GSOC2024RLUsability5GFinalReport
Project Overview
- Project Name: Enhancement of RL Approach Accessibility in NR
- Student: Hyerin Kim
- Mentors: Katerina Koutlia, Amir Ashtari, Bijana Bojovic, Gabriel Ferreira
- 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.
- Project Proposal: https://summerofcode.withgoogle.com/programs/2024/projects/vPuZgTe1
- Project Wiki: GSOC2024RLUsability5G
Merge Requests and Commits
I maintained a single branch for all work during GSoC: gsoc24-nr-usability
Merge Requests
All the following activities can be easily reviewed on the following MR:
No. | Name | Status |
---|---|---|
[1] | Draft: GSoC2024: RL-based Scheduler | Draft |
Milestones
During the project, I pushed 170+ commits and squashed them to about 70 commits for merge. I managed all commits during the work in my personal repository, named "5g-lena-integrated-with-ns-3-gym/gsoc24-nr-usability" by organizing them into milestones and issues
No. | Name | Period |
---|---|---|
[1] | Design Scenario | Jun 10, 2024–Jun 17, 2024 |
[2] | Drafting an AI scheduler | Jul 11, 2024–Jul 17, 2024 |
[3] | Develop an RL-based scheduler | Jul 18, 2024–Jul 24, 2024 |
[4] | Update the RL-based Scheduler (Code Refactoring) | Jul 24, 2024–Jul 31, 2024 |
[5] | Create test | Jul 29, 2024–Aug 11, 2024 |
[6] | Develop Gym Interface in "cttc-nr-rl-based-sched" Example | Aug 12, 2024–Aug 25, 2024 |
[7] | Develop Gym Python Scripts | Aug 21, 2024–Oct 2, 2024 |
[8] | Resolve comments in MR: cttc-lena/nr!166 | Sep 2, 2024–Oct 6, 2024 |
Project Details
Phase 1: Design example
During this phase, I became familiar with 5g-lena by studying cttc-nr-demo example and cttc-nr-demo tutorial, and analyzed the existing schedulers in 5g-lena (i.e., QoS, PF, RR) through cttc-nr-simple-qos-sched example, cttc-nr-multi-flow-qos-sched example, and NR module documentation.
Based on this studies, I designed draft scenario which be applied RL-based scheduler.