GSOC2024RLUsability5G: Difference between revisions
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* '''Mentors:''' Amir Ashtari, Katerina Koutlia, Bijana Bojovic, Gabriel Ferreira | * '''Mentors:''' Amir Ashtari, Katerina Koutlia, Bijana Bojovic, Gabriel Ferreira | ||
* '''Google page:''' https://summerofcode.withgoogle.com/programs/2024/projects/vPuZgTe1 | * '''Google page:''' https://summerofcode.withgoogle.com/programs/2024/projects/vPuZgTe1 | ||
* '''Project Goals:''' In this project, I will | * '''Project Goals:''' In this project, I will design a new RL based MAC scheduler of NR and implement it in 5g-lena integrating with ns3-gym. Additionally, I will enhance the usability of 5G-lena in terms of RL approach by providing an example using the designed RL based scheduler. | ||
* '''Repository:''' https://github.com/mye280c37/GSoC-2024 | * '''Repository:''' https://github.com/mye280c37/GSoC-2024 | ||
* '''About Me:''' I am currently pursuing a Master's degree in Computer Science and Engineering at Seoul National University, Korea. My research at the Mobile Computing & Communications Laboratory focuses on resource allocation methods in NR V2X Sidelink. As an undergraduate, I conducted research on improving spatial reuse in dense Wi-Fi environments and implemented a Reinforcement Learning (RL)-based modified OBSS/PD algorithm using ns3 gym. I believe that participating in GSoC 2024 presents an excellent opportunity for me to contribute to enhancing the usability of 5G and RL experiences on ns-3, while also deepening my understanding of 5G technology, mechanisms, and system architecture. | * '''About Me:''' I am currently pursuing a Master's degree in Computer Science and Engineering at Seoul National University, Korea. My research at the Mobile Computing & Communications Laboratory focuses on resource allocation methods in NR V2X Sidelink. As an undergraduate, I conducted research on improving spatial reuse in dense Wi-Fi environments and implemented a Reinforcement Learning (RL)-based modified OBSS/PD algorithm using ns3 gym. I believe that participating in GSoC 2024 presents an excellent opportunity for me to contribute to enhancing the usability of 5G and RL experiences on ns-3, while also deepening my understanding of 5G technology, mechanisms, and system architecture. | ||
= Milestones = | = Milestones = |
Revision as of 11:28, 29 May 2024
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Project Overview
- Project Name: Enhancement of RL Approach Accessibility in NR
- Student: Hyerin Kim
- Mentors: Amir Ashtari, Katerina Koutlia, Bijana Bojovic, Gabriel Ferreira
- Google page: https://summerofcode.withgoogle.com/programs/2024/projects/vPuZgTe1
- Project Goals: In this project, I will design a new RL based MAC scheduler of NR and implement it in 5g-lena integrating with ns3-gym. Additionally, I will enhance the usability of 5G-lena in terms of RL approach by providing an example using the designed RL based scheduler.
- Repository: https://github.com/mye280c37/GSoC-2024
- About Me: I am currently pursuing a Master's degree in Computer Science and Engineering at Seoul National University, Korea. My research at the Mobile Computing & Communications Laboratory focuses on resource allocation methods in NR V2X Sidelink. As an undergraduate, I conducted research on improving spatial reuse in dense Wi-Fi environments and implemented a Reinforcement Learning (RL)-based modified OBSS/PD algorithm using ns3 gym. I believe that participating in GSoC 2024 presents an excellent opportunity for me to contribute to enhancing the usability of 5G and RL experiences on ns-3, while also deepening my understanding of 5G technology, mechanisms, and system architecture.
Milestones
Phase1. Design example (3 weeks)
- Familiar with 5g-lena (2 weeks)
- Design Scenario (e.g., UEs deployment, UEs speed, cell configuration, …) (1 week)
- - Define Assumption (e.g., delay, TDMA/OFDMA, …)
Phase2. Design RL based Scheduler (6 +1 weeks)
- Design scheduler (2 weeks)
- - input/output
- - goal of optimization
- Design RL process (1 week)
- - Define suitable RL techniques considering optimization objective of the scheduler and computational complexity
- Implementation of RL based scheduler in 5g lena (3 +1 weeks)
- - Create the test
- - Create documentation
- - Create MR to 5g lena (Milestone 1)
Phase3. RL Integration (4 weeks)
- Design RL framework (1 week)
- - Define RL technique
- Develop gym scripts (3 weeks)
- - Develop gym python scripts
- - Develop ns3 gym interface in RL 5g lena example
- - Validate RL process of the example
- - Create MR to 5g lena (Milestone 2)
Phase4. Evaluation (3 +1 weeks)
- Evaluate the result of example compared with other schedulers
- - Write simulation campaign scripts
- - Execute scripts
- - Plotting python scripts
- Address review comment of the MR 1 and 2
- Update MR 1 and 2 with necessary modification
- Create brief description of the work and the results for 5g lena blog (Milestone 3)