoseinAtaei 18
26/10/2020 (oct)
- Exploit all the specification of q-learning python program
- improve the time efficiency
full thesis
Artificial intelligence in the air

19. Politecnicodi Milano - AmirhoseinAtaei 19
Virtualy run on top of powerful HW
Powerful resource

20. Politecnicodi Milano - AmirhoseinAtaei 20
Q-learn
https://www.youtube.com/watch?v=e3L4VocZnnQ
Find and solve the problem of UMTS-OLPCcode Related to number of episodes

21. Politecnicodi Milano - AmirhoseinAtaei 21
Run the episodes
Output plots

22. Politecnico di Milano - AmirhoseinAtaei 22
10/11/2020 (nov)
- Solve the problems of q-learning python program
- change the configuration and compare result
full thesis
Artificial intelligence in the air

23. Politecnicodi Milano - AmirhoseinAtaei 23
Fix the problem of plots
Solve the problem and now We have two plot with different scale in figure one

24. Politecnicodi Milano - AmirhoseinAtaei 24
Change the result with different parameter
Comparing results with change config file

25. CONFIGparameterslike carrier frequency
Politecnicodi Milano - AmirhoseinAtaei 25
Parameters that we can change

26. Politecnico di Milano - AmirhoseinAtaei 26
01/12/2020 (dec)
- find split in time frequency file
- implement qlearn in time frequency program
full thesis
Artificial intelligence in the air

27. Politecnicodi Milano - AmirhoseinAtaei 27
Frequency resource allocation
FRA